“AI will take over all IT roles over the next 2-3 years, leaving IT career employees out of the job as top CIOs move into business leadership roles.”

No one ever said that statement, and I don’t believe it for a second.

But as more of IT automates its operations and AI generates more code, many employees feel a sense of doom about their IT careers, and some are retiring early. Graduates are increasingly angered by the impact AI is having on employment opportunities.

Meanwhile, many companies are reducing their IT workforce or holding back on hiring entry-level roles. Now, even the economists recognize AI’s impact on jobs.

Many CIOs take an active role in planning IT skills training and helping top employees gain certifications. Most will take performance management programs seriously so that employees receive feedback and compensation awards are equitable. Many participate in mentoring programs.

But not enough CIOs take the next step and guide employees on career planning. This is a mistake, when so many IT roles are being disrupted by AI’s capabilities.

Experts suggest asking these five questions to get started with who and how to guide IT career planning with high potentials and emerging leaders.

1. Who is on board with the AI strategy?

Let’s first consider developers who are facing the most change due to AI code generation, vibe coding, and spec-driven development. CIOs first need an AI strategy and governance model – and then need to see who’s embracing it while adopting new responsibilities.

Vishnu Shankar, chief data officer at Draup, shared data from The Polycentric Tech Workforce showing that 40% of IT skills face partial obsolescence by 2027, concentrated in areas where entry- and mid-level work sits. “The debate about AI reshaping developer roles is over. The harder problem for CIOs: most orgs have no signal for who’s adapting; that gap only surfaces in reviews or exits,” says Shankar.

Shankar shares these three recommendations for CIOs:

• Evaluate who’s reviewing AI-generated code and improving outputs.
• Assign ownership, not tasks, and put developers in roles where they own decisions with real consequences.
• Make mobility visible, because if the path from execution to judgment isn’t clear, talent with options will leave.

2. What technical skills should high potentials learn?

Several experts suggest that CIOs take a more active role in reviewing where top employees invest in skill development. Their suggestions:

• Architecture and systems thinking – “An architectural perspective matters, as AI absorbs the boilerplate work, developers move from the weeds to connecting the dots across a system,”  says Hannes Hapke, director of the 575 Lab at Dataiku. “Ultimately, AI loses sight of requirements spanning multiple codebases, and humans hold the big picture. This shift toward design and systems thinking should be framed as a step up in their careers, not a step out.”
• Data management and AI context engineering – “AI is accelerating what developers can do, and most organizations want their teams to embrace it,” says Tim Dalton, group project manager at Redgate Software. “But CIOs need to understand the risks that come with that, particularly in the database, where AI tools operate on whatever data sits in the dev and test environment.”
• AI and data governance – “AI is changing the work IT teams do, but many companies are training people on prompts while ignoring the harder problem underneath: information quality,” says Stéphan Donzé, CEO at AODocs. “CIOs who want AI to succeed need to help employees build skills around managing and governing the data AI depends on. Teams that can maintain trusted knowledge will increasingly determine whether AI creates value or creates noise.”
• AgenticOps specialists and SREs – “CIOs should prioritize upskilling their teams in AI governance, compliance, and operational control with modern AI tooling,” says Nikhil Mungel, head of AI R&D at Cribl. “Engineers and practitioners who can govern, monitor, and deploy AI systems safely at scale will be more resilient as roles evolve and more differentiated in a crowded market.”

3. What are IT role growth areas in your organization?

Employees in IT operational roles have already experienced a wave of change from automation. AI is enabling consolidation between IT Ops and SecOps, but CIOs are also facing greater demands for SREs.

In developer roles, I expect CIOs may need fewer coders but many more product managers and QA specialists.  

“The fear is real because typically people associate automation with replacement,” says Alejandro Duarte, developer relations engineer at MariaDB. “I don’t think that’s the case, and think it should be reframed as automation is augmentation”

Duarte suggests these growth paths that are directly tied to growing AI needs.

• AI orchestration – Building and maintaining AI agents and RAG pipelines.
• Data curation – As AI takes more and more coding tasks, humans must own the “what”, that is, the data quality and governance.
• Infrastructure – You cannot just let AI agents “try” fixes in production; you must own production.

At an episode of Coffee With Digital Trailblazers covering workplace transformation, we brainstormed 25 genAI roles. These included several novel ideas, such as AI change agents, AI diagnosticians, and Ecosystem Networkers. CIOs should consider developing apprenticeship programs to guide people into new roles.

4. How should CIOs position role changes?

Even before the AI era, I advised CIOs to avoid using the word automation as it sends the wrong message to employees and unrealistic expectations to executives.

Rather than overstating what IT will not be doing, or doing less of because of AI’s capabilities, CIOs should clearly communicate what their organizations need more of.

“For developers, the integration of AI isn’t a career threat; it’s an automatic promotion from writing manual code to acting as engineering leads who orchestrate and evaluate what these models construct,” says Miles Ward, CTO of AI at Insight. “CIOs have to adapt career paths to prioritize cross-training, say pairing developers with operators, architects, and SME’s, and give their development teams the new tools to help them completely collapse the time between idea and quality output.”

Review some of my previous articles when crafting and communicating career paths:

• 7 Rewarding Career Paths for the Fearless Agile Program Manager
• 3 Ways for Product Managers to Promote Their Career Paths
• 5 Ways Ambitious DevOps Engineers Can Advance Their Careers

5. What are the leadership and soft skills to reinforce?

Beyond roles and skills, CIOs must build career paths for future AI and digital transformation leaders, i.e., Digital Trailblazers! See my career checklist and transformational leadership competencies for ideas. For those early in their careers, start by reinforcing “soft skills” that show leadership potential.

“Critical thinking is what keeps the developer role valuable,” says Hapke of Dataiku. “AI is fast and broad, but it still makes mistakes, and we’ve all seen it write 10,000 lines for a simple file lookup. The developers who thrive will know which questions to ask of AI output, including whether it is correct. Is it appropriate? Is it maintainable?”

Keep in mind that AI is only reshaping business. It will take a new generation of transformational leadership to drive business model evolution. As I wrote in Digital Trailblazer, “You will always be transforming.”