Report:
The Forrester Wave™: AI/ML Platforms, Q3 2024
How does Forrester define the AI/ML Platforms market in 2024?
In our 19-criterion evaluation of AI/ML platform providers, we identified the most significant ones and researched, analyzed, and scored them. This report shows how each provider measures up and helps technology leaders select the right one for their needs. AI/ML platforms enable AI teams—comprising business and technology leaders, subject matter experts, application developers, solution architects, business analysts, UX designers, and other roles—to design and implement business processes using tooling that maximizes productivity while enabling friction-free collaboration. The evaluation focuses on platforms that support both predictive AI and generative AI capabilities.
Key Facts for The Forrester Wave™: AI/ML Platforms, Q3 2024 in 2024
- Publication Date: 28-Aug-2024
- Document ID:
- Summary: In our 19-criterion evaluation of AI/ML platform providers, we identified the most significant ones and researched, analyzed, and scored them. This report shows how each provider measures up and helps technology leaders select the right one for their needs.
- Authors: Mike Gualtieri, Sudha Maheshwari, Sarah Morana, Jen Barton
How did the AI/ML Platforms market evolve in 2024?
- AI teams now include business and technology leaders, SMEs, application developers, solution architects, business analysts, UX designers, and other roles beyond just data scientists and AI experts
- Organizations need AI/ML platform tooling that maximizes productivity of each role while enabling friction-free collaboration
- Rapid advancements in fundamental AI models and approaches, particularly generative AI, are evolving faster than any other modern technology
- AI/ML platform vendors have invested heavily in capabilities for generative AI including prompt engineering, governance, and application development
- Agentic AI will herald a step change to deliver capabilities that change how enterprises operate, serve customers, and adapt to the market
- Enterprises need platforms from vendors that keep pace with, and ideally push the envelope of, enterprise AI technology
- The technology must serve a reimagined enterprise operating in a world of abundant intelligence
- End-to-end collaboration and governance are critical, with increased scrutiny of data lineage and model accuracy tracking
- Unified data mesh platforms supported at the platform level enable better transparency into data lineage and model monitoring
- First-class user experience for both predictive and generative AI applications is essential for advanced users
What product features are required to be included in this year's evaluation?
- Offers a comprehensive, differentiated AI/ML platform solution that provides capabilities allowing enterprise AI teams to collaborate on designing, developing, and deploying bespoke AI solutions, including ML models and/or AI applications
- Actively markets an AI/ML platform for enterprise customers specifically shopping for an AI/ML platform to build custom AI solutions for the broadest number of use cases
- Has at least 10 paying, named enterprise customers using the version of the AI/ML platform that was evaluated
- Has sparked client inquiries and/or has market momentum through Forrester client interest demonstrated through inquiries, guidance sessions, customer shortlists, and consulting projects, or the vendor's market presence indicates its relevance to Forrester clients
What are the common features of top products in the AI/ML Platforms space?
No common features specified.
Scope Exclusions
- Platforms focused primarily on single-role users (data scientists only) rather than multirole AI teams
- Solutions without comprehensive capabilities across both predictive and generative AI
- Vendors without adequate enterprise customer base (fewer than 10 paying enterprise customers)
- Platforms lacking end-to-end collaboration and governance features
- Solutions without demonstrated market presence or client inquiry momentum
Inclusion Criteria
Vendors must, among other requirements:
- Offers a comprehensive, differentiated AI/ML platform solution that allows enterprise AI teams to collaborate on designing, developing, and deploying bespoke AI solutions, including ML models and/or AI applications
- Actively markets an AI/ML platform for enterprise customers targeting the broadest number of use cases
- Has at least 10 paying, named enterprise customers using the evaluated version of the AI/ML platform
- Has sparked client inquiries and/or has market momentum through demonstrated client interest via inquiries, guidance sessions, customer shortlists, and consulting projects
Offering Strengths — Relative Weighting
- Data: explore — 9%
- Data: prepare and enrich — 9%
- Training: tools — 9%
- Training: evaluation — 9%
- Governance: data — 9%
- Governance: models — 9%
- Development: predictive — 9%
- Development: generative — 9%
- Architecture: workload performance — 9%
- Architecture: security — 9%
- Architecture: ecosystem — 9%
Strategy Strength — Relative Weighting
- Vision — 18%
- Innovation — 18%
- Roadmap — 18%
- Partner ecosystem — 18%
- Adoption — 18%
- Pricing flexibility and transparency — 10%
FAQs
Q: What does this research cover?
