AI Appreciation Day Quotes and Commentary from Industry Experts in 2026

For AI Appreciation Day 2026, the editors at Solutions Review have compiled a list of quotes, predictions, and commentary from leading experts across industries.

As part of this year’s AI Appreciation Day, the Solutions Review editorial team called for the best and brightest minds in the enterprise technology market to share best practices, predictions, and personal anecdotes about the human impact of artificial intelligence. The experts featured represent some of the top influencers, consultants, and solution providers with experience across industries, and each projection has been vetted for relevance and ability to add business value.

AI Appreciation Day Quotes from Industry Experts in 2026

Addie Achan, Aspen Policy Academy Fellow and Founder of The Kaleidoscope Project

To me, appreciating AI means understanding its potential to promote human flourishing, as well as the need for deliberate action to realize it. Throughout our history, humanity has thrived by being the most capable, efficient, and intelligent beings on Earth. Traditionally, technology has enabled this by reacting to our decisions and taking our actions further. AI introduces a new paradigm in which technology itself proactively makes decisions and executes actions.

This makes the next couple of years a critical inflection point, as how AI is governed and developed can change the trajectory of our species. If done right, AI could help us approach utopia by eradicating diseases, ending hunger, and shifting our daily focus from survival to joy and fulfillment. But if mismanaged, AI could exacerbate inequalities, enable widespread surveillance, and destroy our planet.

Appreciating AI means recognizing that the choices we make now will shape the future of humankind. We must use an intersectional lens and draw expertise from diverse disciplines. Doing so will help us understand critical questions like: What does it mean to be human? What constitutes a genuine human connection? And where do we draw the line between raw efficiency and human touch?

I’ll admit these questions intimidate me, but I have hope because, unlike AI, we possess resilience and a moral compass to help us do the right thing. On ‘AI Appreciation Day,’ we should remember that an optimistic future is possible through human-centered thoughtfulness.

Shiv Agarwal, Co-Founder and CEO at Singulr AI

AI Appreciation Day is the perfect moment to move past the hype and understand how AI can actually create value inside an enterprise. That value isn’t simply created through better models, more tools, or agents. AI creates value when people can use it to eliminate painstakingly repetitive tasks, make better decisions, experiment safely and securely, and move faster.

The challenge in 2026 is that most organizations are trying to govern a constantly evolving, dynamic technology with processes built for a much slower generation of software and controls that have become fragmented over time. Employees are using these new tools before IT and security teams have had a chance to review them; new AI features appear in SaaS applications without as much as a notification; and, on top of that, agents are starting to take actions across systems. The cost of using AI is skyrocketing without proper usage oversight and optimization controls. Governance can’t just apply to a policy or onboarding document anymore; it has to operate in real-time, where AI is actually being used.

True AI appreciation means recognizing both the technology’s promise and the reality of how it operates within a given organization. To get the most value from AI, your company needs visibility, clear digital and interpersonal controls, training, and the confidence to keep internal policies aligned with the real world as AI continues to gain autonomy.

Sammy Ahmed, VP and GM at name.com

AI fundamentally changes who gets to build. Tasks that once required deep technical expertise, significant time, or an entire team can now be accomplished by a single person with the right AI tools. That shift is giving entrepreneurs, developers, and creators the freedom to prototype faster, experiment more often, and turn promising ideas into real products. As these tools continue to evolve, they’ll make it even easier for builders to tackle bigger problems, explore new business models, and bring entirely new ideas to market. AI Appreciation Day is a great opportunity to celebrate how far the technology has come and the possibilities it continues to create for the next generation of builders.

Karl Bagci, Director of IT and Information Security at Exclaimer

One thing AI has made me appreciate more is that the technology is forcing us to redefine what makes people valuable at work. We spent decades optimizing for speed and efficiency because machines couldn’t think. Now machines can help with both. The skills that become more valuable are critical and strategic thinking, judgment, accountability, empathy, and the ability to build trust. AI isn’t reducing the importance of people. It’s raising the importance of the qualities that only people bring.

Husnain Bajwa, SVP of Product, Risk Solutions, at SEON

AI’s real value in fraud prevention isn’t the model, it’s what you feed it. The teams winning are the ones grounding AI in rich, trusted signal data, device history, behavioral patterns, and network context, so the model can tell a fraudster from a legitimate customer.

That’s only effective if teams aren’t locked into one vendor’s black box. AI should adapt to how a fraud team already works, not the other way around. Give analysts the freedom to choose their models, pair that with data they can actually trust, and you get detection that improves as fast as the threats do. On AI Appreciation Day, that’s worth remembering: the technology only appreciates in value when the humans running it stay in control.

Ashish Bansal, CEO and Founder of StarSpark.AI

AI Appreciation Day should be about how it can have positive outcomes for people, like equitable access to learning, rather than being a celebration of algorithms. It should be a reminder that the purpose of AI is human empowerment. For the first time, we can give every student personalized support, not just those who can afford tutors or attend elite schools. AI works to empower teachers and students alike; it should give every student the support they need while allowing teachers to spend more time inspiring and mentoring. The real promise of AI isn’t better technology, it’s better outcomes for people.

Josh Bartolomie, VP, Global Head of Threat Intelligence at Doppel

AI is the most transformative technology I’ve seen in more than two decades in cybersecurity, and I believe we’re only beginning to understand its potential. Across industries, it’s accelerating discovery, solving increasingly complex problems, and enabling people to work with more information than ever. In cybersecurity, where teams are constantly overwhelmed by the volume and complexity of threats, AI is helping defenders process vast amounts of data, uncover patterns that would otherwise be missed, and turn an overwhelming volume of signals into meaningful intelligence. That’s what makes AI worth celebrating.

That said, like every major technological breakthrough, AI brings both opportunity and new challenges. Within cybersecurity, we’re seeing attackers use AI to scale phishing, impersonation, and social engineering attacks at a pace we’ve never seen before. The answer isn’t to slow AI innovation; it’s to ensure defenders can evolve just as quickly. That means building AI-native security that combines powerful models with rich, contextual threat intelligence so teams understand not just what’s happening, but why it matters and what action to take.

AI isn’t going anywhere, and its greatest impact will come from pairing its extraordinary capabilities with trusted intelligence, context, and human judgment.

Kimberly Basile, Chief Information Officer at Kyndryl

AI is creating real opportunities for employees to move faster than before, but speed only matters if your organization is ready to move with that change. You can’t just roll out technology for technology’s sake – every new tool must come with a thought-out strategy for redesigning work around it, including the investment in skills and training to help people work with it. In fact, our recent research showed that just about a quarter of leaders feel their organizational culture and workforce are ready to successfully use AI. This means there’s a lot of work to be done to help people work better with AI. Those that are able to effectively bring their people along the journey of AI readiness will gain the greatest business value from AI.

Jay Bavisi, Founder and CEO of EC-Council Group

AI Appreciation Day is a useful moment to recognize how deeply AI has entered everyday work. But appreciation should not be confused with uncritical adoption. The more mature conversation is about what it takes to adopt AI responsibly, defend the systems it touches, and govern its use with discipline.

AI is no longer only a productivity tool that helps people write, search, or analyze faster. It is moving into workflows where it can recommend actions, trigger processes, access data, and influence decisions. That changes the responsibility for every organization using it. The question is not simply how much AI can improve productivity, but whether leaders understand where it is being used, who is accountable for it, how it is secured, and when human judgment must intervene.

For AI to be sustainable, organizations have to look beyond immediate efficiency gains. The real measure is whether AI can be scaled without weakening trust, increasing unmanaged risk, or leaving people unprepared for the decisions these systems now influence. A system that is powerful but poorly understood, widely used but weakly governed, or difficult to secure will eventually create more pressure than progress.

The real test for enterprises is not whether they can deploy more AI. Most already can, and many already are. The test is whether their people are prepared to work with AI, question its outputs, defend against its misuse, and govern autonomous action before it creates business risk.

That is what AI Appreciation Day should remind us of. The future of AI will not be shaped by enthusiasm alone. It will be shaped by the discipline organizations build around AI: Adopt. Govern. Defend.

Luis Blando, Chief Product and Technology Officer at OutSystems

Despite the hype around fully autonomous systems, most enterprises today are using AI in far more practical ways, and that’s where the real value is showing up. The strongest use cases cluster around three areas: processing documents that would otherwise require human review, handling high-volume transactional work, such as mapping incoming orders, and supporting decision-making by making sense of unstructured data. In these scenarios, AI excels at summarizing complexity and offering recommendations, but not at making final calls, unless organizations are willing to accept mistakes.

Used poorly, AI behaves like a team of interns: fast and prolific, but still requiring oversight and double-checking. Used well, it becomes a force multiplier for simpler applications, especially when fueled with the right data and guardrails. Trust doesn’t come from autonomy alone. It comes from knowing when AI should assist, when humans should decide, and how the two work together.

