Spotlight

Report:

The Forrester Wave™: AI Decisioning Platforms, Q2 2023

How does Forrester define the AI Decisioning Platforms market in 2023?

AI decisioning platforms (AIDPs) provide enterprise business and technology teams with tools to author and automate business decision logic in a wide variety of applications by leveraging combinations of decision intelligence technologies such as business rules, machine learning models, mathematical models, and more. The defining capability of AIDPs versus AI/ML platforms is that they include no-code tools enabling business experts to author decision logic that governs and/or enhances decision models. The market is driven by enterprises' need to harness AI to improve decision-making while managing well-articulated risks through a combination of AI power and trusted human business expertise.

Key Facts for The Forrester Wave™: AI Decisioning Platforms, Q2 2023 in 2023

How did the AI Decisioning Platforms market evolve in 2023?

What product features are required to be included in this year's evaluation?

What are the common features of top products in the AI Decisioning Platforms space?

No common features specified.

Scope Exclusions

Inclusion Criteria

Vendors must, among other requirements:

Offering Strengths — Relative Weighting

Strategy Strength — Relative Weighting

FAQs

Q: What does this research cover?

A: This research evaluates 13 AI decisioning platform providers across 23 criteria, analyzing their current offerings, strategies, and market presence. It covers platforms that enable enterprise business and technology teams to author and automate business decision logic using combinations of decision intelligence technologies including business rules, machine learning models, and mathematical models. The evaluation assesses each vendor's capabilities in data handling, authoring tools, decision intelligence technologies, deployment options, ModelOps, security, solution accelerators, and learning loops.

Q: Who should use this research?

A: Technology professionals evaluating AI decisioning platforms should use this research to understand vendor positioning and select the right platform for their needs. Buyers should use the Excel-based vendor comparison tool to adapt criteria weightings to their specific requirements. The research is particularly valuable for organizations seeking to implement automated decision-making in applications across various industries, especially those needing to balance AI capabilities with human business expertise, governance, and regulatory compliance. It helps identify vendors with strengths in specific areas like analytics integration, industry solutions, workflow automation, or regulatory compliance.

Q: What are the mandatory features of vendors included in this market?

A: To be included in this evaluation, vendors must offer: (1) A comprehensive AI decisioning platform with tools for building, deploying, orchestrating, and managing decision models that can be embedded in applications, (2) Solutions specifically marketed to enterprise customers for building custom decisioning models/solutions across broad use cases, (3) At least 10 paying enterprise customers using the evaluated platform version, (4) Proven revenue from platform adoption, and (5) Evidence of client interest through inquiries or market momentum.

Q: What are some reasons for not being included in this report?

A:

  • Fewer than 10 paying, named enterprise customers
  • No proven revenue from AI decisioning platform adoption
  • Not actively positioned or marketed as an AI decisioning platform
  • Lack of comprehensive platform capabilities across the decision lifecycle
  • Insufficient client inquiries or market momentum
  • Platform is primarily an AI/ML platform without business expert authoring tools
  • Declined to participate or only partially participated in the evaluation

Q: What should buyers consider when evaluating products in this market?

A:

  • Keep human business experts in control - Look for powerful and easy-to-use no-code tools that enable business experts to author, change, test, and deploy decision models that govern and/or enhance AI
  • Have industry-specific solution accelerators - Seek vendors with experience in your industry and/or horizontal use cases, offering training materials, sample code/flows, or ready-to-configure modules
  • Support rapid learning loops - Evaluate vendors' capability to monitor decision model effectiveness and learn/refine from the impact of decisions on KPIs, not just monitor production models

Q: How has the AI Decisioning Platforms market evolved in 2023?

A:

  • Enterprises must harness AI to improve decision-making while managing well-articulated risks
  • Best automated decisions come from combining AI power with well-proven human business expertise
  • Growing need for no-code tools that enable business experts to author and control decision logic
  • Demand for industry-specific solution accelerators to reduce implementation time
  • Importance of rapid learning loops to improve AI decisions based on real-world business outcomes
  • Integration of multiple decision intelligence technologies (business rules, ML models, analytics, mathematical models)
  • Focus on decision governance, monitoring, auditing, and explainability especially in regulated industries

Q: What differentiates Strength of Offering vs. Strength of Strategy?

A: Current Offering (vertical axis) evaluates the strength of vendors' existing platforms across data capabilities, authoring tools, deployment options, applications, and architecture. It measures what the platform can do today including explore, prepare, augment, features, tools, intelligence, testing, explainability, ModelOps, learning, accelerators, design, and security. Strategy (horizontal axis) evaluates vendors' future direction and market positioning including product vision, market approach, supporting products/services, planned enhancements, partner ecosystem, and commercial model. It measures where the vendor is headed rather than current capabilities.

Reference

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