AI is becoming part of how businesses operate, make decisions, and run technology initiatives. This shift is also changing the demand for IT talent.

This does not mean the need for IT talent is shrinking. On the contrary, the required competency standards are starting to shift.

Technical ability remains the foundation. However, companies also need talent who can use AI effectively, understand business context, evaluate AI-generated output, and still maintain the quality, security, and reliability of their work.

This shift means IT talent search strategies need to evolve as well.

IT Skills Are Changing as Ways of Working Change

The shift in skill needs is already visible.

LinkedIn, through its Skills on the Rise 2025 report, found AI literacy to be one of the fastest-growing skills across countries and job functions. For engineering and IT functions, skills related to Large Language Models (LLM) also emerged as one of the fastest-growing skills.

LinkedIn also estimates that around 70% of the skills used in most jobs will change between 2015 and 2030, with AI as one of the catalysts of that change.

This shift shows that AI's impact on the workforce is not limited to creating new roles directly related to AI.

AI is also starting to change the competencies required for roles that already exist.

Technical Experience Alone Is Not Always Enough

For years, companies have looked for IT talent based on a combination of role, experience, and specific technical skills.

That approach is still relevant. However, as AI enters the workflow, companies need to look beyond a candidate's list of mastered technologies.

IT talent increasingly needs the ability to work in a constantly changing environment.

For example, AI can help speed up certain activities in software development. But the ability to use AI does not mean accepting every output without evaluation.

Talent still needs to understand the logic, architecture, security, business requirements, and risks of the solution being developed.

In other words, AI literacy needs to go hand in hand with technical judgment, problem solving, adaptability, and an understanding of business context.

This is what makes finding IT talent in the AI era more than just finding people who have used AI tools before. What matters more is understanding whether their competencies are genuinely relevant to the project's needs and the organization's way of working.

Looking at Talent Needs Through Capability, Not Just Job Title

This shift also affects how organizations plan their workforce.

A role-based approach usually starts from the position that needs to be filled. A capability-based approach looks further: what competencies need to be available for a project to run well.

The difference looks simple, but the implications are significant.

A single project may require a different combination of technical expertise, AI literacy, industry understanding, communication, and problem-solving. These needs can also change as the project moves into its next phase.

This is why workforce planning is becoming increasingly dynamic.

Businesses need to understand the capabilities already available internally, the capabilities that still need to be developed, and the capabilities that need to be brought in externally to support specific needs.

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Related article: Read also Why Traditional Hiring Strategies Are No Longer Enough for Modern IT Projects to see how recruitment time and time-to-productivity can affect your project timeline.

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The Challenge Is Not Just Finding Talent

As skill needs change faster, finding the right candidate is only part of the challenge.

Businesses also need to consider availability, onboarding time, understanding of project context, and the time needed before someone can contribute productively.

At the same time, not all capabilities are needed permanently.

Some needs are strategic and long-term, making them suitable for internal development. Others arise for a specific period or project.

This is why an adaptive workforce strategy does not have to rely on a single approach.

Permanent hiring, internal upskilling, and external expertise can be used together, depending on the nature of the business need.

The focus shifts from simply adding headcount to ensuring the business has access to relevant capability when it is needed.

What Makes IT Talent AI-Ready?

In the context of the IT workforce, AI-ready is best understood as talent's readiness to work effectively in an environment where AI is increasingly integrated into work processes.

At least a few characteristics are becoming increasingly relevant:

Strong technical foundation

AI can speed up work, but technical understanding is still needed to evaluate output quality and make the right decisions.

AI literacy

Talent needs to understand how AI can be used in the workflow, including its benefits, limitations, and context of use.

Critical judgment

AI output still needs to be verified. The ability to evaluate results is just as important as the ability to use the tools.

Adaptability

Tools and ways of working can change quickly. Talent who can learn new approaches will be better prepared for changing project needs.

Business understanding.

Technology is ultimately used to solve business needs. Talent who understand this context can contribute more relevantly than those who simply complete technical tasks.

This combination is what makes workforce readiness for AI broader than simply having an “AI specialist” on the team.

AI-Ready IT Professional Services: Strengthening Capability, Not Just Adding Resources

The shift in skill needs means the approach to IT Professional Services needs to evolve as well.

A model that focuses only on providing resources is becoming less adequate as organizations need a more specific combination of competencies, one that can change according to project needs.

AI-Ready IT Professional Services starts from a capability-based approach

This means needs are not viewed only in terms of the number of resources or job titles to be filled. The focus is on understanding the capability a project needs, the relevant level of competency, and how that talent can integrate with the existing team and way of working.

This approach allows organizations to strengthen team capacity without turning every new need into permanent headcount.

As project needs change, the capability brought in can also be adjusted. Organizations can retain strategic competencies within the internal team, develop skills through upskilling, and use IT Professional Services to fill capabilities that are not yet available or are needed only for a specific period.

In the context of AI, this flexibility becomes increasingly relevant.

Technological change can make skill needs shift faster than traditional recruitment and workforce development cycles. Organizations need a way to bridge that gap without losing project momentum.

This is where AI-Ready IT Professional Services can play a role as part of workforce strategy: helping bring in talent with a relevant technical foundation, the ability to adapt to AI-enabled workflows, and readiness to contribute according to project needs.

Not just providing more talent.

But helping ensure the capability the business needs is available at the right time.

Building an IT Team Ready for Change

AI is likely to keep changing tools, workflows, and expectations for IT talent.

That is why workforce strategy also needs to move from a static approach toward a more adaptive model.

Permanent hiring remains important. Upskilling is still needed. External expertise can also be part of the strategy when organizations need a specific capability faster or for a specific period.

Companies that can combine all three will have more room to adjust their team's capacity and competency as technology needs change.

An AI-ready workforce, in the end, is not about having as many talents as possible with an AI label.

It is about building a team with the right combination of competencies, strong learning ability, and readiness to work in a way of working that keeps evolving.

Prepare Your IT Capability for What's Next

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