Jody Brazil, Founder and CEO at FireMon

On National AI Day, some will focus on the potential and exponential gains achieved, while others will call it a harbinger of overwhelming risk and exposure–and advocate fighting AI with AI. For the AI Arms race camp, I’d advocate that a massive segment of risk and potential blast radius from AI can be measurably reduced by taking a hard look at the fundamentals of security visibility, governance, and control that have fallen victim to the increasing complexity of hybrid environments and security infrastructure sprawl. Our own analysis of 9.2 million policy checks found 58 percent of firewalls showed high-severity compliance failures and 48 percent showed critical-severity failures. While no one thing is a silver bullet, establishing a control plane over the policies that define access will create more opportunity for AI deployments and less friction from security controls.

Shane Buckley, President and CEO, Gigamon

AI Appreciation Day comes at an important moment in the technology’s evolution. We’ve moved beyond asking whether AI belongs in the enterprise. The conversation is now centered on how organizations operate in the Mythos era, where increasingly capable AI models and agents are changing the economics of work, innovation, and cybersecurity. Capabilities that once required specialized expertise, significant time, or large teams are becoming dramatically more accessible. That creates tremendous opportunity, but it also changes how organizations compete, innovate, and manage risk. The growing cost of AI is also becoming a barrier to wide-scale deployment across organizations. Given the massive investment in infrastructure by leading AI companies, token costs are expected to continue to soar, putting even more pressure on IT budgets and forcing some important investment trade-offs.

As AI becomes embedded across business-critical systems, leaders need a clear understanding of how models, agents, and AI-powered workloads interact with their data and infrastructure. Visibility into AI activity is becoming just as important as the AI itself, providing the context organizations need to strengthen security, govern these systems responsibly, make better decisions, and provide better cost/ROI controls to ensure spend is aligned to return. The organizations that create lasting value from AI will be the ones that invest as much in visibility, governance, and operational discipline as they do in the technology itself.

Phil Calvin, CPO at Delinea

AI Appreciation Day is a moment to reflect on how artificial intelligence is transforming organizations so that they can innovate faster, defend against cyber threats, and operate more efficiently at scale. However, the same advancements that are supercharging security programs today are also giving cyber-criminals new tools to create highly personalized attacks, automate malicious activity, and exploit overprivileged systems.

As organizations race to integrate AI into their operations, they must ensure their security posture is evolving alongside it. AI agents must be treated as privileged identities, with strong access controls, much as an employee would. AI’s greatest value won’t come from how quickly it’s adopted, but from how securely and reliably it’s deployed.

John Cannava, Chief Information Officer at Ping Identity

Organizations are increasingly deploying AI agents across the enterprise, and the opportunities for innovation and efficiency are tremendous. These systems are doing more than just responding to prompts. They’re making decisions, taking actions, and even spawning new agents with increasing autonomy and speed. That evolution is transforming how work gets done and reshaping the security landscape.

Now the challenge is that many organizations are adopting AI agents faster than they can establish clear identity, accountability, and governance for them. When you can’t definitively answer what an agent did, why it did it, or under whose authority it acted, you create unnecessary risk and uncertainty. This is why identity for AI must become a foundational priority. Every agent needs a verifiable identity with clear permissions and continuous oversight, just like any human user or service account. By building trust, visibility, and accountability into AI from the start, organizations can unlock the full potential of autonomous AI while managing risk and strengthening security.

Dr. Diana Cano, CIO at Cambium Learning Group

Over the last year, we’ve learned that successful enterprise AI adoption isn’t just about providing everyone with access to new tools. It’s about empowering employees to use AI in ways that allow them to do the work they genuinely want to do. When AI takes on routine tasks, employees have more time to make a tangible impact – whether that’s by helping a customer solve a problem or giving an educator more time to focus on student progress.

As AI continues to evolve, the opportunity isn’t just to complete work more quickly. It’s to spend more time on work that requires human judgment, creativity, and connection. Investing resources to achieve that outcome is worth it.

Jerry Carter, Chief Technology Officer at Nasuni

AI Appreciation Day is a good time to pause and consider what truly will drive AI success within your organization. While enterprises are moving quickly to deploy AI, many are still struggling to achieve the outcomes they expected. In fact, recent data shows that while 97 percent of enterprises have deployed or are piloting AI, only 43 percent of AI projects are achieving their intended objectives, and nearly half say AI initiatives have exposed data quality and governance issues. The data points to a new conversation: that AI success depends on how well organizations manage and prepare their data. Too many enterprises are still relying on outdated approaches to unstructured data management, limiting their ability to unlock the full value of their proprietary operational data that powers meaningful AI.

At the same time, AI is reshaping far more than just applications and workflows. It is also redefining the infrastructure assumptions enterprise IT has relied on for years. As demand for AI infrastructure continues to place pressure on the global memory and storage supply chain, hardware procurement is becoming less predictable, forcing organizations to rethink operating models built around stable refresh cycles and long-term capital planning. The economics of enterprise infrastructure are changing, making it more difficult for IT leaders to plan, scale, and control the data environments their AI initiatives depend on.

It’s worth noting that AI is revealing these problems, not creating them. At a time of rising hardware costs, supply chain uncertainty, and growing infrastructure complexity, getting your data house in order is the ultimate no-regrets move. To achieve long-term value from AI, organizations need to reduce dependence on unpredictable hardware cycles and ensure their unstructured data is accessible, governed, and ready for both employees and the AI that supports them.

Chao Cheng-Shorland, CEO of ShelterZoom

AI has shifted outcomes from the aspirational to the practical. In highly regulated industries such as healthcare, AI solutions deliver the most value by helping professionals spend less time on administrative tasks and more time on the work that matters. This is where AI earns trust and delivers lasting value.

Ziv Cohen, Director of Data & AI at Cust2Mate

When e-commerce has conditioned consumers to expect personalized recommendations, relevant promotions, transparent pricing, and instant product information, the physical store must also deliver on those promises. Today, AI can bridge this gap.

In fact, the future of brick-and-mortar isn’t about competing with online shopping. It’s about combining the strengths of physical retail with the personalization consumers already experience online. Our research shows that shoppers aren’t asking retailers for more AI. They’re asking for better experiences. They want to find products faster, understand pricing more easily, discover relevant promotions, and complete purchases without unnecessary friction.

The opportunity for retailers is clear. Only 36 percent believe supermarkets consistently deliver the fast, hassle-free shopping experience consumers now expect. Another 68 percent say real-time visibility into pricing, discounts, and basket totals is important, yet only 48 percent believe stores provide it. AI, smart carts, and connected in-store technology can provide this. Looking forward, the true potential lies in the deployment of specialized AI agents. Unlike passive systems, these autonomous agents can proactively anticipate shopper needs in real-time, optimize store operations on the fly, and act as a personalized digital assistant for every customer right on the cart.

Consequently, success won’t be defined by how much AI a retailer deploys, but by whether customers feel the experience has become more intuitive, transparent, and convenient. The future of physical retail will belong to retailers that bring digital-age experiences into the store. AI succeeds when customers don’t notice the technology itself; they simply notice that shopping feels easier.

Henry Comfort, Co-Founder and CEO of Geordie AI

AI Appreciation Day is a good reminder that the conversation has moved well beyond whether AI works. Through our customers, we’ve seen what AI agents can accomplish when organizations have the confidence to put them to work. They’re accelerating workflows, taking repetitive tasks off people’s plates, and helping teams move much faster than they could on their own.

That confidence doesn’t come from the models themselves. It comes from understanding what AI agents can access, how they behave, and having the right governance in place to keep them operating safely. The organizations getting the most value from AI aren’t necessarily using the most advanced models. They’re the ones getting the controls in place that let their teams adopt AI agents with confidence. That’s what I’m most excited to see as AI agents continue to mature over the next year.

Steve Conner, President at EdgeCore Digital Infrastructure

AI Appreciation Day isn’t just about celebrating how far we’ve come with AI. It’s also about recognizing the physical infrastructure making these advances possible. Every new model and application depends on digital infrastructure to support unprecedented computing demands. AI adoption will only accelerate from here, and data centers will continue to be foundational to innovation across every industry.

To stay ahead, the next wave of AI infrastructure must be able to handle more power, utilize advanced cooling methods, and support denser workloads. As demand for AI capacity grows, data center developers play an important role in delivering the reliable infrastructure that organizations need with certainty and confidence. Appreciating AI also means appreciating the infrastructure underneath it all.

Michael Curry, President of the Data Modernization Business Unit at Rocket Software

AI is creating new opportunities for organizations to extract greater value from the systems and data they already rely on every day. For enterprises, this includes the mainframe, which continues to support many of the world’s mission-critical infrastructure while housing decades of high-value operational data. As organizations expand AI initiatives, securely connecting these environments to modern AI workflows will play an important role in improving decision-making, accelerating innovation, and delivering business outcomes.

