Building a Data Strategy with an AI Focus: Leveraging the Power of Agentic AI
It’s on the lips of many at the moment and is accelerating at pace every day. Yes, you guessed it Marmite! Ha!
No, I mean the fact that everywhere you turn on LinkedIn or content out there it’s all about Agentic AI or DOG! So, I thought, even though it is and the echo chamber that is LinkedIn knows all about Agentic AI and it’s uses, there are plenty of people out there who quite frankly either don’t know or are too afraid to ask! This post is for all those people.
It’s interesting for me, seeing the trends burst onto the scene these days. The era of traditional data strategies isn’t gone, it’s just being transformed by a new wave of AI capabilities, and one of those is Agentic AI.
I’ve decided I’m going to call it a new class of AI, mainly because ultimately, they will be able to learn and act autonomously, adapting to real-world changes without constant human oversight. Can you imagine that a “mini me”, being able to do all the things that I would love to do! I will end up living vicariously through my Agent!
As it is, Agentic AI is already poised to reshape multiple industries, offering organisations the ability to operate with intelligence, flexibility, and efficiency. What do you mean they don’t do that now Samir? Well, let’s fess up, we live in the matrix!
In this article, I will explore how businesses can integrate Agentic AI into a data strategy to deliver measurable value across different functions, as well as provide examples of its use across industries.
What is Agentic AI?
Hers is the best way I can define it:
Agentic AI involves AI systems that can autonomously act based on real-time inputs, adapting to situations with minimal human intervention.
It’s a little like having your own digital twin, that can work 24 hours a day, doesn’t need sleep, water, rest, all it needs is big amounts of electricity! That’s a conversation for another day, seeing as COP29 is going on, which of course will do naff all for anyone!
So for example, my agent could go off and interact with a kitchen agent to order my new kitchen, then interact with the travel agent (see what I did there) to book my holiday as my apartment is being redone, and then it can go off and rebook my hire car because I had hired a convertible and now it’s going to rain for the week. As we get into the future, it will be able to monitor my health and if it sees markers for my blood pressure it might intervene and order an ambulance or book a doctor’s appointment.
But, unlike traditional AI, which typically follows pre-programmed responses, Agentic AI uses intelligent agents to interact with changing environments and respond accordingly. This positions Agentic AI capable of providing real-time decision support in areas such as customer service, supply chain management, and financial trading.
Although still an evolving field, Agentic AI has transformative potential. As organisations recognise the value of self-improving AI, this technology will play a central role in supporting business objectives and enabling adaptive decision-making across the board.
The rest of this article is about how organisations can think about using Agentic AI for their purposes.
The Value of Agentic AI Now and in the Future
Agentic AI offers immediate and long-term value by enhancing responsiveness, operational efficiency, and resilience across industries. Here are a few key benefits:
- Rapid Responsiveness: Agentic AI can react in real time to changing data, enabling businesses to meet customer needs, optimise operations, and adjust to market conditions without delay. This advantage is critical for organisations competing in fast-paced industries.
- Cost Efficiency: By reducing the need for manual oversight, Agentic AI allows businesses to streamline operations and cut costs. As autonomous systems become more capable, organisations can scale efficiently without increasing operational overheads.
- Future Scalability: Agentic AI systems can adapt to new tasks and environments, making them scalable across different areas of an organisation. As this technology advances, businesses can implement Agentic AI in more complex processes, enabling future growth without the need for extensive restructuring.
- Continuous Improvement: Agentic AI systems learn from every interaction, evolving to deliver improved results over time. This ongoing development enables them to provide increasingly accurate insights and drive continuous optimisation.
Examples of Agentic AI Across Different Industries
To better understand Agentic AI’s potential, consider the following examples of its application across different sectors:
- Retail: Agentic AI can optimise stock management by analysing purchase patterns, tracking inventory in real time, and automatically restocking items based on demand forecasts. In customer service, agents can manage customer inquiries, escalate issues to human agents when needed, and even make product recommendations tailored to individual customers. We are still early days here, but, and you may laugh because most agents can probably be duped, however, it can only get better.
- Manufacturing: Agentic AI systems can autonomously monitor equipment, predict maintenance needs, and order parts before a breakdown occurs. This predictive maintenance helps avoid costly disruptions. Additionally, Agentic AI can optimise production schedules in response to supply chain delays, ensuring efficient workflows and minimising downtime. I work with a CPG and in the future, this is something they will want to do when they get their data right!
- Finance: In financial services, Agentic AI can analyse market data in real time, adapt trading strategies based on current market conditions, and execute trades autonomously. It can also detect and respond to fraudulent transactions more swiftly than human analysts, helping prevent financial losses and maintaining customer trust.
- Healthcare: Agentic AI can streamline patient care by managing appointment schedules, monitoring patient vitals in real time, and sending alerts when immediate intervention is needed. In diagnostics, AI agents can continuously analyse new medical data to improve diagnostic accuracy and treatment recommendations.
- Logistics and Transportation: Agentic AI can optimise delivery routes in real time by considering traffic patterns, weather conditions, and package priority, ensuring timely deliveries. It can also manage fleet maintenance by monitoring vehicle performance, scheduling repairs as needed, and maximising fleet efficiency.
- Energy and Utilities: In the energy sector, Agentic AI can monitor energy grids, anticipate power fluctuations, and autonomously adjust supply to meet demand. It can also manage renewable energy sources by optimising energy storage and distribution, balancing grid load, and reducing waste.
Amazing right? Yes, early days, but the potential is massive for going off and autonomously and proactively improving efficiencies and inevitably revenues.
