Pega Infinity 26 release shifts customer service to outcome-based pricing

The shift to outcome-based pricing addresses a critical barrier in enterprise AI adoption by decoupling costs from unpredictable token consumption. By positioning Pega Customer Service as a governed layer beneath platforms like Amazon Connect, the company is prioritizing complex back-office orchestration over the crowded CCaaS interface market. This strategy forces a clear division between conversation handling and case resolution, requiring competitors like Salesforce and ServiceNow to prove their depth in regulated, multi-step workflows. Watch for how procurement teams define a 'resolved case' in upcoming contracts to determine if this pricing model truly lowers the total cost of ownership for agentic service.

Pegasystems is entering a crowded field of enterprise vendors racing to embed agentic AI into customer service workflows. In June 2026, Nokia announced work with AWS and Databricks to build the data, cloud, and control layers for autonomous networks, demonstrating how major platform vendors are stacking AI orchestration layers on top of existing infrastructure. While Nokia's focus is telecom operations, the architectural pattern mirrors what Pega is attempting in customer service: a governed orchestration fabric that sits between raw AI models and business outcomes. The broader trend of vendors moving from isolated AI pilots to production-grade agentic operations accelerated sharply in mid-2026, with Ericsson launching its AI in RAN commercial software subscription on June 11th and Verizon disclosing agentic AI applied across its 60,000-site vRAN for configuration changes and service assurance. These deployments validate the same outcome-based logic Pega is applying to contact centers: operators want measurable results, not token bills. The competitive landscape for agentic customer service is intensifying as platform giants push their own agent frameworks. Amazon Connect, which Pega positions as a complementary conversation layer rather than a competitor, has been expanding its native AI capabilities throughout 2026. Meanwhile, Ericsson and Nokia are diverging sharply on AI-RAN architecture, with Nokia betting on Nvidia's CUDA platform and Ericsson pursuing a GPU-free approach built on custom silicon. That strategic bifurcation in telecom mirrors the choice facing enterprise buyers in customer service: adopt a single vendor's full stack or assemble best-of-breed components with a governance layer like Pega's. The Model Context Protocol support in Infinity 26 positions Pega as the interoperability layer, similar to how Ericsson is framing silicon independence as protection against single-vendor lock-in. On the technical side, Nokia's experience deploying agentic AI into production environments offers a useful benchmark for what Pega buyers should expect. Nokia reported that AI agents in its mobile core reduced call setup times from roughly 10 seconds to one or two seconds by using machine learning to page user equipment more efficiently, while the company maintained human supervision until a zero-trust environment could be established. That cautious deployment model, with guardrails and staged rollouts, aligns with Pega's emphasis on governed workflows over autonomous agent free rein. Nokia also claimed automation rates above 90 percent and service delivery times under four hours across its autonomous networks portfolio, metrics that enterprise contact center buyers will likely demand Pega match or exceed before committing to outcome-based contracts at scale.