Behind the delegate pass: IBM THINK 2026

ibm think 2026

United Kingdom, May 13, 2026

Scaling AI responsibly in a complex landscape

Authored by Jo Walsh, IBM Solutions Director, Logicalis UK&I

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 how organisations integrate AI into development at scale and whether that impact is measurable.

Three key themes emerged from the THINK keynotes.

Day 1: The winners are rebuilding their operating model around AI

There's a small group of organisations that are pushing ahead of the pack with increases in productivity and margin. The difference between these organisations and their competitors is how they're weaving AI into the fabric of their operations. This AI-operating model is built on:

  • Real-time, connected intelligence
  • Automated, coordinated action
  • Scalable operations
  • Embedded trust and governance

The gap between organisations that bake AI into their core processes and those that don't is widening. The pressure is on IT leaders to close that gap before they fall too far behind.

Day 2: Real value comes from scale, not another pilot

Across several industries, Agentic AI is defining itself as a differentiator. The ability to offload complex, time-consuming processes or tasks to AI agents directly impacts how quickly IT leaders can react and make decisions.

IBM shared some examples:

  • Healthcare organisations are cutting hiring timelines by 12 days and significantly improving efficiency
  • Insurance firms are reducing claims processing times from weeks to days
  • Retail and consumer brands are using AI to accelerate innovation and customer personalisation dramatically

Day 3: Governance is a necessity if scale is the goal

Scaling AI is complex, and with effective governance, that complexity can become a risk. This creates new challenges organisations face regarding data access, security, visibility, control, and compliance.

To address these issues effectively, organisations need to build around three core principles:

  • Visibility
    To gain an understanding of where AI is being used and who is using it
  • Control
    Erecting guardrails to maintain the integrity of AI, governing how it's used
  • Accountability
    Demonstrating outcome and proving compliance.

Final thoughts

AI, on its own, will not produce the results that business leaders want to see. If organisations want to achieve the next phase of enterprise transformation, they need to focus on executing quickly and with intention.

 

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