The Forrester Wave™: AI Decisioning Platforms, Q2 2023

AI Decisioning Platforms Vendor Product Comparisons 2023

Key features and pros and cons of top AI Decisioning Platforms products:

CRIF - Leaders

Pros:

Tools for business experts
Decision intelligence technologies
Application development tools
Security

Cons:

Can improve by adding more industry-diverse solution accelerators
Needs automated feature engineering for machine learning

FICO - Leaders

Pros:

Platform design
Solutions accelerators
Decision intelligence technologies
Authoring tools
Learning feedback loops
Security

Cons:

Can improve by adding more robust data pipeline tools
Needs annotation for machine learning

IBM - Leaders

Pros:

Decision intelligence technologies
Authoring tools
Explainability
ModelOps
CPLEX for optimization
Ability to run in any cloud including mainframe transactions
Decision governance in IBM OpenScale

Cons:

Could improve platform by unifying tools
Integration between ADS and Watson Studio could be better
Arbitrary division between Cloud Pak for Business Automation and Cloud Pak for Data

InRule Technology - Leaders

Pros:

Decision authoring tools
Deployment options
Security
Platform design
Ease of use for business experts

Cons:

Can improve by adding broader set of machine learning methods
Needs constraint programming optimization methods
Should nurture more partnerships with software companies and global consulting firms

SAS - Leaders

Pros:

Comprehensive data capabilities
Decision intelligence technologies
User experience
Breadth of authoring tools
ModelOps
Seamless integration of analytics and AI

Cons:

Can improve by offering more capabilities for application development teams

ACTICO - Strong Performers

Pros:

Decision logic authoring tools
Explainability
Application development tools
Solution accelerators
Security

Cons:

Could dramatically improve by adding more comprehensive data capabilities
Needs data exploration, pipelines, and feature engineering for machine learning
Should expand more aggressively into North America

Pegasystems - Strong Performers

Pros:

Workflow development tools
ModelOps
Decision intelligence technologies
Testing
Platform design
Security
Agility to fine-tune workflows and decisions

Cons:

Can improve by expanding data tooling for bespoke machine learning models
Needs to add more machine learning tools and prebuilt models

TIBCO Software - Strong Performers

Pros:

Data visualization and analysis
Explainability
Learning loops
Platform architecture
TIBCO Spotfire for business intelligence

Cons:

Can improve by enhancing decision logic authoring tools
Needs integrated decision testing tools
Should better meld decision authoring tools with TIBCO Data Science

Decisions - Contenders

Pros:

Coherent set of no-code tools to build complete applications
Workflow capabilities
Decision capabilities
User interface design tools
Training and support

Cons:

Lagging in capabilities for in-product machine learning
Needs more sophisticated data tools
Must increase AI capabilities to keep pace with enterprise needs

FlexRule - Contenders

Pros:

Decision logic and workflow authoring
Deployment
Application development
Automated machine learning

Cons:

Could improve explainability and ModelOps
Must invest significantly in sales, marketing, and product development
Needs to keep pace as market grows

Sapiens - Contenders

Pros:

Decision modeling
ModelOps
Security
Easy-to-use tooling for complex business decisions
Ability to monitor and audit decisions in production

Cons:

Lacks built-in machine learning capabilities
Needs no-code AutoML approach
Must extend decision model vision to include more in-platform ML tools

Sparkling Logic - Contenders

Pros:

Authoring tools
Feedback loops
Testing
Data augmentation
Accelerators
Ease of use

Cons:

Must boost data and machine learning capabilities
Unclear vision and enhancement roadmap
Appears stalled in development
Needs modernization

Progress - Challengers

Pros:

Application development tools
Deployment options
Integration with other Progress products in Digital Experience portfolio

Cons:

Must reassess from ground up and invest in platform
Needs to add new authoring tools
Requires machine learning capabilities
Needs data pipelines
Only offers basic decisioning

FAQs

Q: Which vendors are Leaders in 2023?

A: CRIF, FICO, IBM, InRule Technology, SAS

Q: What does "Leader" mean in Forrester Wave terms?

A: Leaders are vendors that offer a comprehensive AI decisioning platform with strong current offerings and robust strategies. Leaders demonstrate excellence in providing tools for business experts to author and manage decision logic, strong decision intelligence technologies, comprehensive capabilities across the decision lifecycle, and a clear product vision. They excel at enabling enterprises to combine AI with human business expertise for automated decision-making.

Q: How do I interpret a Forrester Wave?

A: https://www.forrester.com/policies/forrester-wave-methodology/

Report:

Top Vendor Products for AI Decisioning Platforms in 2023

AI Decisioning Platforms Vendor Product Comparisons 2023

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FAQs

Q: Which vendors are Leaders in 2023?

Q: What does "Leader" mean in Forrester Wave terms?

Q: How do I interpret a Forrester Wave?

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