As AI Appreciation Day highlights the growing impact of AI across industries, it’s also a reminder that long-term success depends on access to trusted enterprise data. Realizing that value depends on making trusted enterprise data accessible without sacrificing governance, security, or reliability. Advancements in AI automation and real-time data integration are helping organizations extend the value of their core systems by making mainframe data available across hybrid environments. AI is giving organizations new ways to leverage their existing information, and businesses that combine trusted data with modern AI capabilities will be well-positioned to scale their initiatives with confidence.

Adam Field, Chief AI Officer of Tungsten Automation

There’s something very on-brand for our industry about inventing a holiday to appreciate our own technology. If we’re not careful, the agents will start expecting cards. So much attention this year has been captured by the rapid evolution of AI models, agents, and new capabilities—flashy this and flashy that. I’ve always been a firm believer that the biggest factor determining true enterprise AI success stems directly from the work happening behind the scenes. This year, we’ve witnessed a massive wave of organizations quickly realizing that measuring AI adoption through metrics like token usage is no longer a feasible way to evaluate ROI. As a result, the industry was forced to take a healthy step back and really think about what it truly means to unlock value from AI.

At the core of it all, it’s always been about improving processes, enhancing decision-making, and delivering measurable business outcomes. Achieving that comes from foundational work around data readiness, system access, security controls, compliance, and governance.

The future of enterprise AI will be built on what I call ‘boring AI.’ And what I mean by this is the critical foundational work that may not generate headlines but enables organizations to innovate responsibly and at scale. But technology is only half the equation. The other half is the people you enable to use it, and if you invest in one without the other, you will fail. Deploying AI tools is the easy part, but creating the right environment for AI to deliver value is where the real transformation happens. So, I’ll leave you with this. The next generation of AI leaders will be the ones who look beyond the latest models and usage metrics to focus on outcomes, asking investors and companies what outcomes AI is creating rather than simply what AI they are deploying.

Dr. Stanislav Fort, Co-Founder, Chief Scientist, CTO at AISLE

AI Appreciation Day is a reminder of how far the technology has come in a remarkably short time. Having spent years building frontier AI models, I’ve seen that progress firsthand. But one lesson has become increasingly clear: raw model capability is only part of the story.

In cybersecurity, it’s critical that we consider everything around the model. In doing so, we give it the right context, ground its reasoning, and design systems that security teams can trust when the stakes are highest. Frontier models will continue to improve, which is worth celebrating, but the next wave of innovation will come from the systems that reliably turn models’ capabilities into positive security outcomes.

Aaron Fulkerson, CEO of OPAQUE Systems

AI Appreciation Day should come with a reminder: AI’s future depends on whether people can verify its actions, not just trust promises they’re asked to accept. Public skepticism around AI is not a communications problem. It’s an architecture problem. As AI agents handle more sensitive data, make more decisions, and operate across more systems, the industry can’t continue to rely on a ‘trust us’ model. The early web faced a similar turning point when HTTPS replaced promise with proof. AI now needs the same shift. To truly appreciate AI as a force for progress, we need collaboration across the ecosystem to make verifiable privacy and policy enforcement foundational to how AI is built, deployed, and used.

Munu Gandhi, President of Xerox IT Solutions and Chief Technology Officer at Xerox

AI Appreciation Day is an opportunity to recognize how quickly artificial intelligence is evolving from a technology innovation into a core business capability. As organizations move beyond experimentation, the real value of AI will be measured not by the insights it generates, but by the business outcomes it enables, from improved productivity and faster decision-making to better customer experiences and more efficient operations.

At Xerox, we are helping organizations apply AI across documents, workflows, and IT environments to simplify complexity, automate routine work, and create more connected, intelligent operations. The organizations that will lead in the years ahead will be those that combine human expertise with AI-driven capabilities to accelerate execution, enhance agility, and unlock new opportunities for growth and innovation.

Ashutosh Garg, CEO and Co-founder at Eightfold AI

AI Appreciation Day should be a reminder that adoption matters more than admiration. According to Gallup, 65 percent of employees in organizations that have implemented AI say it has improved their productivity and efficiency, yet only 12 percent strongly agree that AI has fundamentally changed how work gets done in their organization. That gap is the real story.

Yrieix Garnier, VP of Products at Datadog

Nearly 70 percent of organizations are already using three or more AI models, underscoring how quickly AI is changing the way companies operate. As AI becomes increasingly autonomous—detecting issues, remediating incidents, validating releases, writing and shipping code—the question is no longer what the software can do. The question now is whether an organization can see what AI is doing, govern when it acts, and trust it when it matters.

To reach that level of trust and operational control, successful AI implementation hinges on whether companies have unified visibility across the whole system—infrastructure, applications, security, and AI workloads.

Sudeep George, Chief Technology Officer at iMerit

When people celebrate AI, they usually picture the model, not the person who spent hours working with it, challenging it, and correcting it until it improved.

I think about a physician I worked with on a medical imaging project. The model had confidently classified a borderline case as normal. She paused, looked more closely, and corrected it because she brought years of clinical judgment that the model lacked. That correction became part of the feedback used to improve the system’s handling of similar cases in the future.

That is the story I keep coming back to on AI Appreciation Day. Real progress in AI depends on the expert human judgment that teaches models where their confidence should end and humility should begin.

AI Appreciation Day is an opportunity to recognize how rapidly AI has evolved, but also to raise the bar for what meaningful progress looks like.

As AI agents move from answering questions to taking actions across enterprise systems, the real test is not whether they perform well under ideal conditions but whether they behave safely and reliably when information is incomplete, workflows break down, and the consequences of an error are significant.

There’s a fundamental difference between AI that appears correct and AI that is operationally correct. The next phase of agentic AI will require more than static benchmarks. It will require real-world “driving tests” that evaluate how agents handle ambiguity and edge cases, remain within defined boundaries, recover from failure, and recognize when human intervention is needed.

Human experts remain essential to designing these evaluations and defining what safe behavior means in a specific context. Healthcare, mobility, and agriculture have already demonstrated that reliability is often determined by how a system handles the exception, not just the routine case.

AI delivers its greatest value not when it acts alone, but when rigorous evaluation and human judgment make its actions dependable and trustworthy.

Robin Gilthorpe, CEO of Earnix

The best insurers have always relied on experience, judgment, and an understanding of people. AI shouldn’t replace those qualities. It should strengthen them. By taking on the work of connecting information and identifying patterns across millions of decisions, AI gives underwriters, actuaries, and claims professionals more time to focus on what people still do best: applying expertise, exercising judgment, and helping customers through some of the most important moments in their lives.

Jason Gladu, Chief Alliances Officer at Convertr

Most people talk about AI in terms of what it can do, but there’s a real person on the other end of a lot of these decisions. When a company lets AI act on data that hasn’t been properly governed, it shows up as the wrong offer, the wrong denial, or someone’s information being used in a way they never agreed to. It happens fast inside organizations, too. Teams are adopting AI tools quicker than leadership can track, and the people who end up accountable for the outcome often don’t even know the tool is running. The human impact of AI has less to do with job displacement and more to do with whether the systems making decisions about customers and employees are working off data that those people can actually trust. Get the data right, and AI ends up protecting people instead of putting them at risk.

Michael Gray, Chief Technology Officer at Thrive

AI Appreciation Day is a good opportunity to recognize how quickly artificial intelligence is evolving, but it is also a reminder that successful AI adoption is not about moving as fast as possible. The organizations seeing the greatest return are taking a “crawl, walk, run” approach by building foundational knowledge, helping employees understand and trust the technology, and introducing AI with a clear purpose. Buying the latest tools is easy. Building a workforce that knows how to use them effectively is what creates lasting value.

Getting the foundation right changes the AI conversation altogether. Instead of asking, “How can we use AI?” the better question is, “What business problem are we trying to solve?” If you don’t know what problem you’re trying to solve, AI probably isn’t the place to start. Once you understand the business need, AI can help accelerate analysis, uncover new ideas, and improve execution. However, not every AI use case is worth pursuing. Without a clear purpose, organizations can end up taking on more work than they solve. AI should strengthen what already makes your organization unique, not replace the expertise that differentiates it.

As AI becomes part of more business processes, human judgment becomes even more important. AI can dramatically increase productivity, but it’s humans that remain responsible for validating outputs, providing context, and making the final decisions. Organizations that invest in education, governance, and thoughtful adoption today will be best positioned to scale AI responsibly and realize its long-term potential.

Cobus Greyling, AI Evangelist at Kore.ai

AI Appreciation Day is a reminder of how far we’ve come. I’ve had the chance to watch this field evolve through every phase: prompt engineering, RAG, agents, orchestration, and now harness engineering. What I appreciate most isn’t any single breakthrough. It’s the maturity we’ve built around AI technology. Better control, stronger guardrails, and a shared language for designing these systems.

