Decisions + ProcessMaker

Critical Capabilities for Decision Intelligence Platforms | Gartner® Report

Organizations are under increasing pressure to improve decision quality while safely incorporating AI into their operations. This report examines the capabilities organizations should evaluate when selecting platforms that support decision analysis, low-code engineering, decision science, and decision governance.
By 2027, 25% of ungoverned decisions using large language models (LLMs) will cause financial or reputational loss due to human biases, insufficient critical thinking, and AI sycophancy.

By 2027, 50% of business decisions will have been augmented or automated by AI agents for decision intelligence.

By 2030, explicitly modeled business decisions will be five times more trusted and 80% faster than ungoverned decisions, enabled by decision intelligence platform adoption.

In our understanding, what’s inside:

  • Understand the capabilities Gartner uses to evaluate decision intelligence platforms.
  • Explore how vendors approach decision modeling, automation, and governance.
  • Learn what capabilities are required to execute and monitor decisions at scale.
  • Discover which vendors ranked highest across key decision intelligence Use Cases.
  • See how decision intelligence platforms help organizations improve decision quality.

By submitting this form, you agree to our Privacy Policy to receive communications from Decisions. We use tracking tools to process your request, improve your experience, and share relevant updates.

FAQs

A decision intelligence platform is software that helps organizations design, automate, execute, and govern decisions using data, analytics, business rules, and AI. These platforms allow teams to model decisions, orchestrate decision flows, monitor outcomes, and continuously improve decision quality across the enterprise.

As organizations increasingly rely on AI for decision automation, governance becomes critical to ensure decisions remain transparent, auditable, and compliant. Decision governance provides oversight into how decisions are made, which rules and models are used, and how outcomes are monitored and improved over time.

Decision modeling allows organizations to explicitly define how decisions should be made using structured logic, rules, data inputs, and AI models. By modeling decisions instead of relying on ad hoc processes, organizations can make decisions more consistently, adapt them faster, and scale decision automation across systems and teams.

Decision monitoring provides visibility into how decisions are executed and their outcomes. By tracking decision performance, logic changes, and metadata, organizations can identify issues, refine decision models, and ensure automated decisions continue to deliver the intended business results.

Decision orchestration connects rules, workflows, data, and AI models into coordinated decision flows across systems. This allows organizations to automate complex processes, apply consistent logic across applications, and ensure AI-driven decisions operate within governed and auditable frameworks.