Pega Recognized as a Leader in Gartner Magic Quadrant for Process Intelligence as AI-Driven Enterprise Automation Accelerates
Pegasystems Inc. a provider of enterprise workflow automation and AI-driven decisioning software, announced that it has been named a Leader in the 2026 Gartner Magic Quadrant for Process Intelligence. The recognition highlights Pega’s growing influence in the rapidly evolving market for process intelligence, enterprise orchestration, and AI-powered workflow automation.
The Gartner report evaluated 13 vendors based on two primary criteria:
- Completeness of Vision
- Ability to Execute
Pega was recognized across multiple evaluation categories including:
- Product strategy
- Innovation
- Customer experience
- Product capabilities
- Operational execution
The recognition reflects the increasing importance of process intelligence platforms as enterprises accelerate adoption of artificial intelligence, workflow automation, and agentic operational systems.
The report also marks an important evolution in the broader enterprise software market. Gartner previously referred to this category as “Process Mining Platforms,” but has now expanded the terminology to “Process Intelligence,” signaling the growing convergence of:
- Process mining
- Task mining
- Workflow orchestration
- Operational analytics
- AI automation
- Intelligent decisioning
Pega believes this broader category better represents the emerging role of AI-enhanced operational intelligence platforms within large enterprises.
Enterprises Increasingly Need Operational Context for AI
One of the key themes behind the Gartner recognition is the growing realization that enterprise AI systems require operational context to function effectively.
As organizations deploy:
- AI agents
- Autonomous workflows
- Intelligent automation
- Real-time decision systems
they increasingly need visibility into:
- How work actually gets done
- Where operational bottlenecks exist
- How employees interact with systems
- Which processes should be optimized
- Where automation delivers the greatest value
According to Gartner, process intelligence platforms help organizations:
- Visualize operational workflows
- Analyze business processes
- Monitor execution
- Identify inefficiencies
- Prioritize automation opportunities
This operational intelligence becomes especially important as enterprises attempt to scale AI deployments across complex organizational environments.
Without accurate process visibility, AI systems may automate inefficient or poorly understood workflows, reducing the effectiveness of enterprise transformation initiatives.
Pega Infinity Positioned as the Core Enterprise Transformation Platform
The Gartner evaluation focused on Pega Infinity, the company’s broader enterprise transformation platform built on the Pega Platform foundation.
Pega Infinity combines multiple operational technologies into a unified enterprise system, including:
- Workflow orchestration
- AI-driven decisioning
- Business automation
- Process intelligence
- Customer engagement
- Case management
- Operational analytics
The platform is designed to help enterprises coordinate complex workflows across departments, applications, and operational systems.
Pega’s architecture focuses heavily on orchestrating enterprise work dynamically using AI and rules-based automation.
This becomes increasingly important as organizations attempt to manage:
- Multi-system workflows
- Hybrid work environments
- Real-time operational changes
- Cross-functional automation
- AI-assisted decisioning
Process Mining and Task Mining Expand Operational Visibility
A major part of Pega’s process intelligence strategy centers on:
These technologies provide organizations with visibility into how business processes actually operate in practice.
Process Mining
Process mining focuses on analyzing system-level workflow activity across enterprise applications.
The technology helps organizations:
- Map process flows
- Detect bottlenecks
- Identify inefficiencies
- Monitor operational performance
- Analyze execution patterns
Process mining systems typically ingest event logs and operational data from enterprise applications to reconstruct end-to-end workflows.
Task Mining
Task mining focuses more closely on how individual work activities are performed at the user level.
This includes analyzing:
- Employee workflows
- Repetitive tasks
- User-system interactions
- Manual operational activities
Task mining helps enterprises understand:
- Which activities are candidates for automation
- Where operational friction exists
- How work varies across teams
Together, these technologies provide enterprises with a more comprehensive operational picture spanning both:
- System-level workflows
- Human-level task execution
AI and Process Intelligence Are Becoming Deeply Integrated
One of the most significant aspects of Pega’s strategy is the integration between process intelligence and generative AI systems.
The company highlighted the role of Pega Blueprint, its AI design agent that transforms operational insights into agent-driven workflows.
Pega Blueprint uses mined operational data to:
- Simulate workflows
- Design optimized processes
- Generate applications
- Create workflow automations
- Accelerate transformation initiatives
The platform effectively attempts to shorten the distance between:
- Operational discovery
- Process analysis
- Workflow design
- Application generation
- Deployment execution
This is increasingly important as enterprises seek faster ways to operationalize AI-driven transformation initiatives.
Rather than relying solely on traditional manual development cycles, organizations are increasingly adopting AI-assisted operational design systems.
Agentic AI Workflows Becoming a Major Enterprise Trend
Pega’s announcement repeatedly emphasized the rise of “agentic” workflows.
Agentic AI refers to systems capable of:
- Acting autonomously
- Making operational decisions
- Coordinating workflows
- Executing multi-step tasks
- Adapting dynamically to changing conditions
Unlike traditional static automation systems, agentic AI environments require:
- Real-time operational visibility
- Contextual awareness
- Governance oversight
- Decision transparency
- Workflow adaptability
Process intelligence platforms play an important role in enabling these capabilities because they provide the operational context needed for AI agents to function reliably.
Pega believes enterprises need strong process visibility before deploying large-scale autonomous systems.
Without clear operational understanding, autonomous agents may:
- Misinterpret workflows
- Escalate inefficiencies
- Introduce operational risk
- Create governance challenges
Enterprise AI Requires Governance and Transparency
Another major theme in Pega’s positioning is governance.