For me, that’s what AI Appreciation Day is really about. Not the hype or the fear, but the steady engineering progress that’s turning something remarkably capable into something people can actually trust and use.

Garrett Gross, Field CISO at Portnox

AI Appreciation Day is a good reminder to define what AI agents actually are inside a business: they’re not just software, but identities. They authenticate. They move laterally. They touch sensitive data, often around the clock, often without direct human oversight.

The organizations ahead of the curve aren’t the ones deploying the most AI. They’re the ones who understand exactly what an agent is allowed to do versus what it can reach. The gap between intended privilege and actual access is becoming one of the biggest governance challenges in enterprise AI.

Appreciating AI means treating agents like members of the workforce, not simply just a tool or application to install, and setting clear permissions and continuous oversight. The conversation is about building the right access controls so agents do right by the business. That’s worth appreciating, and it’s worth securing.

Rohit Gupta, CEO and Co-Founder of Auditoria

The best AI implementations are surprisingly quiet. They don’t ask people to change who they are or how they think. They remove the work that gets in the way. When finance professionals spend less time chasing invoices, reconciling data, or answering the same questions over and over, they have more time to do the work only people can do, like solving problems, advising the business, and making better decisions. That’s the human impact of AI.

Jessica Hammond, the Senior Director of Product Management (Gen AI) at Protegrity

While AI Appreciation Day is a moment to recognize the value AI creates for organizations, we cannot celebrate its adoption without considering the risks that come with it. AI systems are moving from content generation tools to agents that retrieve knowledge and act across enterprise workflows. The more AI is embedded into daily business, the more sensitive data moves through prompts, logs, retrieval systems, tools, and outputs.

Appreciating AI without considering how it handles data is how innovation quickly turns into liability. Reliable AI starts with data that is accurate, well understood, and managed throughout its lifecycle. Organizations need to know where data came from, how it is classified, who can access it, when it can be used, and how it is protected if something goes wrong. Those that succeed in this next phase of AI adoption will be the ones that can prove their AI is governed, protected, and secure by design.

Dale Hoak, CISO at RegScale

Artificial intelligence is rapidly changing the conversation around governance, risk, and compliance. Not by replacing people, but by eliminating the manual work that has slowed security and compliance teams for decades. For too long, organizations have relied on spreadsheets, screenshots, and point-in-time audits to answer questions that should be continuously validated. AI gives us the ability to move beyond documenting compliance and instead continuously measure, analyze, and verify it. That’s a fundamental shift. Security teams can spend less time chasing evidence and more time reducing risk, while executives gain confidence that compliance reflects the organization’s current security posture rather than a snapshot from months ago.

The real value of AI isn’t simply automation; it’s acceleration with context. Modern organizations are deploying new applications, cloud services, and AI systems faster than governance teams can traditionally keep pace. AI can correlate evidence across security tools, identify control failures, recommend remediation, and surface emerging risks in minutes instead of weeks. When combined with automation and continuous controls monitoring, organizations can achieve a level of visibility that was previously impossible without dramatically increasing headcount. In an environment where cyber threats and regulatory expectations evolve daily, AI helps organizations move faster while strengthening governance, not weakening it.

As AI continues to mature, the organizations that succeed won’t be the ones using the most AI; they’ll be the ones governing it the best. The future of compliance isn’t about preparing for the next audit; it’s about building continuous trust. AI is becoming the engine that transforms governance from a reactive, document-driven exercise into an intelligent, real-time capability that enables innovation while keeping risk under control. That’s where the real appreciation for AI should be focused, not on the technology itself, but on its ability to help organizations confidently say “yes” to moving the business forward.

Ryan Heidorn, Chief Technology Officer at C3

On AI Appreciation Day, I think less about the technology in the abstract and more about what it can make possible for teams operating under real security and compliance pressure. In the Defense Industrial Base, organizations are expected to protect sensitive government data, manage identities across increasingly cloud-native environments, and prove that CMMC controls are working in practice. That creates a constant stream of alerts, evidence, access decisions, and risk signals that can overwhelm even mature teams.

Where AI becomes especially valuable is in helping security teams turn that complexity into action. It can identify patterns faster, surface unusual access behavior, prioritize the risks that matter, support documentation, and make continuous monitoring more achievable. For contractors preparing for a CMMC assessment, that kind of speed and visibility can help bridge the gap between security that exists on paper and security that can be demonstrated day-to-day.

But appreciation should not become blind trust. AI is not a substitute for governance, accountability, or operational discipline. It can make strong processes faster and more scalable, but it cannot make weak processes defensible on its own. The organizations that will benefit most are the ones using AI to strengthen security processes they already have, not bypass them. For the DIB, that means applying AI responsibly to support identity management, assessment readiness, and stronger protection of the data our national security ecosystem depends on.

Dirk Hoerig, Founder and Chief Innovation Officer at commercetools

For years, we’ve talked about what AI might do. Now the conversation is finally shifting to what it’s actually changing. The biggest opportunity isn’t simply making people more productive. It’s enabling businesses to operate differently.

Take commerce. Every day, enterprises make thousands of decisions about pricing, inventory, promotions, fulfillment, and customer experiences. As digital commerce becomes increasingly dynamic, those decisions are becoming too fast, too interconnected, and too complex for people and traditional software to manage alone.t

That’s where AI changes the equation. It doesn’t replace human judgment. It enables businesses to make better decisions, execute them faster, and continuously adapt as conditions change, all within clear business rules and governance.

The real impact of AI is that it helps businesses operate more intelligently. Not more automation for its own sake, but better decisions, faster execution, and stronger customer experiences.

Sarah Hoffman, Director of AI Thought Leadership at AlphaSense

Over the past few years, we’ve moved from remarkable AI demos to the harder work of putting AI into production. Along the way, we’ve expanded access to data, but that’s never been the hard part. The more pressing challenge is giving LLMs the right context to connect signals, weigh evidence, and generate insights that are defensible and backed by citations – not just fast. For businesses, this standard is non-negotiable.

Organizations are now scrutinizing ROI, becoming more selective about deployments, and taking a much closer look at where AI is delivering measurable operational value. That’s a healthy sign: It means the technology is mature enough to be held to a real standard. Enterprise AI expectations are rising on every front, from cost to consequences. Businesses want to evaluate performance, manage risk, and have confidence in the outputs they’re investing in. That’s driving greater emphasis on governance and domain-specific AI that can produce trustworthy results. AI will continue to evolve quickly, but the industry is getting sharper at measuring what actually works.

Heidi Johnson, CPTO of Smart Communications

We’ve moved past the question of whether AI is here to stay. MIT and BCG’s latest research shows 86 percent of leadership teams already treat it as a core strategy. The real test now is trust: our own research found just 52 percent of consumers believe companies will use AI responsibly. In regulated industries, you don’t earn that trust by moving fast; you earn it through verification, oversight, and accountability at every step.

Matt Jones, Executive Vice President of Strategy at Cielo

Sarkis Kalashian, VP Product Management at Smartsheet

As organizations celebrate National AI Day and the rapid pace of innovation, it’s worth stepping back to ask a more important question: Does AI have the context it needs to continue delivering meaningful business value? How can AI produce better outcomes for businesses?

Organizations are adding and embedding AI into more tools and workflows, but business outcomes rarely occur within a single application. Product launches, project management, employee onboarding, etc., require people, data, and historical context to work across teams and systems. That’s where context gets lost. If you layer AI on top of disconnected work, you’re not solving the problem. You can’t automate your way out of a work coordination problem—you’ll just get to the wrong answer faster.

The organizations that are seeing the greatest returns from AI are moving beyond disconnected AI adoption. They’re connecting work end-to-end so AI can operate with shared context across teams.

The next phase of enterprise AI won’t be defined by who deploys the most agents. Everyone’s racing to give AI more horsepower, but the real unlock is giving it a map. That map is the organizational and business context, the shared understanding of how work flows across teams and systems. It’ll be defined by who gives AI that context to help people make better decisions and execute work better, not just produce more.

Joseph Kim, CEO of Druid AI

AI Appreciation Day is a good moment to ask what your AI is really delivering, not just whether it’s running. Customers across banking, healthcare, retail, insurance, and higher education have already made their expectations clear: they want help now, in their language, on their channel. We’re seeing enterprises meet those expectations every day. Banks are delivering 24/7 service to millions of customers while reducing reliance on physical branches, healthcare organizations are expanding patient access and reducing call handling times, and universities are giving students answers when critical decisions cannot wait. Our production data shows that up to 39 percent of customer demand happens outside traditional business hours, making always-on AI an essential part of the modern customer experience. The organizations embracing AI today are creating an always-available extension of their business that delivers better customer experiences while empowering employees to focus on the work that matters most. That is the lasting advantage AI will bring to the enterprise.

Timothy King, Executive Editor at Solutions Review

AI Appreciation Day is a reminder that we’re entering an era where visibility is increasingly determined by what trusted third parties say about your brand, not just what your brand says about itself.

