Heads up, HR: 2025 is the year of agentic AI 

Despite slow take-up in HR and mixed reports about the return on investment (ROI), global executives see AI as the top business priority and the biggest potential value driver in 2025. Agentic AI is transforming company systems, processes and the workforce, and HR leaders who don’t prepare will be left behind.

To clarify, agentic AI isn’t exactly new. It already shapes our lives and can take many forms, from simple thermostats to air traffic control systems. But the next generation of agents running on large language models (LLMs) can function in a way that seems almost human.

Agentic AI is a complex, autonomous system that uses a mix of technologies to achieve goals without relying on constant human input. It learns, perceives, reasons, plans and even makes decisions by combining:

• The efficiency of robotic process automation (RPA)
• The natural language processing (NLP) of chatbots
• The trial-and-error of machine learning (ML)
• The processing power of LLMs
• The data-driven logic of predictive AI
• The novel outputs of generative AI (Gen AI)

The complementary features of these technologies are critical to delivering the benefits of agentic AI: 

Modern agentic AI is a giant leap forward. Other systems and bots can be reactive and input-dependent, like new hires awaiting their next assignment. AI agents are proactive, developing strategies, optimizing workflows, finding solutions and executing tasks to meet business objectives — all with minimal supervision.

The true power of agentic AI isn’t just in automation; it’s in augmentation. While other types of AI are excellent tools for specific tasks, agentic AI is uniquely suited to augment the workforce more broadly. Agents can mimic human reasoning, interactions and decision-making to effectively work alongside human employees, rather than just supporting them. When we blend human creativity with AI’s analytical capabilities, we create a workforce that’s greater than the sum of its parts.

As companies focus on the tools and capabilities they truly need, vendors and in-house teams are building AI agents that specialize in different functions. These agents might collaborate via multi-agent models, or even human-machine teams that work toward a shared goal.

Here are some common types of agents and how they could work with humans:

• Conversational agents support a range of self-service tasks, from workers’ time-off requests to managers checking employee availability.
• Functional agents can take on certain personas or roles, like a recruiting agent to screen candidates or explain role requirements.
• Supervisory agents might delegate tasks to other agents, assess workforce metrics in real time, and create reports for human managers.
• Utility agents support tasks at the direction of supervisory agents, like completing enrollment forms or sending routine notifications.
• All agents could, in theory, request human input when needed to mitigate risk — though it’s unlikely that every agent will be designed this way.

Navigating this fresh division of labor requires work design: deconstructing jobs into tasks; identifying which tasks are best performed by humans, technology or a combination of the two; and reconstructing new ways of working. The rise of agents allows for human input that’s less constant and more thoughtful, and thus fundamentally changes the nature of work. Many employees will pivot from task execution and prompt engineering to applying uniquely human skills such as empathy, creativity and ethical AI governance.

As AI increasingly mimics human behavior, discussing it in human terms can help us explain and understand it. NVIDIA CEO Jensen Huang went so far as to suggest that IT departments will become HR for AI agents. While it’s an interesting comparison, it’s fundamentally flawed: equating tools with talent diminishes the value of human contributions and the significant role of work in our lives. 

Let’s be clear: The human and digital parts of our workforce are not the same. IT will certainly handle the more technical, tactical side of agent adoption and management. But in a climate of cyber risk, cost optimization and skills shortages, the rise of agentic AI poses new challenges and opportunities for HR to consider.

While HR and IT clearly aren’t merging anytime soon, managing human-machine teams will require both functions to work together and learn from each other. IT might focus more on orchestrating the optimal combination of technologies; HR can help business leaders redesign work around AI’s capabilities while ensuring the seamless development and deployment of the new skills required.

These joint efforts might also include a system of record for agents. Much like human capital management (HCM) software or a human resources information system (HRIS), an agent system of record can help organizations manage in-house and third-party agents, from onboarding to monitoring to compliance. This becomes more important as more agents get added to the company roster.

This is the Year of Agentic AI — and with HR functions on track to show early achievements, the future of work is brighter than ever. Executives think AI and automation will have the biggest impact on cost optimization this year, so conversations around cost and efficiency can help secure buy-in for agents. But the greatest return comes from empowering people to do more impactful work.

As business leaders double down on AI this year, maxing out ROI requires a full-scale digital transformation. It’s about realigning every part of the business around AI: core systems and processes, innovation and strategy, insights and reporting, analytics and decision-making, team structures and tech stacks, governance and compliance, investments and risk management.

Many organizations have begun their AI journey, and they’re ready to keep scaling. If you want to better understand or even deploy AI agents, here’s what to consider:

Ready to master the future of work with agentic AI? Get in touch, and let’s talk deployment.