Follow ZDNET: Add us as a favorite source On Google.
ZDNET Highlights
- Professionals are urged to move into AI roles, but which ones?
- Four emerging roles will lead the agentic AI revolution.
- Managing agents requires both business and technical skills.
Study after Study Urges everyone to join the artificial intelligence and agentic AI train, with the promise of significantly higher incomes and greater job security. This pressure to move into AI-enabled roles leaves technology and business professionals with a burning question: What are exactly the roles they need to prepare for? Who will lead the agentic revolution?
For professionals with technology skills, at least four emerging job roles are emerging, particularly with the rise of agentic AI. I recently discovered these opportunities andy dovganCreatio’s Chief Development Officer, who identified their emerging roles: AI leader, agent operator, AI no-code creator, and workflow architect.
Also: Do you have AI skills? You Can Earn 43% More in Your Next Job – And Not Just for Technical Work
“AI isn’t just being added as another layer of automation,” Dovgan explained. “This requires the creation of new workflow architectures. It is reshaping how work is designed, executed and controlled.”
At the same time, he added, “These roles will not emerge overnight. They will evolve from existing business, operations and technology roles.” The skills sought require “a deliberate blend of business expertise, AI literacy and no-code configuration.”
The common formula is ownership
Such new roles include the following four:
- AI Leader: AI leaders are “responsible for transforming AI from technical capability to business value, ensuring it is used responsibly and strategically,” Dovgan said. “This role has no defined path and is attracting change agents focused on innovation. They oversee the application of AI across an organization, the definition and execution of strategy to deploy agentic use cases. They bridge human and digital talent.”
- Agent Operator: These individuals are essentially “human observers” of the agentic workflow. “They monitor execution, intervene when needed, and ensure accuracy, compliance and business continuity,” Dovgan explains. “These roles typically emerge from the business and operations side, with a deep understanding of the workflows being automated and the results those workflows should deliver.”
- AI No-Code Creator: These professionals design, test, and deploy AI agents using no-code tools. “These roles evolve from business analysts, process owners, automation leaders and digital transformation teams who already understand how work should flow across the organization,” Dovgan said. “With no-code AI platforms, they go beyond documenting requirements to proactively shape agent goals, constraints, and behaviors.”
- Workflow Analyst: These individuals take a holistic view of how humans and agents work together to accomplish tasks. “At its core is a deep understanding of business functions and workflows,” he adds. “An agentic model requires strong business analysis to redesign work, not simply replicate manual or rule-based processes. Agents work within real operational constraints, and without domain expertise, they will optimize for the wrong outcomes.”
The common thread across all of these roles is ownership — “ownership of results, accountability for agent behavior, and constant adaptation as business conditions change,” Dovgan said.
Initially, getting started with agentic AI may require external help as internal teams develop their expertise and experience. “This change elevates internal IT and operations teams,” Dovgan predicted. “They will need to learn new skills and apply different approaches to agentic automation because previous playbooks will not work.”
Also: Deploying AI agents isn’t your typical software launch – 7 lessons from the trenches
In terms of external expertise, at this stage in the market, “the ecosystem will be hybrid and fluid, not dominated by a single player type,” Dovgan predicted. “AI vendors will increasingly implement forward-deployed engineering approaches, working hand-in-hand with customers to design, tune, and operate agents. In parallel, global consulting firms will make significant investments in agentic practices with deep expertise in enterprise processes, governance, and compliance. Niche boutique companies will emerge, bringing deep AI expertise focused on specific domains, industries, or use cases.”