As enterprises expand AI deployment, organizations face growing pressure to ensure:
- Explainability
- Operational transparency
- Workflow oversight
- Regulatory compliance
- Decision accountability
AI systems operating inside enterprise environments often interact with:
- Customer data
- Financial systems
- Compliance processes
- Operational infrastructure
This creates significant governance requirements.
According to Kerim Akgonul, process intelligence helps organizations create:
- Reliable AI workflows
- Transparent operational systems
- Real-world context for decisioning
- Better enterprise outcomes
Pega positions its technology as enabling “smarter, more reliable agentic workflows” supported by operational visibility and governance controls.
Gartner Recognition Adds to Broader Analyst Momentum
The latest Gartner recognition adds to several other recent analyst acknowledgments received by Pega across multiple enterprise software categories.
The company was also recognized in:
- Gartner Magic Quadrant for Business Orchestration and Automation Technology 2025
- Forrester Wave for Real-Time Interaction Management
- Forrester Wave for Digital Process Automation
- Forrester Wave for AI Decisioning Platforms
These recognitions reflect Pega’s broad positioning across multiple enterprise transformation categories including:
- Workflow automation
- Decision intelligence
- AI orchestration
- Customer engagement
- Operational transformation
The overlap among these categories highlights how enterprise software markets are increasingly converging around AI-enabled operational ecosystems.
Process Intelligence Market Continues Expanding
The broader process intelligence market has grown rapidly in recent years as organizations pursue digital transformation initiatives.
Enterprises are increasingly investing in technologies that help:
- Improve operational efficiency
- Reduce process friction
- Identify automation opportunities
- Optimize workflows
- Enable AI deployment
The market includes a wide range of vendors focused on:
- Process mining
- Workflow analytics
- Automation intelligence
- Task discovery
- AI orchestration
However, the category is evolving quickly beyond traditional process mining into broader operational intelligence ecosystems.
The shift in Gartner’s terminology from “Process Mining Platforms” to “Process Intelligence” reflects this expansion.
Why Process Intelligence Matters in the AI Era
Historically, many organizations automated workflows without fully understanding how processes actually operated.
This often resulted in:
- Fragmented automation
- Incomplete workflows
- Operational inefficiencies
- Low ROI from transformation projects
Process intelligence technologies help solve this challenge by creating detailed operational visibility before automation occurs.
In the AI era, this visibility becomes even more important because:
- AI systems are more dynamic
- Autonomous workflows are more complex
- Decisioning environments change rapidly
- Operational dependencies become harder to monitor
Process intelligence platforms provide the foundational operational data layer needed to support enterprise-scale AI systems.
AI-Driven Enterprise Transformation Accelerating
Pega’s recognition also reflects the larger acceleration of AI-driven enterprise transformation initiatives globally.
Organizations across industries are investing heavily in:
- Workflow automation
- Generative AI
- Intelligent assistants
- Operational orchestration
- Decision automation
- AI-powered customer engagement
However, many enterprises still struggle with:
- Legacy systems
- Fragmented workflows
- Siloed data
- Complex governance requirements
Vendors capable of integrating:
- AI
- Workflow intelligence
- Process visibility
- Automation orchestration
are becoming increasingly important within enterprise software markets.
Pega has positioned itself at the center of this convergence.
The Convergence of AI, BPM, and Operational Intelligence
Pega historically built its reputation around:
- Business process management (BPM)
- Workflow orchestration
- Customer engagement systems
The modern enterprise software landscape is now converging many of these disciplines together with AI.
Today’s enterprise transformation platforms increasingly combine:
- BPM
- Process mining
- AI decisioning
- Automation
- Operational analytics
- Workflow orchestration
This convergence is reshaping how organizations manage operational transformation.
Rather than deploying disconnected systems, enterprises increasingly seek unified platforms capable of:
- Discovering workflows
- Analyzing operations
- Designing automations
- Executing decisions
- Monitoring outcomes
Pega’s integrated platform strategy aligns closely with this trend.
Blueprint Represents a Shift Toward AI-Generated Enterprise Workflows
One of the most forward-looking aspects of Pega’s platform is Blueprint’s role as an AI design agent.
The concept of AI-generated workflows represents a major shift in enterprise software development.
Instead of manually designing applications and workflows from scratch, organizations may increasingly:
- Analyze operational data
- Generate workflow recommendations
- Simulate process changes
- Auto-generate applications
- Deploy AI-assisted operational systems
This could significantly accelerate enterprise modernization timelines.
It also potentially lowers the technical barrier for operational transformation initiatives.
Pega’s recognition as a Leader in the Gartner Magic Quadrant for Process Intelligence highlights the growing importance of operational visibility in the AI era.
As enterprises increasingly deploy:
- AI agents
- Autonomous workflows
- Intelligent automation
- Real-time decision systems
the need for deep process intelligence is becoming foundational rather than optional.
Pega’s integrated approach combining:
- Process mining
- Task mining
- Workflow orchestration
- AI design agents
- Enterprise automation
positions the company within one of the fastest-evolving segments of enterprise technology.
The broader shift toward process intelligence reflects a key reality of modern AI adoption: organizations cannot automate effectively without first understanding how their operations truly function.
As AI-driven enterprise transformation accelerates globally, platforms capable of providing operational context, governance, and intelligent orchestration are likely to play an increasingly central role in how businesses modernize their workflows and deploy autonomous systems at scale.
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