Is 2026 the year AI delivers return on investment? European companies and governments will certainly hope so. The impetus to turbocharge economic growth and productivity has never been greater. When used wisely, AI is the most powerful tool available to make this happen. IBM is a clear example: more than $4.5B of productivity gains made in the past two years by deploying 155 AI solutions across workflows, from sales to HR.
Like elsewhere, many enterprises in Europe are still struggling to convert AI into ROI, but new research from IBM’s Institute for Business Value suggests optimism is growing. The Enterprise in 2030 study, which surveyed 2,000 C-suite executives across 33 countries, reveals most respondents are confident their organisations can turn AI investment into value within just a few years. More than 80% of European business leaders expect significant AI-driven revenue by 2030, despite only 24% being able to clearly identify that source of revenue.
Make way for the smarter enterprise
What the majority of European respondents can agree on is that AI-led growth will be driven more by innovation than efficiency. This points to a new era of the “smarter enterprise” – AI-first, intelligent, with real-time responsiveness to changing dynamics. While it’s too soon to say what will create new revenue streams in 2030, leaders can start building the foundations of a more intelligent business today, so they are set up to capture the market opportunities of tomorrow. There are three trends they should keep in mind.
Trend 1: Today’s productivity gains should fund tomorrow’s transformation
Our research shows European executives expect AI to boost productivity by 41% by 2030, with most organisations capturing the bulk of those gains well before then. But efficiency is only AI’s opening act. The main event is transformation – of business models, innovation timelines, revenue streams, and ways of working.
More than half of European leaders believe AI will have transformed business models in their industry by 2030, and 72% plan to reinvest productivity gains into growth and innovation, rather than simply banking them as savings. This creates a flywheel effect: productivity frees up resources, those resources fund innovation, and innovation reshapes the business model — driving further growth in return.
In an AI-first economy, cost reduction is easily copied. Using productivity as growth capital is not. The enterprises that win will be those that treat efficiency not as the destination, but as the fuel for reinvention.
Trend 2: The best AI will be one of a kind
As AI becomes ubiquitous, advantage will come from uniqueness, not scale. The winners of the next decade will not be those running the biggest models, but those using AI in ways competitors cannot replicate – grounded in proprietary data, deep domain knowledge, and tightly integrated operations.
This is where Europe, with its strong industrial base, has a significant advantage waiting to be tapped. There are retailers, automotive producers and medical device manufacturers with decades of data that only they possess; a goldmine of potential customer value.
In addition, foundation models are becoming commoditised. Differentiation now lies in smartly assembled AI portfolios: combining large language models for general reasoning with smaller, customised models for specific tasks, security requirements, or edge applications.
This matters because tailored AI performs better. Globally, organisations planning to scale AI through fit-for-purpose models infused with enterprise data expect 24% higher productivity gains, 55% greater operating-margin improvement, and twice the reduction in process and delivery times by 2030 compared with those relying on pre-trained models.
The shift required is strategic and technical. Unique AI is not built one model at a time, but managed as a dynamic portfolio that can adapt to market swings, regulation, and business priorities. Unique AI also depends on having enterprise data at the core, underlining the importance of hybrid cloud infrastructure.
The smartest enterprises will treat AI portfolios as competitive assets in their own right, to be evolved, partnered, and monetised. And they will focus on making their data AI-ready so it can be connected safely, in real-time to models.
Trend 3: Leadership, structure and skills must flex
The third trend is about people and the nature of work itself. Today’s job roles will be unrecognisable in the enterprise of the future. 57% of European leaders we spoke to expect most current employee skills to become obsolete by 2030. Teams comprising people and autonomous AI agents will become the norm, and the combination of personal agents for employee efficiency and enterprise agents that automate workflows will give rise to new roles. As pre-AI skills become obsolete, companies will need orchestrators who can manage AI across domains and traditional departmental boundaries instead of teams who use AI to augment individual job roles.
New roles such as functional AI agent leads and AI safety specialists will be needed to oversee and manage agent‑driven work.
But our data shows most companies aren’t ready for this new reality. Today, 67% of executives in Europe believe their current structures hinder AI’s full potential.
Crucially, this is a management and cultural transformation, not only a technology upgrade. Companies must redesign their workforces to account for growing AI capabilities and create cultures that help workers thrive during this transition.
At the same time, ensuring the decisions AI agents are making remain trusted, explainable and aligned with business objectives and policies will become table stakes.
Turning ambition to advantage
To transform into a smarter enterprise with sustained competitive edge, Europe’s leaders must act decisively:
- Make fewer, bolder bets: Replace incremental projects with clear, disciplined, long-term action.
- Treat productivity as growth capital: Resist the urge to bank efficiency gains as savings, instead investing them into the innovation that will drive tomorrow’s revenue growth.
- Build proprietary AI: Shift focus away from generic tools towards proprietary capabilities that harness your unique data and domain expertise.
- Redesign the org chart: Overhaul leadership models and governance to support decision-making defined by human-machine collaboration. Start with defining the future version of your own role and go from there.
There is a growing belief that AI will be the engine powering the competitive advantage European businesses need. By 2030, success will belong to the enterprises that have deeply embedded AI at their core, tailoring it to accelerate innovation and achieve specific outcomes. Today, leaders face a clear choice: attempt to lead this wave of reinvention or risk falling behind.
