AI trends for 2026

Large consulting firms are undergoing a structural reset as AI replaces much of the work traditionally done by junior analysts. Data collection, benchmarking, modeling, and slide production, once the foundation of the consulting pyramid, are increasingly automated by AI. As a result, teams are flattening: fewer juniors, greater reliance on senior consultants. Value shifts away from execution capacity toward experience, judgment, the ability to frame the right questions and guide complex decisions, and the alignment of teams. In 2026, consulting becomes more about leadership and experience.

Annual strategy cycles give way to always-on strategic intelligence. AI systems continuously monitor markets, competitors, customer behaviour, and internal performance, surfacing strategic signals earlier than traditional analysis ever could. Strategy teams increasingly work with AI dashboards and simulations rather than static slide decks. The strategic advantage comes from speed, adaptability, and scenario testing, not from perfect long-term predictions. AI is there as a solid base that the senior teams leverage with their expertise.

AI-driven marketing in 2026 is defined by autonomy rather than automation. AI systems increasingly manage campaign testing, budget allocation, creative optimization, and channel performance in real time. This allows human marketeers to focus on positioning, brand coherence, and strategic direction, while AI handles execution at scale. This shift dramatically improves speed and efficiency, but also requires clearer objectives, stronger brand guardrails, and better data literacy. If done correctly, the marketeers can focus on where the brand should go next and how the brand is best represented.

While large foundation models remain important, 2026 sees growing adoption of smaller, task-specific AI models. These models are cheaper to run, easier to control, and better suited to regulated environments. By combining large models for general reasoning with specialized models for specific workflows, companies achieve better performance, lower costs, and improved explainability. This modular approach to AI architecture becomes the norm rather than the exception, allowing businesses to explore what actually really works for them.

Europe’s AI ecosystem enters a more mature phase in 2026, with a focus on enterprise-grade, regulation-ready AI solutions. In the Netherlands and across the EU, emerging AI companies, like Axelera AI and OtterlyAI, specialize in areas such as AI infrastructure, creative intelligence, compliance tooling, and industry-specific applications. Rather than competing directly with global hyperscalers, these firms differentiate through trust, data sovereignty, deep domain expertise, and local support. For European organizations, this creates new opportunities to build AI capabilities that are both powerful and aligned with regional values and regulation.