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Revolutions don’t always turn out quite the way people wanted or expected. As the calendar turns to the 25th anniversary of The Agile Manifesto, I’ve been thinking about how change plays out and what its impact has really been.

Enterprises face a critical turning point in their AI infrastructure strategy as the operational costs of cloud-based large language models (LLMs) escalate. While cloud infrastructure provides unmatched capabilities for complex tasks, a shift toward local hardware and hybrid architectures is emerging as the solution for sustainable cost management and data sovereignty. By optimising local environments and leveraging governed platforms, organisations can balance performance with strict enterprise compliance.

Generative AI (GenAI) is shifting creative industries from pure production to strategic curation. This framework provides enterprise leaders with a pragmatic, human-centric approach to managing workforce transitions while using technology to augment, rather than replace, human talent.

Many organisations are guilty of approaching AI adoption as a technical or operational challenge, hinging on tooling, productivity, and governance. However, for their teams, AI can raise more human questions about value, creativity, and autonomy.

For over a decade, enterprise app marketplaces worked like digital convenience stores. If a team needed a specific feature—better reporting, a custom workflow, or a UI improvement—they could download a plugin and move on.

Generative AI awareness is high, but adoption at work remains stalled. Learn how you can beat pilot purgatory, build trust, and integrate AI into your team AI.