Getting Real Value from AI

AI is now part of almost every company. Turning it into profit, however, is still something only a few manage. McKinsey’s annual survey, published in August with responses from 1,719 executives in 97 countries, puts numbers to that picture.

In this issue we picked the findings that told us the most, and looked at what they mean for companies doing business between the Netherlands and Türkiye.

People are gaining, companies not yet

80% of respondents say AI helps them do their work faster, and half say it helps them make better decisions. The share saying AI is being scaled across their organisation rose from 38% to 44% in a year.

Yet only 37% say AI has contributed to their company’s profit. That is almost exactly where it was last year.

This one sounds familiar. In most teams, AI starts as a personal habit: one person drafts emails faster, another speeds up presentations. The time saved is real, but nobody tracks where it goes. For it to show up in results, that time has to be put somewhere on purpose: more client conversations, quicker proposals, or a new service.

The gap with large companies is widening

54% of companies with more than $1 billion in annual revenue have scaled AI across the organisation. Among smaller companies it is about a third.

The biggest difference is in AI agents, systems that can carry out work steps on their own. At large companies, the share scaling agents jumped from 27% to 40% in a year. At smaller ones it stayed flat at 22%.

At first glance this looks like bad news for small and mid-sized businesses. We don’t quite see it that way. Changing a single process at a large company can take months; a smaller team can make the same move in a few weeks. The way to close the budget gap is to pick one or two areas where results can be measured clearly, and go deep there instead of experimenting everywhere at once.

What the leaders do differently

The most useful part of the report is about the small group that gets real value from AI. Companies that attribute at least 5% of their profit to AI make up just 6% of respondents.

They use AI for growth and innovation as well as for cutting costs. Nearly three quarters of them have redesigned their workflows around AI, compared with a quarter of everyone else. Visible commitment from senior leadership and regular measurement of results are also about twice as common in this group.

There isn’t a single technical item on that list, and to us that is the report’s most important message. The choice of model or tool is not what decides it. What decides it is the goal, how the work is rebuilt, and who owns it inside the company. That is why treating AI as a project to hand over to the IT department is the first mistake many companies make.

Costs and jobs: expectations meet reality

The running cost of AI is now part of the conversation. One in five companies say operating costs have led them to limit their use of AI. Even so, 60% of respondents expect investment to grow next year. And 32% have decided against buying at least one piece of software because they could build it in-house with AI coding tools.

The picture on jobs is calmer than expected. Last year, 32% of respondents expected AI to reduce their headcount; only 14% now report that it actually did. Just 13% say AI makes them anxious about their careers.

We take two things from this. AI isn’t free, and not every use pays for itself, so measuring where it actually helps is essential. And the anxiety in teams mostly comes from the unknown. In our view, the best answer is to show people how to use these tools in their own work.

Where to start

Reading the report, one question kept coming back to us: what should a company do tomorrow morning? Our answer is to start by choosing one outcome you want to change. It could be proposals that go out faster, communication that sounds the same in two markets, or more time for your sales team to spend with clients.

Then redraw the process that leads to that outcome, decide who owns it, and check a few weeks later what has changed. Starting small and growing what works gets results much faster than trying everything at once.

info@eddacreative.com · eddacreative.com

Global Mind, Local Soul.

Source: McKinsey & Company, The state of AI in 2026: On the road to ROI, 25 August 2026.