Most Companies Have an AI Plan. Far Fewer Have Redesigned the Work.

Most companies can now point to something that looks like AI progress. They have bought tools, launched pilots, trained teams, and told the board they have a strategy.

But inside the organization, a harder question is still unresolved:

What actually changed in the work?

Which decisions should now be automated? Which still require human judgment? Which responsibilities have become more important? And if the title stayed the same, is it even the same role anymore?

That is the real gap in most AI efforts. Not awareness. Not access. Not experimentation.

Role clarity.

The scale of the shift is real. The World Economic Forum says employers expect 39% of workers’ core skills to change by 2030, and LinkedIn says 70% of the skills used in most jobs are expected to change by 2030, with AI acting as a major catalyst.

Microsoft and LinkedIn’s 2024 Work Trend Index found that 75% of global knowledge workers were already using AI at work, but many leaders still said their organizations lacked a clear plan and vision for turning individual use into business impact. McKinsey’s 2025 research adds the missing piece: the value of AI comes from rewiring how companies run, and workflow redesign is one of the strongest predictors of bottom-line impact.

That is why “AI adoption” can be a misleading metric.

A company can have licenses, pilots, and employee activity and still have no shared answer to the most important question:

What is the role now?

A role is not just a title. In practice, a role is a bundle of outcomes, decisions, interfaces, capabilities, and risks.

When AI changes even part of that bundle, the role changes.

Sometimes the title stays the same, but the work underneath it shifts. A recruiter may spend less time on manual screening and more time on evidence quality. A product manager may spend less time collecting inputs and more time shaping judgment. A financial advisor may spend less time documenting meetings and more time being present in them.

That is not just productivity gain. That is role redesign.

The organizations moving well on AI are starting to reflect that reality.

Morgan Stanley, for example, launched AI tools that help advisors summarize meetings, draft follow-ups, and reduce documentation burden while keeping the human relationship at the center. The point was not to remove the advisor. It was to free up more of the advisor’s time for trust, context, and judgment.

Bayer has publicly described collecting hundreds of generative AI opportunities across functions, showing that the shift is not contained to one team or one use case. It spreads across roles and workflows in uneven ways. Dow has shown another pattern: applying AI inside high-value operational workflows where better exception handling and better decisions have measurable business impact.

These examples point to the same lesson.

The companies seeing real value are not just asking which tools to buy. They are asking:

What outcomes does this role now own?
Which parts of the work can be automated, accelerated, or augmented?
Where does human judgment still matter most?
What new capabilities and evidence now matter?
How should hiring, onboarding, and performance evolve as a result?

That is a much more useful sequence than starting with a tool.

Deloitte’s 2026 Human Capital Trends makes the same point from a different direction: organizations that intentionally redesign roles, workflows, and decision-making to support human-AI collaboration are more likely to exceed expectations on investment returns and deliver meaningful work. IBM has also reported that AI-first organizations are more likely to create new roles and redesign organizational structure.

So the question for leadership teams is not just whether AI is being used.

It is whether the organization has become clearer about work.

What is the work now?
What is the role now?
What belongs to AI?
What still belongs to people?
What judgment matters more because AI exists?

The companies that answer those questions well will not just use AI more. They will hire better, train better, redesign work faster, and make stronger decisions than companies still treating AI as a software rollout.

We’re studying exactly this shift: how AI is changing work, how roles are being redefined, and where organizations are still struggling to create clarity.

If this is a decision you are working through right now, a 30-minute conversation is the fastest way to test it against your own workflows.