Hiring trends indicate that employers are not simply eliminating technical jobs because of artificial intelligence — they are redefining them. New data from Dice, explained by its president, Paul Farnsworth, shows a dramatic rise in demand for AI-related capabilities and a shift in the kinds of work engineering and IT teams are being asked to do.
Numbers underline a rapid shift in hiring
Farnsworth told Digital Journal that recruiters and hiring managers are asking a different question now: not whether AI will replace people, but how it changes the nature of their work. The platform’s analysis found that demand for AI skills has climbed sharply, with postings for AI and machine-learning roles accelerating and a large share of tech job advertisements now listing at least one AI requirement.
“We’ve spent the last year asking the wrong question. Instead of asking whether AI is replacing jobs, we should be asking how it’s changing the work people do.”
Key figures from Dice’s research include a 380 per cent increase in demand for AI skills since early 2024, a 173 per cent year-over-year growth in AI and machine-learning job postings, and the finding that about three-quarters of tech job listings now request at least one AI-related skill.
| Measure | Change |
|---|---|
| Demand for AI skills (since early 2024) | +380% |
| AI & ML job postings (YoY) | +173% |
| Tech job postings requiring AI skills | ~75% |
Three distinct ways AI is showing up at work
Farnsworth identifies three practical categories where employers are integrating AI into operations, and each has implications for hiring and team structure.
- AI in products — Companies are embedding generative AI or other AI features directly into customer-facing products or retrofitting existing offerings to include intelligent capabilities.
- AI at work — Technology teams are building the infrastructure, governance and training that allow employees across an organisation to use AI securely and effectively.
- AI agents — Organisations are beginning to deploy autonomous agents that can operate across enterprise systems to perform tasks without continuous human direction.
Each category demands different combinations of skills. Product teams need engineers who can design and integrate ML models; platform and security teams must enforce policies and build reliable pipelines; and operations groups will be tasked with supervising agents and maintaining enterprise integrations.
Institutional knowledge and systems expertise gain value
Farnsworth also stresses that as AI spreads through businesses, deep familiarity with company systems and institutional knowledge will become more important, not less. That expertise helps organisations understand where AI can add value, how to mitigate risks and how to preserve business continuity when models or agents behave unexpectedly.
In practical terms, that makes roles focused on systems engineering, platform reliability and data governance more strategic. Rather than a simple trade-off between automation and head count, employers are shifting hiring priorities toward people who can place AI into operational context and keep enterprise systems running.
For workers, the message is twofold: technical literacy in AI-related tools and concepts is increasingly expected, but the kinds of human skills that prevent breakdowns — systems thinking, institutional memory and governance — remain critical. Employers appear to be combining both approaches by seeking candidates who pair AI familiarity with deep operational competence.
As organisations experiment with product-grade AI features and internal agents, the balance of responsibilities in engineering and IT teams will continue to evolve. The immediate result is not wholesale elimination of technologists, according to Dice’s analysis, but a redefinition of roles and fresh demand for expertise that ties models to real-world systems and business processes.
That reframing should shape how hiring teams, educators and workers plan for the next phase of tech employment: less about whether AI will take jobs and more about how it will change the skills those jobs require.
