PegaWorld 2026: four key takeaways

Earlier this month, we travelled to Las Vegas for PegaWorld 2026. For three days, the MGM Grand was dedicated to AI, automation and digital transformation. With more than 200 demos, dozens of customer success stories and thousands of attendees, there was plenty to see. Yet it wasn’t the scale of the event that stood out most—it was the clarity of the message.

While many technology vendors continue to focus on larger language models, more AI agents and faster code generation, Pega took a notably pragmatic approach. The central theme throughout the event was clear: AI only delivers value when it produces predictable business outcomes. These are the four key insights we took away from Las Vegas.

 

1. Replacing token-based AI costs with predictable pricing

One of the biggest announcements at PegaWorld was the introduction of a new pricing model for AI capabilities within Pega Infinity 26. Many organisations experimenting with Agentic AI face a practical challenge: cost predictability. As AI agents perform more tasks, token consumption increases, making costs difficult to forecast and often leading to unexpected expenses.

Pega is taking a different approach. Under the concept of Predictable AI, as much reasoning as possible is shifted to the design phase. During runtime, AI agents follow predefined and approved workflows instead of continuously generating new reasoning paths. This delivers three clear benefits: lower costs, improved performance and greater predictability. The commercial model is changing as well. Instead of charging per token, Pega is moving towards outcome-based pricing: a fixed price per completed case or business process. For organisations looking to scale AI adoption, this makes budgeting far more straightforward.

 

2. Governance matters more than flashy demos

Many technology vendors still try to impress customers with spectacular AI demonstrations. In reality, organisations are increasingly asking a different question: how do we stay in control? That topic received significant attention throughout PegaWorld. For many enterprises, AI is no longer an experiment—it has become business-critical technology. As a result, the focus is shifting from impressive demos to governance, compliance, auditability and human oversight.

Pega therefore positions AI agents firmly within existing business processes. Rather than operating outside established rules, agents work within predefined workflows where responsibilities, controls and decision-making are clearly defined. An interesting development is that these same governance mechanisms remain active even when external AI agents access Pega workflows through open standards. This enables large organisations to deploy AI at scale while maintaining control.

 

3. Keeping the business in the driver’s seat

It’s a familiar challenge: the business knows what it wants to achieve, IT knows how to build the solution, but somewhere along the way valuable context gets lost. As a result, the final solution often differs from the original business intent.

Pega’s Blueprint Delivered methodology is designed to bridge that gap between business ideas, implementation and measurable business value. The journey starts in Blueprint, where business processes and logic are designed. From there, development continues in Infinity Studio, where those designs are transformed into working applications.

One of the most notable innovations presented at PegaWorld concerns this second phase. The AI capabilities previously introduced in Blueprint are now fully integrated into Infinity Studio. AI agents assist Pega developers by accelerating application development, coding and refinement. The goal is not to replace developers, but to help them work more efficiently and shorten the journey from concept to production-ready software.

This aligns seamlessly with the Blueprint Delivered philosophy: moving from Blueprinting to Authoring and ultimately to Value Activation. Not by asking business users to build applications themselves, but by reducing the handover between business and IT, allowing development teams to deliver faster. As a result, the original business intent is preserved more effectively and measurable business value is achieved sooner.

 

4. The biggest opportunity lies within existing systems

Many organisations still rely on applications that were built years—or even decades—ago. Replacing or modernising these systems is often expensive, complex and time-consuming.

Pega demonstrated how AI and Blueprint technology can accelerate the analysis, understanding and redesign of existing applications. Rather than simply moving legacy systems to the cloud, the focus is on rethinking business processes and redesigning them in a smarter way. This makes application modernisation not only faster, but also significantly more manageable.

 

Conclusion

The conversation around AI is shifting from what AI can do to how organisations can deploy AI responsibly and predictably. Cost control, governance, application modernisation and closer collaboration between business and IT have become the key themes. How well organisations address these challenges will ultimately determine whether AI delivers real business value.