Building a Data Strategy with an Agentic AI Focus
As I’ve always maintained throughout my career in data (which is now over 20 years), an effective data strategy with an AI focus should begin with clear business objectives, practical use cases, and a long-term vision that aligns data initiatives with value outcomes. Integrating Agentic AI requires a solid foundation built on reliable data, agile processes, and a commitment to responsible AI use. So, here are 5 areas that you should concentrate on:
1. Identify Value-Driven Use Cases
Start by identifying specific areas where Agentic AI can create measurable value, such as improving customer experience, enhancing operational efficiency, or minimising downtime. For example, a retailer might deploy Agentic AI to manage inventory or provide personalised customer service. Setting clear objectives and measurable outcomes ensures that the AI investments align with business goals, preventing wasted resources on projects with little impact.
2. Build a Strong Data Foundation
Agentic AI relies on high-quality, real-time data to function effectively. A data management strategy (a subset of your overall data strategy), should consolidate data sources, enforce data quality standards, and establish governance policies that enable ethical and responsible data use. A strong data foundation is essential for autonomous systems to perform accurately and adapt to new information as it becomes available.
3. Implement an Agile and Adaptive Framework
Agentic AI is best implemented in environments that support iterative improvements and flexible processes. Adopting an agile approach allows organisations to test Agentic AI in targeted use cases and then scale up based on the results. Establishing a feedback loop for continuous learning will enable data insights from AI implementations to refine business processes and enhance data quality.
4. Invest in Skills and Change Management
Successful integration of Agentic AI requires skilled personnel who can manage, monitor, and refine AI systems. Change management is critical as well; employees need to understand and trust autonomous systems for them to be effective. This includes educating leaders on Agentic AI’s long-term potential and ensuring that it is strategically integrated into decision-making processes.
5. Create a Governance and Ethical Framework
Agentic AI’s autonomy raises new questions about transparency, accountability, and ethics. Establishing a governance framework that addresses bias, transparency, and accountability is essential. This ensures that AI systems operate responsibly and that organisations can maintain customer trust and comply with regulatory requirements.
Preparing for the Future with Agentic AI: The Rise of the Augmented Human
The journey to fully autonomous, adaptive AI is just beginning. By implementing Agentic AI, organisations position themselves not only to enhance current operations but to anticipate an incredible transformation in the human and machine collaboration. In this vision, humans will increasingly rely on AI agents to support decision-making, anticipate challenges, and respond with precision, freeing up human creativity and judgment for higher-order thinking. That’s the hope, or, they will take over the world and it will be the real Matrix!
As Agentic AI evolves, we can expect this technology to complement human skills in even more profound ways, reshaping the nature of work, re-imagining customer service, and enabling organisations to function at levels previously thought impossible. Here are some of my thoughts as to how Agentic AI could expand its role in future workplace scenarios.
- Augmented Decision-Making and Strategy: In the coming years, Agentic AI could take on roles as strategic advisors, running billions of simulations to predict the impact of various scenarios on the business. This idea came from @mark Stouse and Imagine AI agents assessing complex geopolitical or environmental factors in real time, suggesting supply chain changes, or alerting leaders to early signals of market disruption. They could provide decision-makers with comprehensive, data-driven insights tailored to individual strategic goals.
- Personalised AI Advisors for Every Employee: Imagine every employee equipped with their own personal Agentic AI assistant, designed to understand their specific role, skill set, and goals. This assistant could enhance productivity by automating routine tasks, managing communications, and providing tailored learning recommendations. It would allow employees to focus on complex, creative tasks that bring value, while the AI seamlessly manages time-consuming details. These personal AI advisors would effectively democratise access to the highest level of organisational intelligence. It would be great for all the agents to attend meetings and revert to you for only the most important of strategic decisions. A world where there would be less meetings, bliss!
- Predictive and Preventive Health Support: Agentic AI will likely extend into the realm of healthcare, offering augmented support not only to patients but to entire workplaces. AI-driven wellness programs could monitor environmental conditions, predict individual health risks, and even recommend adaptive workspaces to improve employee well-being. Imagine AI agents that monitor stress signals in real-time and alert HR departments when employees may need support, empowering organisations to proactively create healthy, engaged teams.
- Hyper-Customised Customer Experiences: Businesses will also leverage Agentic AI to deliver deeply personalised experiences for customers. Going beyond today’s recommendations, AI agents could autonomously predict a customer’s needs before they are even expressed, using nuanced patterns in data to anticipate preferences. This would empower brands to engage with customers in ways that feel intuitively personal and significantly improve satisfaction and loyalty.
- Intelligent Collaboration Networks: In the future, Agentic AI could manage and optimise collaborative networks across organisations. These intelligent networks would automatically match individuals with the right teams and projects based on skills, interests, and real-time workloads, breaking down silos and encouraging cross-functional teamwork. AI could even suggest opportunities for external partnerships, continuously scanning the environment for companies with aligned missions or complementary resources, reshaping the very fabric of how businesses operate and compete.
- AI-Augmented Ethics and Governance: As Agentic AI becomes more autonomous; organisations will need ethical agents designed to ensure Agentic AI behaviours align with human values. Future generations of Agentic AI could autonomously monitor compliance with ethical standards, detecting potential biases or ethical risks in real-time. By embedding ethical AI oversight at every level, organisations could build a foundation of trust and transparency that strengthens their brand and customer relationships.
Thriving in the Future with Agentic AI
Agentic AI offers a rare opportunity for organisations to rethink how they create value, manage resources, and respond to market dynamics. Organisations that embrace these future possibilities will find themselves on the leading edge, not just surviving but thriving in a world where human skills are augmented by powerful, adaptive AI. By preparing today with a value-focused data strategy, organisations will be able to navigate this transformative journey, enhancing both their own capacity and that of the individuals within them.
Are you ready to make this part of your data and AI strategy?