As AI search and answer engines become a primary gateway to information, organizations need a content strategy built around authoritative editorial coverage, expert perspectives, and multimedia that creates genuine information gain.

The brands that will be cited most often are those that consistently contribute meaningful expertise through trusted media ecosystems, where articles, videos, podcasts, and expert discussions reinforce one another and give AI more authoritative signals to ingest, understand, and reference.

Matt Kunkel, Co-Founder and Executive Chairman at LogicGate

From HR and marketing to compliance and finance, there’s not a single department that doesn’t use AI in some form or another today. Yet, too many organizations hesitate at the idea of AI governance because, to them, governance means red tape, rules, and other roadblocks. But what these leaders fail to realize is that a strong AI governance framework isn’t hindering innovation – in fact, it’s exactly what your company needs to keep pace with today’s innovation and deliver real value.

With an AI governance framework in place, businesses can move forward with full visibility into their current AI landscape, a clear understanding of how AI directly ties to business goals, and immediate recognition of risks and how to mitigate them. This ensures that the AI solutions in use deliver real value while also allowing you to rapidly deploy them across departments for use cases without legal bottlenecks each time you implement a new tool.

Freddy Kuo, Chairman of Luminys Systems Corp. and Chief Executive Officer of Foxlink Group

This AI Appreciation Day, the conversation should move beyond celebrating AI for its own sake. The next chapter of AI will be defined by systems that operate reliably in the real world, support better human decisions, and deliver measurable outcomes. That requires more than powerful models. It requires an AI Factory approach: a closed-loop ecosystem where real-world data, computing, model training, solution development, deployment, and feedback continuously reinforce one another.

As AI moves into physical environments, trust will matter as much as intelligence. The most valuable AI will not replace people. It will strengthen the teams responsible for making critical decisions every day.

Unnikrshnan Kurup, the Director of Client Consulting and Strategy at Theorem

On this AI Appreciation Day, it’s important to remember that AI’s value is clearest when it helps people discover things, get educated, and make better decisions. In commerce, that is becoming more important as the path to purchase becomes more hybrid across people, content, media, and AI agents. Retail media is playing the performance role, video commerce is helping build trust and education, and AI agents are becoming a new way to help consumers make decisions.

When we think about the future of AI in commerce, it should sit where it makes everyday decisions easier and more useful. People will keep using AI when the value exchange is clear: it saves me time, it saves me money, it helps me make better decisions, and it makes my life easier.

A large share of commerce will become agent-assisted, but there will still be a separation between tasks and desires. AI agents can take over routine work like replenishment, comparison, deal hunting, delivery optimization, product filtering, and subscription management. Humans will still drive taste, identity, values, gifting, discovery, and emotional choices.

Rather than replacing people altogether, agents will become a new layer between intent and decision-making. The biggest opportunity is using AI to create convenience without taking away control. AI should help people make decisions they understand and feel confident in, not decisions they cannot explain or reverse.

Dan Kutchel, CEO at Acclaim AI

On AI Appreciation Day, we’re reminded that AI’s promise is not just about moving faster. It’s about building better, more flexible experiences for people. Ultimately, AI’s value should be measured not by the technology itself, but by the business outcomes it delivers.

AI’s most meaningful impact will be in how it expands choice for consumers, creating experiences that not only better meet an individual’s needs but also help businesses drive stronger engagement, loyalty, faster payments, and growth. In some moments, consumers will want the speed, convenience, and 24/7 availability of interacting with an AI agent. In others, they’ll want the empathy, judgment, and creativity that only a human connection can provide. The future we should be building is not one that forces a single way of interacting, but rather one that offers people flexibility and choice. It’s about giving people the right experience at the right time, with trust built into every interaction.

As voice AI and agentic systems evolve, we have a responsibility to build technology that earns trust through transparency, reliability, and thoughtful design. The companies that will succeed will empower businesses to serve consumers in ways that feel more personal, natural, and human-centered.

Laurent Landowski, Chief Product Officer at Nabla

The real shift this past year isn’t that AI got smarter; it’s that the people closest to a problem can now build the solution themselves, without waiting on engineers. A clinician can automate a workflow that used to sit in an IT backlog for 2 years. That’s where the speed comes from.

But in healthcare, speed isn’t the constraint: trust is. The moment AI touches a decision that matters, people need to see what data it used, why it landed where it did, and where a human has to sign off. Over the next year, the companies that pull ahead won’t be the ones deploying AI fastest; they’ll be the ones who do so and make it auditable. In healthcare, we don’t get to choose between the two, and that’s exactly the right pressure to build under.

Daniel Liechtenstein, CEO & Co-Founder of Hypercore

Financial institutions have a fundamentally different relationship with AI than other industries. Every action must be explainable, auditable, and backed by accurate data. So the question firms are asking has changed – no longer whether AI belongs in their business, but where it can be trusted to execute real work.

That question exposes the limits of the first wave of adoption. Most firms started with tools, chatbots, copilots, point solutions, and discovered that integrating AI and getting results from AI are two different things. A tool leaves the burden of accuracy, oversight, and accountability entirely on the firm, which is exactly the burden that regulated institutions can’t carry alone. In private credit, where portfolios are growing more complex, and investors expect more transparency, that burden lands on the operational work behind every transaction – reporting, borrower data, post-close processes that can’t run on spreadsheets and manual effort forever.

The firms preparing well are shifting their focus from which tools to adopt to how to get outcomes they can stand behind, working with partners who pair AI with institutional controls and take responsibility for the result, not just the software. Those firms won’t simply work faster. They’ll operate with greater consistency, transparency, and resilience.

Pete Luban, Field CISO at AttackIQ

The biggest surprise for companies moving AI into production is the speed. When an agentic workflow actually works, there is a near-magical quality to it. Once AI becomes part of the underlying infrastructure and starts contributing to team outcomes without being driven on a daily basis, the upside is tremendous. That is the real shift: moving from copilot to autopilot.

On the flip side, cost is what catches teams off guard. Once AI is infrastructure, the token bill scales with everything else. Recent pricing and quota changes have pushed some companies to press pause on initiatives until they get that under control.

On this AI Appreciation Day, my advice to any CTO in that position is to know your models. Not every task needs frontier intelligence. Model literacy is a genuine developer skill in 2026, and understanding which model to use for which job is what flattens the AI cost curve without stalling the initiative.

Jon Lucas, Co-Founder and Director at Hyve Managed Hosting

AI Appreciation Day is a timely reminder that while attention often focuses on the latest AI models and applications, long-term success depends on the infrastructure supporting them. As organizations move AI from experimentation into production, they need infrastructure that can securely and reliably support increasingly demanding workloads while maintaining performance, availability, and operational control.

As AI becomes embedded across everyday business operations, infrastructure decisions are becoming strategic business decisions. Organizations need to consider where their AI workloads are hosted and whether those environments provide the control, governance, and regulatory alignment necessary to protect the proprietary business information, intellectual property, and customer data that AI systems process.

Cost is also becoming a deciding factor. For many organizations, it is the price of AI infrastructure—not the technology itself—that stands between a promising pilot and production at scale. The growing availability of right-sized, entry-level hosting options is opening AI up to businesses beyond the largest enterprises, and that accessibility will shape who benefits as adoption accelerates. Organizations that establish flexible, sovereign, and cost-efficient foundations now will be best positioned to scale AI with confidence.

Adam Luciano, VP of Product Management at MariaDB

AI isn’t an apocalypse. It’s an evolution, and one worth celebrating. It is making software development more accessible, helping people test ideas in minutes and pushing the industry to build products that deliver greater value. That shift will unlock a new wave of creativity, especially for people who previously lacked the time or resources to build software themselves. At the same time, moving from a quick prototype to a reliable production application is still a very different challenge. The next phase of AI will depend on strong foundations. That means open, stable, and secure infrastructure capable of supporting high-performance applications and rapidly growing fleets of AI agents.

Raj Mallempati, Co-Founder & CEO at BlueFlag Security

While still a new phenomenon, National AI Day could also fit under another National Day recognized in September – National Identity Day. This is because, from an IT perspective, identity is no longer a human concept. From APIs to AI, identity isn’t about humanity; it’s about access and behavior. And the reality is that AI agents have fast become non-human identities with superhuman capabilities. Nowhere is this more pressing than in the Software Development Lifecycle. In the broader IT ecosystem, the underpinnings and attention already exist to expand control over agents, but in the SDLC, there is a concerning lack of visibility and governance over the relationships between code, configuration, and behavior. With exploitation of the software supply chain already in the news far too often, and with technologies like Mythos set to exponentially increase the risks, oversight in the SDLC is an imperative too urgent to ignore.

Raghu Malpani, Chief Technology and Product Officer, UiPath

One part of AI Appreciation Day is reflecting on where AI is creating the greatest value for businesses today.

