A market pivot from “AI tourism” to measurable value
After a year defined by rapid adoption and headline-grabbing demos, 2026 is shaping up to be the moment the AI boom grows up. Industry executives and investors across Europe say organisations are moving past “AI experimentation” and toward a tougher question: what does it take to deploy Generative AI at scale, safely, and with a clear return on investment?
The shift reflects a broader maturation of the market. As models and infrastructure become more widely available, competitive advantage is expected to move away from novelty and toward execution—how well companies integrate AI into real workflows, govern it, and prepare people to use it.
Operationalising AI becomes the core business challenge
Leaders argue that the most important work in 2026 will be less about new model announcements and more about implementation. Sebastiaan Vaessen, Global Head of Strategy at Prosus, expects a surge in demand for specialised talent focused on making AI function inside real organisations.
“In 2026, demand for consulting and engineering talent focused on AI implementation will rise exponentially,” Vaessen said, comparing the wave to the rise of ERP consulting in prior decades. The rationale is straightforward: many companies ran pilots quickly, but the complexity of embedding AI into data systems, security controls, and daily operations has proven far more bespoke than early hype implied.
That reality is also reshaping budgets. Instead of spending primarily on experimentation, enterprises are directing more funding toward integration work—data pipelines, evaluation frameworks, monitoring, and the organisational changes required to keep AI tools reliable over time.
Persistent memory moves onto enterprise requirement lists
A key technical limitation is also rising to the top of buyer checklists: whether AI systems can reliably use enterprise context. Patrik Backman, General Partner at OpenOcean, says businesses increasingly want AI that can access and reference previous discussions and relevant internal data—often described as persistent memory.
Without that capability, Backman argues, large language models risk remaining impressive but shallow tools. In practice, persistent memory is tied to difficult questions about data governance, privacy, permissions, and security—issues that become unavoidable once AI moves from a test environment into regulated, high-stakes workflows.
The “commodity trap” and the rise of vertical AI
As foundational models and infrastructure commoditise, executives anticipate pressure on broad, horizontal AI products. When many vendors can offer similar baseline capabilities, differentiation shifts to domain expertise and deep workflow integration.
In 2026, investors and buyers are expected to favour vertical AI—industry-specific applications and domain-tuned models designed for areas like healthcare, law, finance, and manufacturing. The appeal is pragmatic: higher accuracy in specialised contexts, better compliance alignment, and clearer ROI compared with general-purpose tools.
This dynamic could also change how startups position themselves. Rather than “AI for everything,” companies may need to prove they can deliver outcomes in a specific workflow—reducing cycle times, improving decision quality, or cutting operational costs—while meeting sector regulations.
Agents, robotics, and the next “ChatGPT moment”
Beyond enterprise software, 2026 is also forecast to be a breakout year for robotics. Sandeep Bakshi, Head of European Investments at Prosus Ventures, predicts a “ChatGPT moment” for robotics, driven by advances in self-adaptive, autonomous systems that can operate in real environments with less manual programming.
Bakshi argues the enabling conditions are aligning: hardware maturity, improving autonomy software, and expanding use cases. He expects robotics to move from impressive demos toward scalable deployments—particularly in logistics, delivery, and service sectors—where labour constraints and efficiency demands are strongest.
Alongside robotics, AI “agents” are expected to evolve from simple chat interfaces into tools that coordinate tasks, mediate discussions, and support group productivity. On the consumer side, leaders anticipate new platform architectures and “companion app” experiences, though the long-term winners will likely be those that demonstrate durable utility rather than novelty.
The human bottleneck: skills, culture, and trust
If 2025 was about what AI could do, 2026 may be about what organisations can absorb. Executives predict the biggest constraints will be human and cultural: training, change management, and the ability to redesign processes around AI without eroding accountability.
As AI-generated content becomes ubiquitous, some leaders also expect a countertrend: authentic, human experiences becoming more valuable. For employers, the implication is that upskilling programmes must be treated as seriously as infrastructure investments, and a new cohort of AI-focused change managers may become essential to adoption.
Regulation, sovereignty, and cyber resilience
Governance pressures are also intensifying. The push for AI sovereignty and homegrown innovation is expected to continue as dependence on a small number of global providers is increasingly viewed as a strategic risk. In parallel, boards are being urged to treat cyber resilience as a core governance priority, particularly as AI-enabled attacks evolve.
In financial services and other regulated sectors, executives see AI playing a growing role in compliance operations. Teresa Cameron, Group CEO at Clear Junction, highlighted AI’s usefulness in day-to-day monitoring, including scanning transactions, identifying emerging risk patterns, and helping teams interpret new rules more quickly. She emphasised that final decisions should remain with human analysts, while repetitive screening work can be automated to reduce false positives and speed reviews.
Meanwhile, Europe’s digital identity infrastructure is expected to accelerate. By the end of 2026, EU Member States are widely expected to have rolled out the European Digital Identity Wallet (EUDIW), a shift that could force companies in key sectors to adopt stronger authentication methods and rethink digital access controls.
The year of hard truths
Across these predictions, a consistent theme emerges: 2026 will reward execution. The likely winners will be organisations that can operationalise AI, build or buy vertical solutions with clear outcomes, invest in people and change management, and navigate a more regulated and geopolitically complex environment. For much of the market, the era of experimentation is ending—and the era of accountability is beginning.
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