Recruiting for the Agentic Future: New Roles and Skills for 2026

Agentic AI is transforming how work gets done. As autonomous agents become embedded in enterprise software, the talent landscape is shifting. New roles are emerging, existing roles are evolving, and the skills that matter are changing.

Organisations that want to thrive in the agentic era need to rethink their recruiting strategies. This article examines the roles, skills and hiring approaches that will matter in 2026 and beyond.

How agentic AI changes work

The rise of autonomous agents reshapes work in several ways. Many employees will shift from executing tasks directly to supervising agents that execute tasks. This requires different skills: oversight, exception handling and quality assurance rather than hands-on execution. Agents work across systems and functions, so employees need to understand how different parts of the organisation connect and how agents operate within that context.

Agent-enabled workflows are more fluid and adaptive. Employees need to be comfortable with ambiguity and rapid change. Working effectively with agents requires a different kind of collaboration—employees are not just working with other humans; they are part of human-agent teams.

Emerging roles

Several new roles are appearing in response to agentic AI. Agent operators are specialists who configure, monitor and maintain autonomous agents in specific domains, understanding both the technology and the business processes agents support. AI orchestrators focus on coordinating multiple agents to achieve complex outcomes, designing workflows, managing handoffs and ensuring agents work together effectively. Prompt engineers specialise in crafting effective instructions for AI systems—as agents become more capable, the ability to guide their behaviour becomes increasingly valuable.

AI ethicists and governance specialists ensure AI systems operate within ethical and regulatory boundaries, developing policies, conducting audits and addressing issues as they arise. Human-AI experience designers create effective interactions between humans and AI systems, understanding user needs, agent capabilities and how to combine them seamlessly. AI trainers and feedback specialists focus on improving AI systems through human feedback, training data curation and performance evaluation.

Evolving skills

Beyond new roles, existing roles require new skills. Agent supervision—the ability to monitor agent behaviour, recognise when intervention is needed, and take appropriate action—applies across functions, from customer service to finance to operations. As agents produce more outputs, critical evaluation becomes essential: the ability to evaluate quality, identify errors, and maintain standards. Trusting agent outputs blindly is dangerous.

Agents handle routine cases. Humans handle exceptions. The ability to diagnose unusual situations and develop appropriate responses is increasingly valuable. Agents connect systems and processes, so employees who understand how different parts of the organisation work together can leverage agents more effectively. Everyone needs baseline AI literacy—understanding what AI can and cannot do, how to work effectively with AI tools, and how to maintain appropriate oversight. And as AI capabilities evolve, adaptability becomes fundamental: the ability to learn continuously and adapt to changing circumstances.

Hiring strategies for the agentic era

Recruiting needs to evolve to find and develop the right talent. Assess for potential, not just current skills—AI is changing faster than training programmes can keep up, so hire for learning ability, adaptability and critical thinking. Specific skills can be developed.

Look beyond traditional sources. Agent operators do not need to be former software engineers. Domain expertise, combined with AI literacy, can be more valuable than pure technical backgrounds. Include AI tools in your assessment process to see how candidates work with AI, how they evaluate outputs, and how they handle situations where AI makes mistakes.

AI systems benefit from diverse input. Teams with varied backgrounds are more likely to identify biases, anticipate edge cases and build systems that work for everyone. Work with training providers to develop talent pipelines, defining the skills you need and helping shape programmes that develop them. And invest in internal development—many of the skills needed for the agentic era can be developed in existing employees. Upskilling is often more effective than external hiring.

Retention considerations

Finding talent is only half the challenge. Retaining it requires ensuring that employees who supervise agents still have meaningful work—human roles should involve judgement, creativity and impact, not just oversight of routine processes. Provide clear paths for growth as AI capabilities evolve. Compensation needs to reflect market realities as AI skills are in demand. And employees increasingly want to work for organisations that use AI responsibly—clear ethical commitments and practices help retain talent.

What leaders should do

If you are responsible for talent strategy, assess how agentic AI will change roles across your organisation. Identify the new skills and roles you will need. Review your recruiting processes to assess for AI-relevant capabilities. Invest in upskilling programmes for existing employees. Build relationships with training providers and educational institutions. And ensure retention strategies reflect the changing nature of work.

The organisations that build the right talent capabilities now will have a significant advantage as agentic AI becomes the norm.

The bottom line

Agentic AI is reshaping the talent landscape. New roles are emerging, existing roles are evolving, and the skills that matter are changing. Organisations that adapt their recruiting and development strategies to this new reality will be best positioned to capture the benefits of autonomous AI. Those that continue with traditional approaches will struggle to find and retain the talent they need.