From what I’ve seen from our customers, AI use is scaling within organizations to translate into disproportionate gains for everyone. Across the value chain of complex business processes, discovering the work that should be reimagined and augmented with AI – mapping workflows, systems, and exceptions that actually run the business, is step one. The judgment of what should leverage AI and warrant a positive ROI is becoming a bottleneck. Once that’s identified, you can decide where and how to apply AI and AI tools to eliminate repetitive work that keeps employees from focusing on and solving harder problems.

One such tool is coding agents. They can generate code, accelerate the development of software and new systems, and help teams move faster, but their real impact isn’t measured solely by the lines of code written or the software built. It’s twofold: changing the definition of who gets to build from ‘just’ developers to include business users, and ensuring that what gets built by this expanded set of builders stays in line with governance standards.

The organizations that get the most from AI won’t be the ones using AI as an excuse to cut costs. They’ll be the ones that reimagine their business using that map, then build intelligent workflows that orchestrate automations, AI, systems, and people from end-to-end across the business. This is the value we see.

Jeff Margolies, Chief Product and Strategy Officer at Saviynt

AI Appreciation Day is a reminder that AI is becoming a powerful tool for helping organizations move faster, make smarter decisions, and manage complexity at scale. As AI adoption accelerates, enterprises need the right governance and identity controls in place so teams can use it confidently and responsibly. The fundamentals have not changed. Strong visibility, effective access controls, and rapid risk reduction are still essential to building trust in the AI era. What has changed is the pace of change. Organizations that act now will be better positioned to innovate securely and with confidence.

Tiffani Martin, Aspen Policy Academy Fellow 2026, Founder and CEO of VisioTech

It is my desire that we use AI Appreciation Day as a moment where we rethink how we measure the value of this tool. For the past few years, we’ve measured AI by efficiency, but I believe the better measure is opportunity. AI helps us explore ideas beyond the patterns we naturally gravitate toward. This consequently creates an opportunity to invite more people into the conversation, including those with different backgrounds, lived experiences, and neurodivergent approaches to solving problems. The best cybersecurity teams have shown for years that diversity of thought leads to better outcomes because different perspectives uncover risks others miss. AI expands the range of ideas we can explore while people provide the empathy, context, and judgment that turn those ideas into real, sustainable solutions that move the needle for our customers.

Philip Miller, AI Strategist at Progress Software

This AI Appreciation Day, we need to rethink what AI enablement really means. We do not ask people to understand the electricity grid before switching on a light, or the engineering behind a railway before taking a journey. In the same way, most people do not need to master models, transformers, neural networks, or tokens to create value with AI. They need to understand what they are trying to achieve. Too often, those of us working with AI every day assume a level of familiarity that simply does not exist. This makes it difficult for people to imagine new AI-enabled outcomes, even when they understand the problem they need to solve. Enablement must therefore move from the ‘what’ to the ‘how’: from explaining features and infrastructure to understanding the user’s goals, mapping the human workflow, and identifying where AI can reduce friction, shorten time to value, or scale the outcome. Our job is to make AI accessible, trusted, and usable, so more people can turn their expertise into meaningful results.

Heath Mullins, Chief Evangelist at ExtraHop and Former Forrester Analyst

AI Appreciation Day isn’t just about recognizing how fast AI is changing business operations. It’s a reality check on how it’s changing the game for everyone, ranging from large businesses scaling operations to individuals looking to perform simple tasks with the help of an LLM.

While companies may be running smarter and faster, AI advancements are also enabling cyber attackers to advance in similar ways. Recent research shows that about 85 percent of organizations have already been hit by an AI-powered attack, including everything from hacking attempts to AI identity theft and new tactics that slip in through third-party partners. With AI adoption inevitable for any large-sized organizations, security teams face a new wave of threats that are quicker, stealthier, and tougher to stop.

On the contrary, AI is also making defenders sharper, enabling security teams to automatically detect and triage threats as they’re forming, quickly see what attackers are doing, and get a clearer picture of the whole attack surface faster. Using the right context from the network, endpoints, and identity providers enables organizations to successfully implement a decisive AI defense.

Recognizing the rapid advancements in AI over the past few years isn’t just about the tech itself; it’s also about understanding how broadly it’s changing the way we operate, from daily tasks to how we protect our digital ecosystems.

Markus Nispel, CTO EMEA and Head of AI Engineering at Extreme Networks

AI is transforming leadership by giving leaders better data, deeper insight, and greater transparency. But while AI can inform decisions, it can’t own them. Leadership will always be about judgment, accountability, and the courage to make the final call. AI won’t change every role in the same way, but it consistently frees people from time-consuming tasks so they can focus on higher-value work. We’re already seeing experienced teams use AI to deliver significantly greater productivity—particularly in software development—while improving both quality and speed. The greatest opportunity isn’t replacing human expertise; it’s amplifying it.

Kunj Pandya, VP of Product and Customer Success at AutoScheduler

What companies need at this moment is a bridge between the future of AI and the realities of the warehouse floor. There’s a lot of pressure on companies to adopt AI quickly, but the opportunity is to do that in a way that respects the people, processes, and constraints already in place. I don’t think the most interesting story is AI replacing operators. It’s AI helping operators become more effective and more influential inside the business. Some roles will change, as they always do with new technology, but there’s a huge opportunity to upskill the people who already understand the operation best.

Cigdem Patlak, an AI Red-Teaming Professional and Aspen Policy Academy Fellow

AI is redefining productivity by dramatically reducing the effort required to move from idea to execution. As generative AI evolves toward agents capable of carrying out multi-step tasks, employees are increasingly coordinating human-AI teams, and work is shifting from doing to directing, placing greater value on human judgment, context, creativity, and decision-making. In 2026, the conversation is moving beyond whether organizations should adopt AI toward how they can redesign workflows so that human flourishing becomes a practical consideration in how work is structured, measured, and experienced.

Appreciating AI means recognizing how profoundly it is reshaping the way we work and think. As AI takes on more execution, organizations have an opportunity to be intentional about preserving space for critical thinking, questioning assumptions, and applying human judgment where it matters most. A practical starting point is to identify which tasks can be delegated, which decisions require meaningful human oversight, and how employees will continue developing expertise rather than simply approving AI-generated work. The organizations that gain the greatest long-term advantage are those that treat AI not just as an efficiency tool, but as a catalyst for better decisions, continuous learning, and more resilient ways of working.

James Patrick-Evans, Founder and CEO of RevEng.ai

Artificial Intelligence has rapidly evolved from a productivity tool into a force multiplier for cybersecurity teams. In software development, AI is accelerating coding by helping developers generate, review, and optimize code at unprecedented speed. This allows security professionals to spend less time on repetitive tasks and more time focusing on designing resilient systems, identifying architectural risks, and embedding security throughout the software development lifecycle. As AI-assisted development becomes the norm, the opportunity to build secure applications faster has never been greater.

The same transformation is happening in cybersecurity. Security Operations Centers (SOCs) are increasingly using AI to correlate vast amounts of telemetry, prioritize alerts, identify anomalous behavior, and automate investigations that would otherwise consume valuable analyst time. Rather than replacing human expertise, AI amplifies it — helping defenders detect threats earlier, respond faster, and stay ahead of increasingly sophisticated adversaries who are also leveraging AI to scale their attacks. The future of cyber defense is a positive one and will belong to organizations that successfully combine AI-driven automation with skilled human judgment.

Ashley Raysin, U.S. Director at VoCoVo

AI can only be truly appreciated when it’s leveraged to better support the workforce using it. This is especially evident for frontline workers in retail. It’s not about replacing these teams, but ensuring they can use this technology effectively.

Yes, retailers have invested heavily in AI to advance forecasting, inventory management, and customer insights. But the next step is extending those insights beyond the back office and into the hands of frontline staff. One of the biggest misconceptions about AI is that success depends on deploying the most advanced model. In reality, retailers often see the greatest value from practical, everyday use cases that help frontline employees make faster, more informed decisions. It’s about turning AI insights into action.

To do this, retailers must focus on delivering the right information to the right employee at the right moment. This means AI should fit naturally into existing workflows so frontline employees can access information immediately, receive relevant guidance, and continue helping customers without disrupting the shopping experience. Recent research indicates that 62 percent of consumers seek out staff when they cannot find a product, and that poor or unhelpful service is the top reason 53 percent would not return to a store. This emphasizes the need for technology that augments, not replaces, staff.

Ultimately, the retailers seeing the greatest AI impact aren’t treating the technology as a standalone tool. They’re embedding it into everyday workflows so frontline employees can respond faster, solve problems in real-time, and spend more time serving customers.

Brian Remmington, Chief Software Architect at M-Files

On AI Appreciation Day, it is tempting to celebrate what the technology can produce. What deserves more appreciation is who AI reaches and the positive impact it delivers: clearing routine work that slows organizations down and helping people get what they need faster.

