Artificial intelligence is no longer an emerging technology. Across every industry, organisations are experimenting with generative AI, automating processes, enhancing customer experiences and uncovering new business insights.

What began as a discussion about data residency has evolved into something much bigger. Today, organisations are being asked to prove they know where their data lives, who can access it, how it's protected, and whether it can be governed effectively as AI adoption accelerates.

AI adoption is accelerating at a remarkable pace. Across every department, employees are embracing AI tools, assistants and agents to work more efficiently, automate repetitive tasks and unlock new opportunities for innovation. What was once limited to experimentation is quickly becoming embedded in everyday business operations.

As AI continues to seep into the day-to-day operations of organisations worldwide, many businesses have been running pilots and testing use cases to demonstrate how AI can improve different areas of the organisation, but there's a roadblock that's becoming harder to ignore

At THINK this year, IBM made one thing very clear: the AI conversation has moved on. Pilots have been developed, use cases have been proven, and concepts completed. The focus now is on measurable AI integration for businesses.

IBM’s acquisition of Confluent for approximately $11 billion marks a significant development in data streaming and AI-driven enterprise innovation.

Sustainability has moved from a corporate ambition to a strategic necessity. But unlocking real impact depends on how effectively organisations can harness their ESG data to drive decisions, meet compliance obligations, and future-proof operations.

In a landscape where IT performance must meet tight budgets and rapid innovation, IBM Turbonomic stands out by combining artificial intelligence with intelligent automation to optimise resources and reduce IT spend while maintaining service quality.

AI is past the hype and becoming part of the norm, offering businesses new opportunities to innovate and stay ahead. However, organisations face a key challenge—whether to build AI solutions for greater control or buy ready-made solutions for faster results.