Why 2025 Will Be the Year of Agentic Automation

UiPath’s Raghu Malpani offers insights on why 2025 will be the year of agentic automation. This article originally appeared on Solutions Review’s Insight Jam, an enterprise IT community enabling the human conversation on AI.

In the past year, we’ve seen companies of all sizes and from a variety of industries adopt generative AI (GenAI) solutions with the hope of improving productivity and efficiency. While GenAI has been the shiny new AI tool of the last few years, there are more ways organizations can use AI to make decisions and manage end-to-end processes. The next phase of the technology’s evolution is agentic AI, and it will be more established across organizations by the end of 2025.

Agentic AI systems empower autonomous workflows and are capable of independent decision-making. An AI agent can analyze data, formulate strategies, adjust to new information, learn from experiences, and execute actions that serve a predetermined goal. The key differentiator between agents and the GenAI solutions that have been in vogue is that agentic AI can execute a series of strategic actions and adjust to new information all on its own.

For example, GenAI can create marketing emails, but an AI agent can autonomously send those emails to optimal recipients and adjust who those recipients are and what emails they should receive, based on real-time data and campaign goals.

According to Deloitte, 25 percent of companies that use GenAI tools today will launch agentic AI pilots in 2025. This number will grow to 50 percent in 2027, in part because AI agents have such varied use cases across organizations. Businesses view the technology’s most promising areas of implementation as software development, customer support, cybersecurity, and regulatory compliance. AI agents can test and debug code, resolve call center inquiries, identify data anomalies to protect against breaches, keep businesses in compliance through data management, and more.

The ability of AI agents to complete complex tasks autonomously continues to improve with increasing speed, but agents are still not yet widely deployed or adopted. This could change in the coming year, in large part because of the potential for agentic automation.

The Intersection of AI and Automation

For businesses, the value of AI agents greatly improves when they are used alongside automation. Agentic automation — the combination of AI agents, automation, and orchestration — expands the potential of AI agents by giving them the ability to take on end-to-end processes rather than only individual tasks.

Companies have long used robotic process automation (RPA) technology – software that enables workers to build digital robots to automate individual, repetitive tasks – and agentic automation is the natural step forward. Agentic automation uses those same robots that many organizations already rely on, alongside AI agents who can manage and direct those robots, to execute full processes. With humans-in-the-loop that can complete approvals and validations, agents will help automate business processes that are currently complex and consist of many non-deterministic steps, which are manual and often error-prone. Agents can adapt to new data and make intelligent and informed decisions to handle complex tasks.

As businesses gain confidence in agents, they will start to autonomously perform these actions, but always with a human in charge.

This combination enables a single employee to reach the productivity of multiple people, thus allowing the employee to work on other more strategic and fulfilling tasks. And, because AI agents can learn and change, agentic automation has the potential for customization and adaptability that has not been seen before in an automation solution.

By taking certain tasks off the plate of employees, agentic automation gives managers the availability to coach up and mentor their teams, doctors more time for patient care, developers the ability to fine-tune code, and client-facing employees the ability to deliver the personalized experiences they promise. Because of this, organizations of all sizes want to adopt and optimize agentic automation solutions to gain a critical leg up over their competition.

Implementation Challenges and Solutions

The benefits of AI agents and agentic automation are clear — higher productivity and efficiency, and more time for strategic and client-facing tasks — but challenges stall adoption and implementation.

Maximizing the value of AI agents and automated workflows requires orchestration between agents, digital robots, employees, and AI models. The issue is that AI models can be unpredictable, which makes their implementation into critical workflows a barrier for many organizations.

To overcome this, companies need to leverage modern solutions that enable the integration of agentic automation and complex business processes. This includes implementation, monitoring, and optimization of the technology integrations from start to finish so that organizations can ensure compliance, security, and governance by managing the rollout and data usage of models.

Agentic AI is the motor driving agentic automation workflows and processes, which is why AI agent adoption will pick up steam in 2025. Not only can the combination of AI agents and automation improve productivity and efficiency at exponential rates, but leveraging these technologies together will prove critical from a competitive standpoint.