We see it across our customer base. For example, at a UK charity, it automates document-heavy admin, so frontline staff can find a wheelchair grant or a local support group while sitting in someone’s home, rather than heading back to a desk to complete the paperwork. For a global pharmaceutical research company, context-enriched information helps optimize client report times by 65 percent, getting research findings into the right hands faster.

The day also provides the opportunity to consider AI ethics, where the conversation often stays fixed on the model itself. In practice, much of what makes enterprise AI ethical is decided upstream, in how information is governed. An AI assistant that respects who is allowed to see information will not overshare a stroke survivor’s personal data. One built on structured, well-described information can explain why it reached a conclusion, rather than asking people to trust a black box. Privacy, accountability, and transparency are not abstractions here; they are properties of the information that AI is permitted to use.

That, for us, is what appreciating AI should mean: not celebrating cleverness but investing in a trusted foundation that enables AI to serve people quickly and safely.

Abhas Ricky, Chief Business Officer and GM of Applied AI at Cloudera

The hard part of enterprise AI is no longer the pilot. It is everything that comes after. MIT’s NANDA initiative found that 95 percent of enterprise generative AI programs have produced no measurable P&L impact despite $30–40 billion in spending, and that 42 percent of firms abandoned most of their AI initiatives in 2025, up from 17 percent a year earlier. The implication is blunt: access to frontier models is now commoditized, and the durable advantage belongs to whoever can sustain, govern, and defend AI once it leaves the demo.

The economics of enterprise AI are being rewritten because the bottleneck has moved from access to operation. To sustain it, measure useful work and place workloads where they pay. To govern it, enforce common standards, policy controls, traceability, and orchestration. To defend it, apply selective oversight, hard safeguards, and systems engineered for failure as carefully as for success.

The model layer is commoditizing. Frontier capability is now a purchase, not a moat. What compounds is the infrastructure, the governance, and the trust wrapped around it. The 95 percent that stalled treated AI as something to acquire; the 5 percent that broke through treated it as something to operate. That gap is the entire distance between a pilot and production. Increasingly, it is also the distance between the enterprises that will lead the next decade and the ones explaining to their boards why the demo never paid for itself.

Trust, not tokens, is the unit of account now. Build for it.

Alex Rumble, Chief Marketing Officer at HTEC

AI Appreciation Day is important in recognizing the transformational abilities that AI provides enterprises on a daily basis. However, the appreciation must also be shared with the human workforce who use their own skills to translate AI into real economic value. Whether it’s engineers who are designing code that will power the next major AI breakthrough or healthcare professionals managing the clinical supply chain, the combination of human and AI is vital to generating tangible operational improvements.

For business leaders, the reality shaping AI-led industries right now is that there is a literacy gap holding companies back, not a lack of usable models. The true differentiator won’t be who has the most advanced hardware; it will be the enterprises that are focused on closing that gap by combining AI literacy with existing skills to achieve cultural success in AI-led operations.

Achieving the goal of operational success, however, requires visibility, such as sightlines into how AI is being used, where it is making an impact, and the exact value it is generating across the business. This helps teams see the benefits of AI in their workflows, which in turn builds trust in the technology, fuelling a cycle that drives further value and deeper adoption.

Whilst enterprises were once focused on deployment, many are now moving to ensure return on investment from their AI tools, as the boardroom has shifted from “what can it do?” to “what has it delivered?”. The winners over the next year will be those who work closely with their teams to ensure that accurate data and skills are in place to unlock the immense value of enterprise AI.

Dave Russell, SVP and Head of Strategy at Veeam

On AI Appreciation Day, it’s worth acknowledging how far agentic AI has come. Today’s agents can move data, change configurations, and make decisions at machine speed. Work that once took teams days can now happen in seconds.

But that speed also changes the risk profile. Too often, agents are granted more access than they need, and over-privileged agents are becoming a real vulnerability. Trust can’t be based on assumptions anymore — it has to be based on context and verification: knowing who or what is touching your data, what they’re doing, and why, while confirming the identity behind every action. And when something does go wrong, the difference between a bad day and a bad year is whether you can roll back to a known-clean state in minutes, not weeks.

In the AI era, resilience and verification aren’t add-ons — they are prerequisites.

Stephanie Schneider, Senior Cyber Threat Intelligence Analyst at LastPass

While AI is improving automation and efficiency in workplaces, it’s also creating headaches for security teams, who are feeling the impact of accelerated cyber-attacks. With attackers and hackers increasingly leveraging AI to target identities and credentials, access control is now a governance issue requiring full oversight.

To ensure security in today’s AI threat environment, security teams must increase visibility into SaaS and AI usage, ensure critical authentication codes exist, and review governance and audit reporting capabilities. By doing so, security teams can feel more confident in their defense against AI-driven attacks. On National AI Day, it’s important to remember that every day, AI advances and improves, but that those advancements are not just taking place with the good guys. Threat groups will continue to use AI to their advantage when executing attacks, getting faster and more effective to evade security detections.

Dipanjan Sengupta, Distinguished Technologist in Digital Engineering at EY Global Delivery Services

What I appreciate about where we are today is that AI is maturing to include advanced reasoning capabilities that can establish relationships among things, offering a more intuitive perspective. Connections that we take for granted, like text and illustrations, or a contract clause and its amendment three years later, are present in today’s AI protocols. That’s the part that genuinely excites me; it’s not just about speed, it’s about the machine starting to notice patterns that it struggled to connect before and starting to add valuable expertise that can elevate human and workforce impact.

For enterprises, these improvements have finally given us a way to bridge the gap between what an organization knows and what it can act on. For years, so much of that knowledge was locked away in an organization’s knowledge base, and it simply couldn’t scale. Newer approaches to AI’s supporting infrastructure, like adaptive knowledge retrieval, greatly enhance traditional retrieval-augmented generation (RAG) workflows, not only surfacing the right information at the right moment but also acting as a dynamic storytelling engine that greatly enhances the performance of AI models. These improvements have made AI a better partner for humans, and something an enterprise can truly operationalize.

Investment in fostering responsible, scalable AI adoption is critical, not just for helping enterprises move past pilots and proofs of concept, but also for building something durable that delivers the benefits of security, compliance, and consistency from day one.

Rajan Sethuraman, CEO at LatentView Analytics

We’re officially in the next phase of AI, where the conversation has shifted away from who has access to it and toward who is actively creating measurable business value with it. That shift is being driven by people: teams building responsible AI systems, leaders putting the right governance in place, and employees learning new ways of working and applying AI to real business challenges. Organizations pairing AI with trusted data, strong governance, and human expertise are moving faster, making better decisions, and building lasting competitive advantage. At the end of the day, AI can accelerate insight, but it’s people who provide the context, judgment, and accountability that turn technology into real business outcomes.

Akinobu Shimada, CEO of Hitachi Vantara

AI is often discussed in terms of productivity, but its greater significance lies in its ability to convert data into insight and action. As AI becomes embedded across enterprises and society, its success will depend not on the sophistication of the models, but on the quality, scale, and trustworthiness of the data that powers them. Having spent my career in the data storage industry, I see the emergence of AI as one of the most significant shifts in our industry’s history. Yet AI will realize its full potential only when it is integrated into the business processes, industries, and systems that shape how we work and live, and that transformation requires a strong data foundation. Organizations that build resilient, intelligent, and trusted data infrastructure today will be the ones best positioned to transform AI’s promise into meaningful outcomes tomorrow–for their businesses, customers, and society as a whole.

Arnold Shimo, Chief Security Officer & Co-Founder at Sevii

National AI Day is occurring at a time when AI is fast approaching an inflection point. Usage within organizations has reached a level of project saturation, and with that, hard decisions regarding next steps that hinge on concerns of cost and control. The days of tokenmaxxing are coming to a close, and organizations need to find models and tools that deliver the highest levels of efficiency, effectiveness, and transparency. The issues are no more pressing than in AI security, where speed is of the essence, and trust is paramount. Bad actors are using AI to supercharge attacks and vulnerability discovery, and human defenders are far outmanned and outgunned. They need to be able to let AI agents “off the leash” to handle the chain from hunt to remediation, without a human in the loop. This requires the industry to address cost models that don’t just shift the same staffing budget challenges onto technology implementations, and to establish governance frameworks that empower teams to surge to meet the threat with the utmost confidence in the outcomes.

Bojan Simic, CEO and Co-Founder of HYPR

As AI moves from passive assistant to active agent, the definition of identity in the enterprise has to change. We’re giving non-human actors the ability to take actions, make decisions, and touch critical data, often using legacy service accounts or blanket permissions that were never designed for autonomous execution.

If you can’t answer exactly who an agent is acting on behalf of, what its boundaries are, and how to stop it in real-time, you don’t have a policy, and without a policy comes real security risk and exposure.