A: This research provides a comprehensive 19-criterion evaluation of the most significant AI/ML platform providers in the market. It assesses vendors across current offering capabilities, strategy (including vision and innovation), and market presence. The evaluation focuses on platforms that enable enterprise AI teams to collaborate on designing, developing, and deploying bespoke AI solutions, including ML models and AI applications for both predictive and generative AI use cases.
Q: Who should use this research?
A: This research should be used by technology leaders and decision-makers who are evaluating and selecting AI/ML platforms for their organizations. It is particularly valuable for enterprises looking to: 1) Implement platforms that support multi-role AI teams from data scientists to business users, 2) Build both predictive and generative AI applications, 3) Establish end-to-end governance and collaboration frameworks, 4) Keep pace with rapid AI innovation and prepare for agentic AI capabilities, and 5) Transform their organizations into AI-driven enterprises.
Q: What are the mandatory features of vendors included in this market?
A: AI/ML platforms must offer comprehensive, differentiated solutions that enable enterprise AI teams to collaborate on designing, developing, and deploying bespoke AI solutions including ML models and AI applications. The platform must be actively marketed to enterprise customers for building custom AI solutions across the broadest range of use cases. Vendors must have at least 10 paying, named enterprise customers using the evaluated platform version and demonstrate market momentum through client inquiries, guidance sessions, shortlists, or consulting projects.
Q: What are some reasons for not being included in this report?
A:
- Insufficient enterprise customer base (fewer than 10 paying, named customers)
- Platform not actively marketed as an AI/ML platform for enterprise use
- Solution lacks comprehensive differentiation or focuses on narrow use cases
- Absence of demonstrated market presence or Forrester client interest
- Platform does not support multirole AI team collaboration
- Vendor declined to participate or only partially participated in the evaluation process
Q: What should buyers consider when evaluating products in this market?
A:
- A vision and roadmap that will deliver industry-leading enterprise AI and support transformation to AI enterprises, including agentic AI capabilities
- End-to-end collaboration and governance with unified data models enabling business participation in governing data and models throughout the lifecycle
- First-class user experience for both predictive and generative AI applications that serves a wide variety of AI team members from technical developers to business SMEs
- Platform capabilities that enable multirole AI teams to collaborate with friction-free workflows
- Strong data governance with tracking of data lineage and model accuracy within training and deployment processes
- Tools supporting both low-code users and professional data science coding environments
Q: How has the AI/ML Platforms market evolved in 2024?
A:
- AI teams are expanding beyond data scientists to include business and technology leaders, subject matter experts, application developers, solution architects, business analysts, and UX designers
- Rapid advancements in generative AI are evolving faster than any other modern technology
- Agentic AI is emerging as a step change that will transform how enterprises operate, serve customers, and adapt to the market
- Unified data mesh supported at the platform level is becoming more common, enabling better data lineage transparency and model monitoring
- Vendors are expanding governance capabilities to address complex and fragmented AI regulations
- Advanced users are combining traditional predictive models with generative models in hybrid applications
- The pace of AI innovation requires platforms that keep pace with or push the envelope of enterprise AI technology
Q: What differentiates Strength of Offering vs. Strength of Strategy?
A: Current Offering (vertical axis) evaluates the strength of a vendor's current AI/ML platform capabilities across data management, model training and evaluation, governance, application development (both predictive and generative AI), and architecture (workload performance, security, ecosystem). Strategy (horizontal axis) evaluates the vendor's vision for enterprise AI transformation, innovation pace, product roadmap (especially for agentic AI), partner ecosystem strength, market adoption, and pricing transparency. Current Offering focuses on what the platform can do today, while Strategy assesses the vendor's direction and ability to keep pace with rapid AI advancement.
Reference
- Forrester, The Forrester Wave™: AI/ML Platforms, Q3 2024, 28-Aug-2024, ID
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