Articles & Resources

AI agents are moving beyond answering questions. They can plan work, access systems, contact customers, approve routine steps, and trigger transactions.

Trust in artificial intelligence is not created through statements of intent or post-hoc assurances. In 2026, organisations are learning that trust must be deliberately designed into AI systems from the outset. For boards and senior leaders, this means moving beyond abstract principles and ensuring accountability is embedded in practice.

As artificial intelligence becomes embedded in critical business processes, organisations are discovering that compliance alone is not enough. Boards, regulators, customers, and stakeholders increasingly want assurance that AI systems are operating as intended, producing reliable outcomes, and remaining aligned with organisational values. This shift marks the emergence of AI assurance as a strategic capability.

AI introduces new forms of risk, but many boards are still relying on assurance approaches designed for traditional technology. In 2026, this gap is becoming increasingly visible. Effective AI governance requires a more nuanced and proactive approach to risk management.

As artificial intelligence becomes embedded across core business functions, many organisations still treat ethics as a technical or compliance concern. In 2026, this approach is increasingly misaligned with reality. Ethical AI is not a technical issue, it is a leadership responsibility.

Many organisations have experimented successfully with AI. Far fewer have managed to scale those initiatives without introducing complexity, risk, or loss of control. In 2026, the challenge is no longer proving that AI works, but embedding it sustainably across the organisation.