Pegasystems (NASDAQ:PEGA) CTO Don Schuerman said enterprise customers are shifting their artificial intelligence priorities from demonstrating AI adoption to pursuing measurable business value, with a focus on customer experience, efficiency, compliance and predictable operating costs.
Speaking at a Rosenblatt software event, Schuerman described Pega as a provider of workflow and decisioning technology used by organizations in financial services, government, insurance and healthcare. He cited uses including customer service, investigations, claims management, onboarding and know-your-customer processes.
Focus on Workflow Redesign and Governance
According to Schuerman, enterprises are becoming less focused on competition among large language models and more focused on connecting models to their existing data, processes and governance frameworks. He said the models available a year ago can be sufficient for many enterprise applications, while the larger challenge is integrating them into the decisions and workflows that operate a business.
Schuerman referenced a recent Forrester report on AI platforms, saying the research firm distinguished platform providers from foundation-model providers and characterized the market as a “federation, not a monolith.” He said customers are expected to use multiple technology platforms rather than relying on one AI orchestration provider.
Pega’s approach, he said, is centered on redesigning business processes before inserting AI capabilities. Schuerman said banks, for example, are rethinking complaint-handling and customer-onboarding processes, rather than simply applying AI to existing workflows.
He highlighted Pega Blueprint, a product that uses models from providers including Claude, Gemini and GPT to help users design workflows. The goal, he said, is to determine where AI agents should be used and where processes should instead rely on deterministic business rules.
“You cannot just drop the AI onto a broken process and expect it to fix it,” Schuerman said, describing what he expects to be a broad wave of process re-engineering.
- AI agents: Used for targeted tasks such as collecting complaint information, reviewing documents or producing fraud-risk scores.
- Deterministic workflows: Used for repeatable and auditable steps, particularly in regulated processes such as bank onboarding and complaint management.
- Governance: Maintained through visible process models and business rules that can be reviewed and adjusted.
Pricing Model and Agent Integration
Schuerman said Pega has announced that it will not charge customers on a per-token basis for AI use. Instead, the company plans to apply an uplift to its per-case pricing model, which is based on measures such as the number of customer complaints processed, new customers onboarded or claims handled.
He said Pega can support that structure because its architecture is designed to use agents for narrowly defined tasks, rather than repeatedly asking agents to reinterpret an entire process. That approach, he said, is intended to help customers avoid unpredictable token costs.
The CTO also said Pega has expanded support for Model Context Protocol, or MCP, allowing workflows in a Pega environment to be made available as skills that other agents can call. Conversely, Pega workflows can call agents built outside its platform. Schuerman said customers have begun deploying Pega workflows with external agents serving as an intake interface or embedded at specific points in a process.
He said the company’s usage-based model means that connecting workflows to additional channels or front ends could increase case volume, which he described as a potential source of value for both customers and Pega.
Infinity Studio, Legacy Modernization and Autonomous Operations
Schuerman said Pega’s Infinity ’26 release, which he said became generally available last month, includes Infinity Studio. The product brings Blueprint’s AI-assisted design capabilities into the workflow-building phase, enabling users to ask an AI assistant to modify workflows, interfaces, validation rules and other configurations.
The company expects these tools to reduce the time, personnel and specialized Pega expertise needed to deploy applications, Schuerman said. He added that the objective is to help clients achieve business results faster rather than simply reduce staffing requirements.
On legacy modernization, Schuerman said AI has increased urgency because older systems can make it difficult to integrate new AI capabilities with existing business logic and data. At the same time, he said agents can help analyze legacy code and documentation. He noted Pega’s work with AWS Transform, which can use MCP to send workflow-related work to Blueprint for redesign.
Schuerman said Pega does not view robotic process automation as a long-term replacement for process transformation. While AI can help deploy RPA bots more quickly, he characterized RPA as a temporary method for connecting to systems without APIs or generating quick operational improvements while companies pursue deeper redesign work.
Looking ahead, Schuerman said organizations are moving toward what Pega calls the autonomous enterprise by applying AI to measurable business outcomes rather than deploying isolated productivity agents. He expressed skepticism about near-term predictions around artificial general intelligence, saying customers are more concerned with using current AI tools to improve profitability, employee experiences and customer outcomes.
About Pegasystems (NASDAQ:PEGA)
Pegasystems Inc is a software company specializing in customer engagement and digital process automation solutions. Headquartered in Cambridge, Massachusetts, Pegasystems develops enterprise applications designed to help organizations streamline operations, manage customer interactions and automate complex workflows. Its platform supports a wide range of use cases, from sales and marketing optimization to case management and robotic process automation.
The core of Pegasystems’ offering is the Pega Platform, a low-code development environment that enables businesses to build and deploy applications with minimal hand-coding.
