Why are companies struggling to hire data and AI talent while experienced professionals struggle to find the right roles?

For years, the data and AI talent market was predictable. Roles were defined, skills were clear, and hiring followed established patterns.

That is no longer the case.

In 2026, roles are changing faster than companies can define them. AI is compressing work, reshaping teams, and increasing expectations for individual impact. Hiring demand remains high, yet many roles stay unfilled. At the same time, experienced professionals struggle to position themselves for what companies actually need.

The latest Data Masterclass community call focused on this shift. The session brought together Alexander Borek and Aleksejs Plotnikovs (Data Masterclass) and Matthew Miles (MAM Group).

One theme came up consistently. The market feels misaligned because the way companies define roles and hire talent has not kept pace with how work is changing.

The Talent Market Paradox

More people are applying for data and AI roles than ever before. At the same time, companies continue to say they cannot find the right candidates. Roles stay open for months despite high demand.

As Alexander added, “A lot of people are looking for jobs, but hiring teams can’t find who they need.”

The gap shows up in expectations. Companies look for people who can handle problems end-to-end, combining technical work with business understanding and execution. These profiles exist, but they are not easy to define or evaluate.

Where the Mismatch Happens

Role definitions have not caught up. Job descriptions focus on tools and responsibilities, while hiring decisions depend on something else entirely.

• Job descriptions list tools and responsibilities, but do not describe the outcome the role is expected to deliver
• Hiring teams are not aligned on what success looks like
• Candidates apply based on the description, but get evaluated on different criteria

This carries into the hiring process.

Many roles attract hundreds of applicants and still remain open. Strong candidates get filtered out, decisions slow down, and the search continues without a clear definition of the target profile.

Roles Are Collapsing Into Broader Profiles

AI changes how we work. Tasks that previously required multiple roles now sit with one person supported by AI. Fewer handovers. More direct ownership of outcomes.

As Aleksejs described it, “There is no time to build transition bridges. We are already in it.”

The effect is visible in role boundaries. Distinctions between analysts, engineers, and product roles matter less when the same person is expected to take a problem from start to finish.

This shifts expectations. Instead of specializing in one function, people need to connect different capabilities and apply them in context. Technical skills, business understanding, and execution come together in a single role.

The “unicorn” profile reflects this shift. Not defined by deep specialization, but by the ability to combine skills and deliver outcomes without relying on multiple handoffs.

What Actually Matters Now

Technical skills still matter, but they are no longer enough to stand out. Many candidates meet the technical requirements. Hiring decisions are made on different signals.

As Matthew said, “The ability to explain why something was done matters more than the technical answer.”

Companies look for people who can communicate clearly, influence decisions, and work through unclear situations. The ability to operate without complete information has become part of the role. This applies across both leadership and technical positions.

What separates strong candidates is how they describe their work. It is not just about what was built, but why it mattered and what changed as a result. Measurable impact carries more weight than a list of responsibilities.

Career paths reflect the same shift. Titles matter less than the range of experiences behind them. People who have worked across different environments, solved different types of problems, and can connect those experiences in a clear way have an advantage.

The focus moves from skills in isolation to outcomes and context.

What This Means Going Forward

The talent market reflects a broader shift in how organizations operate.

For Leaders

Hiring needs a different starting point. Focus on the problem to be solved, not the role. Fewer hires with clear expectations create more impact than scaling teams without alignment. Defining what success looks like early reduces confusion during the hiring process.

For Individuals

Career paths are less structured than before. Progress comes from building experience across different areas rather than staying within a single role. Working with AI and agentic systems becomes part of the baseline. The focus shifts from accumulating skills to applying them in context.

The current model of roles and hiring is under pressure. Roles are changing faster than companies can define them. Skills are evolving faster than job descriptions can capture them. The advantage goes to those who adapt quickly and focus on solving real problems.

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