Ask AI’s take: The lessons from 2025 are shaping AI adoption in 2026 by reinforcing the importance of robust governance, technical integration, data-centricity, and heightened cybersecurity. Organisations are leveraging these insights to future-proof their AI strategies, drive measurable business value, and mitigate emerging risks.

1. Governance and Risk Management: 2025 highlighted the necessity of comprehensive AI governance frameworks. Organisations learned to conduct risk assessments, implement mitigation strategies, and educate stakeholders on responsible AI practices. The banking sector, with examples like JPMorgan Chase and HSBC, demonstrated that innovation and regulatory compliance can coexist, ensuring trust and sustainable AI adoption.
2. Technical Integration and Early Planning: Executives in 2025 recognised that addressing technical considerations—such as scalability and regulatory compliance—early in the procurement process is crucial. This proactive approach prevents costly disruptions and lays a strong foundation for long-term AI success.
3. AI Centres of Excellence (CoE): The establishment of AI CoEs became a best practice, centralising expertise, governance, and risk management. These hubs facilitate cross-functional collaboration, rapid piloting, and disciplined oversight, ensuring that AI initiatives align with business objectives and deliver tangible outcomes.
4. Data-Centric AI and Quality Datasets: The imperative for data-centric AI was reinforced, with organisations prioritising high-quality, diverse datasets for reliable model training and performance. Leveraging untapped data sources became a key driver for new business initiatives and operational efficiencies.
5. Cybersecurity as a Strategic Priority: Persistent cybersecurity incidents in 2025, especially in sectors like telecommunications, underscored the need for enhanced security measures. This lesson is directly influencing 2026 strategies, with organisations prioritising the safeguarding of networks and data integrity as AI adoption accelerates.
6. Shift to Multi-Agent and Specialised AI Models: 2025 saw a transition from content generation to workflow execution, with multi-agent systems enabling complex task collaboration. The development of both large frontier and specialised models is supporting tailored, efficient AI applications across industries.