Scaling AI safely comes down to basic identity fundamentals applied to non-human actors:

• Verifiable Ownership: Binding every agent to a human owner with an explicit, time-bounded scope of authority.
• Inline Control: Enforcing security at the point of execution through an agent gateway to ensure real-time response rather than trying to audit actions after they’ve already happened.
• Real-Time Oversight: Dynamically keeping a human in the loop who can constrain or shut down an agent instantly if it strays.

AI Appreciation Day is a good reminder that speed is only half the equation. The organizations that get the most value out of AI won’t just be the ones deploying it fastest—they’ll be the ones that solved how to govern non-human identity before things scaled out of control.

Hari Srinivasan, Vice President of Products and Strategy at Lineaje

Agentic AI is driving enterprise technology past ‘just’ assistance and directly into autonomous operational execution. As these systems independently generate code, execute workflows, and make real-time decisions, they fundamentally alter the enterprise risk profile.

The shift demands an immediate evolution in governance. Enterprises can no longer rely on periodic audits; they require continuous, real-time visibility into Agentic AI, including AI-generated software, and rigorous integrity verification throughout the entire development lifecycle. That process begins with software lineage—equipping organizations to trace exactly what AI created, verify its origin, and validate its integrity before a single line of code reaches production.

For AI Appreciation Day, the industry conversation must mature from AI adoption to strict AI governance. As Agentic AI reshapes enterprise operating models, continuous governance should become the baseline, not the exception. True value isn’t what AI can build—it’s about ensuring every AI and AI-generated outcomes can be governed, verified, and trusted.

Paul Stokes, CEO and Co-Founder at Prevalent AI

AI appreciation should start with a simple truth: AI doesn’t create knowledge, it reveals what an organization already knows, and what it doesn’t. The biggest breakthroughs won’t come from faster models or larger datasets. They’ll come from giving people the confidence to act because they finally have trusted information, clear ownership, and relevant context.

Sundar Subramanian, CEO at Zyter

Much of today’s conversation around AI still focuses on the technology itself. We compare models, benchmark performance, and chase the latest features. Those advances matter, but they aren’t what will ultimately determine AI’s value. This is the same approach to emerging technologies that for decades rewarded the people who best knew how to build software. That deep technical and model knowledge is certainly still important. But the future of the AI economy won’t be defined by model capability alone. It will be defined by how well organizations understand what the people using AI are actually trying to accomplish.

In practice, that means looking beyond individual tasks AI can automate and asking how AI can improve an entire workflow or role. Take the healthcare industry as an example. The goal isn’t to replace clinical judgment. When AI is viewed through the lens of human expertise and experience, it can remove administrative burdens like documentation, prior authorizations, and routine coordination so a physician can spend more time actually talking to their patient and building a human-led relationship.

The real opportunity with AI isn’t about removing people from the work. It should be about creating space for people to do more of what’s meaningful, thoroughly human, and genuinely impossible to replicate.

Corey Thuen, CEO and Co-Founder of Gravwell

I’m going into AI Appreciation Day with a healthy dose of skepticism, which I think we all need as we learn to coexist with and utilize it responsibly.

One of the biggest misconceptions about AI is that it’s changing how computers work…but it actually isn’t. Computers still work the way they always have. What’s changed is the interface. For the first time, users are interacting with systems that don’t always produce the same output from the same input.

We’re no longer just exploiting software. We’re social engineering computers; instead of convincing a person to ignore the rules, you’re convincing an AI model to ignore its guardrails. That’s a new attack surface for machines and one that’s evolving extremely fast.

AI deserves credit for helping security researchers uncover vulnerabilities at scale, but it also creates a dangerous misconception. Too many people assume that because AI’s writing sounds pretty good, it understands all situational context and knows what it’s doing. It doesn’t, plain and simple. It’s predicting language, not reasoning about security, policy, or intent. That’s exactly why prompt injection works here: attackers manipulate AI models using language, because those models can’t distinguish between a legitimate instruction and a cleverly crafted one with malicious intent. Security teams that understand those limitations and balance AI’s weaknesses with human intelligence will build stronger defenses than those who assume it’s smarter than it really is.

Bert Van Hoof, CEO at Willow

AI Appreciation Day is a good moment to ask a difficult question: has AI finally moved from describing the physical world to operating it?

Most AI still lives in bits. It shows up in documents, dashboards, and chatbots that read and summarize. Yet, the built world runs on atoms: chillers, elevators, air handlers, and refrigeration, along with the people who keep them working. Traditional building systems can tell you a chiller is underperforming, but leave a person to decide what happens next.

Operational AI is what happens when AI moves from describing the physical world to operating it. It connects live operational data across a building’s systems into a single operational layer with real asset context. When a signal fires, it schedules the repair, routes the work order, and adjusts the setpoint directly.

The same layer that predicts a chiller failure in a hospital can also detect a jet bridge issue at an airport or a refrigeration fault in a retail portfolio. Different assets, same discipline. Buildings shape health, safety, learning, and how communities function. AI is worth appreciating when it helps run them.

Anthony Verna, SVP and GM of Cubic DTECH Mission Solutions

AI is changing how defense organizations enhance adaptability and gain a decision advantage in complex operational environments. Modern operations require mission teams to access, process, and act on mission-critical data locally without assuming constant connectivity.

The next phase of AI adoption will center on greater speed, autonomy, and data operationalization at the tactical edge. We will continue to see accelerated adoption of AI-enabled edge compute, software-defined communications, and integrated mission systems that support distributed operations, faster coordination, resilient communications, and rapid intelligence processing.

AI is helping to reshape how operators turn mission-critical data into an operational advantage through faster, more informed decisions. That role will continue to grow as defense organizations prioritize technologies that improve mission effectiveness, wherever the fight goes.

Roi Vanunu, Director of Product Management at Jazz

AI Appreciation Day is worth pausing on, not to celebrate AI for drafting and generating, but for what it’s starting to make possible at a deeper level: human-level understanding, at scale.

DLP has fallen short for decades, and the failure wasn’t just detection. It was architectural. Rules and pattern matching can flag activity. They can never understand it. A tool can see that a file has been moved, but not whether that made sense given who moved it, their role, and what the business actually cares about. That gap always needed a human to close.

AI changes the equation. For the first time, it’s possible to build security tools that don’t just detect; they understand. They can assess intent, context, and business meaning at the speed and scale humans can’t. The judgment call that used to sit with the analyst now happens before anything is ever surfaced.

That’s the breakthrough worth celebrating: security that finally understands your business the way your team does.

Wiktor Walc, CTO at Tiugo Technologies

The first wave of AI ran on hype. Big expectations, the promise of instant breakthroughs, as well as ambition that outpaced the strategy, governance, and operating models needed.

Now, teams are getting deliberate about where AI improves productivity, where it still falls short, and what it takes to run it responsibly in production. That’s not a push toward more basic systems. Usually, it’s the opposite. Agentic workflows are already spreading, backed by stronger data governance and tighter integration alongside existing processes.

AI generates content, analysis, and data faster than any person can keep pace with, so the human becomes the bottleneck. Removing people from the loop is not the answer. The answer is engineering workflows that serve agents and humans equally well. Agents need secure, structured access to the data and context they run on. Humans need a full, transparent record of every action and change AI made, plus a clean way to review, accept, reject, or refine it.

One of the largest limits on productivity and also one of the largest opportunities is the human-AI layer. Those who get it right will be more productive, but will also convert that output into trusted, governed work at scale.

Mark Wojtasiak, SVP of Market Research and Strategy at Vectra AI

AI Appreciation Day shouldn’t be about celebrating faster tools. It should be about appreciating what AI can give back to people: time to think, room to be curious, and confidence to act. In cybersecurity, defenders have been buried in noise for too long. The best use of AI is not replacing them. It’s taking on the repetitive, high-speed work machines are better suited for, creating room for humans to ask better questions, make better decisions, and build security teams they’re proud to be part of.

Linda Yao, Vice President and General Manager, Hybrid Cloud & AI Solutions at Lenovo

AI’s greatest impact extends beyond transforming technology stacks; it lies in augmenting our time and amplifying our work. At Lenovo, where we’re building Smarter AI for All, we believe these tools improve human experiences, not just productivity. AI has the power to supercharge creativity and innovation, unlock stronger decision-making, and free us to focus on higher-value work.

However, realizing that potential requires more than deploying AI tools. It requires trust. As AI moves from experimentation into production, governance becomes imperative because organizations and their employees must have the confidence that AI is transparent and that decision-making is both explainable and aligned with business objectives. Without clear policy and guardrails, there will be challenges in deploying AI systems. In fact, Lenovo’s 2026 CIO Playbook reveals that only 22 percent of organizations have comprehensive AI governance frameworks in place. Organizations cannot succeed if they do not prioritize governance and policy as non-negotiable with their AI-adoption strategies.

Organizations that succeed won’t be those that simply deploy more AI. They’ll be the ones that empower people to use AI confidently and securely, and to create lasting business value by unlocking the potential of their people.

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