As agentic AI moves from experimentation into real business operations, a new class of roles is emerging to manage, govern, and scale autonomous systems. Many professionals urge to “get AI skills”. Meanwhile, industry leaders argue the real opportunity lies in clearly defined roles that combine business ownership with technical fluency.
According to insights shared by Andie Dovgan, chief growth officer at Creatio, agentic AI is not simply another automation layer. Instead, it is reshaping how work is designed, executed, and governed across organizations. As a result, four emerging roles are positioned to lead the agentic AI revolution, each focused on ownership and accountability rather than pure model development.
The first is AI leaders, responsible for translating AI capabilities into business value. These roles oversee agentic strategy, ensure responsible use, and align AI deployments with organizational goals. Rather than following a fixed career path, AI leaders often emerge from innovation, transformation, or senior operational roles.
Second are agent operators, who act as human supervisors for autonomous workflows. They monitor agent behavior, intervene when necessary, and ensure compliance, accuracy, and continuity. These roles typically evolve from operations or business teams with deep domain expertise.
The third group, AI no-code creators, design and deploy agents using no-code or low-code platforms. Often originating from business analysis or automation teams, they move beyond documenting requirements to actively shaping agent goals, constraints, and behaviors.
Finally, workflow analysts (or workflow architects) take a systems-level view of how humans and agents collaborate. Their role is to redesign processes for agentic models rather than replicate legacy workflows, ensuring agents optimize the right outcomes within real operational constraints.
Key takeaways for professionals and organizations:
- Agentic AI leadership roles are emerging from existing business and tech functions
- Ownership and accountability are the defining characteristics across roles
- Managing agents requires both domain expertise and AI literacy
- No-code platforms are accelerating non-technical participation in AI deployment
As organizations scale agentic AI, these roles will evolve incrementally rather than appear overnight. Those who develop end-to-end ownership of outcomes—rather than narrow technical specialization—will be best positioned to lead the next phase of enterprise AI adoption.
Source:
https://www.zdnet.com/article/4-new-roles-will-lead-agentic-ai-revolution/
