Navigating the Changing Tech Hiring Terrain
The demand for specialized IT talent continues to evolve, with new challenges emerging as technologies advance. While roles like SOC analysts and cloud architects remain relatively easy to fill, hybrid positions requiring expertise across multiple domains are proving most elusive.
According to the 2026 State of the CIO Survey by Foundry/CIO.com, AI/machine learning and cybersecurity now share the top spot as hardest-to-fill IT roles—a trend that has remained consistent over the past two years. Data science and analytics follow closely behind.
The Shift Towards Operationalizing AI
The initial frenzy for LLM engineers has subsided, giving way to a greater need for professionals who can operationalize AI at scale, manage its risks, and ensure responsible use. Organizations now seek:
- AI product engineers who can deploy agents, build testing frameworks, and optimize performance across cost, latency, and quality dimensions
- Governance and red-team specialists to identify vulnerabilities and ensure ethical AI practices
- Security analysts skilled in using AI to enhance cyber defenses while addressing increasingly sophisticated attacks
“The most challenging roles require a blend of technical expertise and business acumen—people who can bridge the gap between innovation and implementation,” explains Niel Nickolaisen, IT advisor at Valcom Technologies.
Key Takeaways from the 2026 Survey:
| Skill | Rank (2026) | Rank (2024) | Change |
|---|---|---|---|
| AI/Machine Learning | #1 (tie) | #1 | Steady |
| Cybersecurity | #1 (tie) | #2 | Rising |
| Data Science/Analytics | #3 | #3 | Steady |
| Business/IT Automation | #4 | #4 (tie) | Steady |
| Risk Management | #5 | #8 (tie) | Rising |
| Software Engineering | #6 (tie) | #6 (tie) | Steady |
| DevOps/DevSecOps | #6 (tie) | #11 (tie) | Rising |
| Enterprise Architecture | #8 (tie) | #10 (tie) | Rising |
| Cloud Services/Integration | #8 (tie) | #12 (tie) | Rising |
| Cloud Architecture | #8 (tie) | #6 (tie) | Falling |
Addressing the Skills Gap
As AI continues to evolve rapidly, organizations should focus on:
- Prioritizing individuals with broad understanding and a demonstrated ability to learn quickly
- Seeking candidates who can adapt to new tools and platforms rather than requiring specific experience
- Investing in reskilling programs that equip existing employees with the emerging skills needed for AI governance, risk management, and responsible deployment
The talent landscape is shifting from those who build models to those who effectively wield them—a critical distinction as organizations increasingly rely on AI-powered solutions.