Is focusing on GenAI careers the answer? Because it’s paradoxically scary out here.

IT unemployment rose to 5.7% in January as AI continues to impact the technology market, according to the WSJ. The opposite is happening in human resources and talent management, where Robert Half reports a high demand for HR professionals. What may be enabling this change is that  72% of HR professionals now use AI weekly, according to HireVue’s 2025 Global Guide to AI in Hiring.

General Assembly’s study suggests more organizations have to address training gaps, as 54% don’t offer any AI training. While 54% of leaders encourage their teams to use AI, less than half (47%) report their teams regularly do so. But here’s the real data point to consider – while only 26% of executives believe AI could replace their roles in the next decade, 79% think it’s likely to replace some of their employees’ jobs.

AI will drive seismic changes in the leadership, skills, and numbers of people companies hire. For those in the market for new jobs, it’s important to reconsider new roles, marketable skills, and your career path. It’s time for many professionals to gear up for lifelong learning.  

AI is changing the expected skillset, and new AI leadership, implementation, and organizational change-related roles are emerging.

We discussed workplace transformation in the AI era and embracing new roles at a recent Coffee With Digital Trailblazers, a LinkedIn Live event I host on Fridays at 11 am ET. I committed to capturing 25 genAI roles and followed up with several experts for their expertise and opinions.

Three Key GenAI Careers Needed Today

Below are three key roles that organizations need and are hiring for today.

1.     AI Change Agents

Organizational leaders are going from genAI beyond a productivity tool to game-changing AI agents driving digital transformation. Top leaders introduce AI governance so employees understand the risks and guardrails when using company data in AI models, LLM tools, and agentic AI.

And how can departments, leaders, and employees adapt to all this change?

“Businesses need to upskill their workforces for the AI era, and that will require change agents to serve as champions for developing AI skills and use cases,” says Lupe Colangelo, director of alumni engagement and employee partnerships at General Assembly. “Technical leaders should partner with HR and talent teams to understand skills gaps and identify ways to close them, such as by creating new AI-focused talent pipelines or upskilling and reskilling programs for existing talent.”

AI change agents will likely have to develop specializations and domain expertise to understand AI-impacted workflows, communicate as department insiders, and help drive adoption.

 “To realize tangible AI business outcomes, companies should engage and embrace AI change agents who have both technical skills and deep knowledge of a specific business function,” says Rob Scudiere, CTO at Verint. “For example, to enhance customer experience (CX) automation, the change agent might be a contact center leader who thoroughly understands existing CX micro-workflows with a goal or mandate of increasing cost savings or revenue generation through AI-powered automation. To facilitate AI adoption and outcomes, change agents must also help other employees embrace change by serving as a resource and guide on new technologies and processes.”

2.     GenAI Business Analysts and AI Lead Developers

While explainable AI is a challenge, IT leaders will need to find ways to explain AI capabilities to gain stakeholder trust and demonstrate their value. IT may be developing AI agents or partnering with the chief data officer to take control of data and improve data quality, but releasing AI into production lags far behind POCs. According to Deloitte, 70% of organizations have moved 30% or fewer genAI experiments into production.

What’s likely needed is for organizations to boost the skillset of leaders of agile teams, especially business analysts and technical leads. Both these roles require hands-on skills to understand the technology and have the ability to explain implementation details to teams and stakeholders.

“Engineers have always had to reference third-party guides to write code, and it’s just gotten easier to access as time passes,” says Daniel Huss, AI instructor at General Assembly. “We started with books, then had online guides, and now we have a chat interface that helps generate code. What will never change is understanding and being able to communicate what you are trying to do on a technical level. Communication skills are essential if you’re heavily leveraging AI as a coding tool, which makes training on code assistants’ capabilities and limitations instrumental.”

3.     AI HR Business Coach and Workplace Futurist

HR leads can transition to two other roles extending beyond their traditional business partner roles. By developing deep AI expertise and understanding its people impacts, they translate how AI impacts employees, hiring, learning, hybrid workspaces, and the vast changes impacting people and culture.

“The former HR Business partner will evolve to the AI business partner and coach,” says Heather May, Founder and President of May Executive Search. “I also see roles for the workplace futurist, focusing on the future of work and workplace well-being leaders because people are uneasy about all the changes impacting work, including political, climate, and DEI.”

22 Emerging genAI careers

Thanks to the Coffee Hour speakers Derrick Butts, Martin Davis, Joanne Friedman, John Patrick Luethe, Heather May, Liz Martinez, and Joe Puglisi. Listen to the episode and view the collaborative dashboard we created for more details!

The genAI careers listed below are likely to grow in demand as more organizations adopt AI capabilities.

HR roles

4. AI Wellness Leader will research AI’s impact on people and extend work/life balance initiatives.
5. AI Career Developer will specialize in helping employees whose roles have been downsized because of automation and AI find new career opportunities.
6. AI Trainer will develop training programs as more SaaS tools embed LLM and AI agents.

Risk management, security, and AI governance roles

7. AI Ethics Leader will oversee the definition of AI ethics and consult teams on implementation. 
8. AI Legal Analyst and Risk Managers understand regulations and compliance functions and review AI implementations for risk.
9. AI Security Architect designs and implements AI-based security solutions.
10. AI Security Analyst monitors network traffic using AI algorithms and AI-enabled tools to identify suspicious activity and respond to security incidents.
11. AI Governance Leader works under the chief data officer to define and manage AI governance, including defining policies, implementing reporting tools, and responding to regulatory inquiries.
12. AI Data Quality Specialist specializes in unstructured data source data quality and classifying data for training AI models.

New Knowledge Management and Collaboration Roles

13. Ecosystem Networker purposefully connects people, partners, and skills to help the organization accelerate the development of AI capabilities and deliver business value.
14. Library Science Specialists will be assigned to mature taxonomies and categorize information across the organization to improve AI’s accuracy and ability to attribute sources.
15. AI Knowledge Leader works with department leaders to identify knowledge gaps and training issues to ensure SMEs exiting the workforce leave behind knowledge, playbooks, and tools for continuing the skillset and sharing their expertise.
16. AI Critical Thinking and Facilitator leads conversations with business leaders and employees on the art of AI’s new possibilities and guides departments to rebuild their operating models based on AI’s capabilities.
17. AI Rancher may hunt for shadow AI but focuses on identifying how employees use AI to improve productivity and which use cases to scale across the organization.

AI technology roles

18. AI Architect is highly knowledgeable on LLM and other AI models and guides teams on selections and implementation.
19. AI Solution Engineer works with the dev team on developing AI capabilities and understanding how to develop workflow experiences.
20. AI AR/VR Engineer will engineer experiences connecting IoT, AR/VR, and other real-world experiences with AI capabilities.
21. AI Scientist and Analyst develops and maintains RAGs and other AI models.
22. AI Agent Developer works on developing AI agents and upgrading web services to become agentic AI services.
23. AI Test Engineers and QA analysts develop regression test plans to validate AI model accuracy, performance, and AI agent functionality.
24. AI Diagnostician is the equivalent of an SRE for AI agents and models and is skilled at researching quality and performance issues and identifying root causes.
25. FinAI Specialist responsibilities are similar to those of FinOps, except they focus on AI cost optimization.

Leaders joining the StarCIO Digital Trailblazer Community can learn more about genAI careers and the learning to prepare for these emerging roles.