Report:
The Forrester Wave™: AI Platforms, Q3 2026
How does Forrester define the AI Platforms market in 2026?
The AI platform market has evolved beyond data science workbenches to encompass diverse vendor capabilities clustering around distinct sweet spots: horizontal use cases, industry-specific depth, technology/cloud affinity, and workflow specialization. Enterprises are shifting from a single-platform approach to a portfolio strategy, matching use cases to platforms based on sweet-spot fit and interoperability. The market emphasizes agentic AI that creates value through workflow execution rather than insights alone, with vendor vision and roadmap mattering as much as current functionality as digital workers reshape enterprise structure.
Key Facts for The Forrester Wave™: AI Platforms, Q3 2026 in 2026
- Publication Date: 13-Aug-2026
- Document ID: f7b6e35e
- Summary: In our evaluation of AI platform providers, we identified the most significant ones and researched, analyzed, and scored them. This report shows how each provider measures up and helps you select the right one for your needs.
- Authors: Mike Gualtieri, Rowan Curran
How did the AI Platforms market evolve in 2026?
- One AI platform is not enough - vendors have distinct sweet spots in data science, workflows, AI applications, and industry-specific solutions
- An influx of new entrants has widened vendor differences rather than narrowing them
- Vendor capabilities cluster around distinct sweet spots: horizontal use cases, industry-specific depth, technology/cloud affinity, and workflow specialization
- Workflows and execution, not just insights, are the value driver in agentic AI
- Deep integration with enterprise knowledge, context, and processes turns AI into completed work
- Agentic AI will reshape enterprise structure as digital workers take on entire functions
- 15 vendors evaluated across Leaders, Strong Performers, and Contenders categories
- Vendors evaluated include Google, Pegasystems, Palantir, C3 AI, Amazon Web Services, Microsoft, ServiceNow, Dataiku, DataRobot, Databricks, IBM, UiPath, Oracle, SAS, and Salesforce
What product features are required to be included in this year's evaluation?
- AI-focused lifecycle development capabilities. The vendor natively provides development lifecycle tools and capabilities to build bespoke AI solutions.
- General-purpose market focus. The vendor approaches the market with a platform to develop AI solutions for a broad swath of vertical and/or horizontal enterprise use cases even though the vendor may also offer use case accelerators.
- Substantial revenue in the market. The vendor has at least $50 million in annual revenue from the AI platforms product in the last four quarters.
- Market momentum among Forrester's enterprise clients. Forrester clients frequently mention the product as one they are considering prior to a purchase. We have heard about the product from our clients in the form of inquiries, advisories, consulting engagements, and other interactions over the past year. Other vendors mention this vendor as a competitor.
What are the common features of top products in the AI Platforms space?
No common features specified.
Scope Exclusions
- Vendors with less than $50 million in annual revenue from AI platforms products
- Vendors focused exclusively on narrow vertical or single use case solutions without general-purpose capabilities
- Vendors without native AI lifecycle development tools and capabilities
- Vendors without significant market momentum or mention among Forrester enterprise clients
- Pure infrastructure providers without integrated AI development capabilities
- Vendors that declined to participate or only partially participated in the evaluation process
Inclusion Criteria
Vendors must, among other requirements:
- AI-focused lifecycle development capabilities - The vendor natively provides development lifecycle tools and capabilities to build bespoke AI solutions
- General-purpose market focus - The vendor approaches the market with a platform to develop AI solutions for a broad swath of vertical and/or horizontal enterprise use cases
- Substantial revenue in the market - The vendor has at least $50 million in annual revenue from the AI platforms product in the last four quarters
- Market momentum among Forrester's enterprise clients - Forrester clients frequently mention the product as one they are considering prior to a purchase
Offering Strengths — Relative Weighting
- Data modeling — 8%
- Data integration — 8%
- Data science — 8%
- Foundation models — 8%
- Model evaluation — 7%
- Knowledge and context management — 8%
- Agent development — 8%
- App/Gen tools — 7%
- Cohesive experience — 8%
- Governance controls — 8%
- Runtime architecture — 8%
- Platform management — 7%
- Security certifications — 7%
Strategy Strength — Relative Weighting
- Vision — 15%
- Innovation — 15%
- Roadmap — 20%
- Partner ecosystem — 15%
- Community — 20%
- Supporting services and offerings — 15%
FAQs
Q: What does this research cover?
A: This research evaluates 15 AI platform providers across their current offerings, strategy, and customer feedback. It assesses capabilities for data science, model development, agent development, application building, data modeling, governance, and runtime architecture. The evaluation focuses on platforms that support the full lifecycle of AI applications, including copilots and agents, with general-purpose market focus rather than vertical-specific solutions.
Q: Who should use this research?
A: AI platform customers using this evaluation to inform a purchase decision should use it to match platform sweet spots to their highest-value and most imminent use cases. Technology leaders, whether first-time buyers or those with operational AI platforms, should treat sweet-spot fit and interoperability as key decision criteria. The research helps enterprises build an AI platform portfolio strategy rather than forcing all use cases onto a single platform. It's particularly valuable for evaluating vendors' vision, innovation, and roadmap alongside current capabilities.
Q: What are the mandatory features of vendors included in this market?
A: Vendors must provide: (1) AI-focused lifecycle development capabilities with native tools to build bespoke AI solutions, (2) general-purpose market focus supporting broad vertical/horizontal enterprise use cases, (3) at least $50 million in annual revenue from AI platforms products in the last four quarters, and (4) significant market momentum with frequent mentions from Forrester enterprise clients in inquiries, advisories, and consulting engagements.
Q: What are some reasons for not being included in this report?
A:
- Annual revenue from AI platforms products below $50 million threshold
- Lack of general-purpose capabilities - focused only on narrow verticals or single use cases
- Absence of native AI lifecycle development tools and capabilities
- Insufficient market momentum or client mentions among Forrester's enterprise client base
- Declined to participate in the evaluation process
- Only partial participation in the evaluation without providing full vendor materials
Q: What should buyers consider when evaluating products in this market?
A:
- Your AI platform strategy will be a portfolio, not a monolith - match use cases to platforms based on sweet-spot fit and interoperability
- Workflows, not insights, are the value driver in agentic AI - evaluate platforms on how well they model and execute processes
- A vendor's vision and roadmap matter as much as its current functionality - weigh innovation capacity and future direction heavily
- Scrutinize both breadth and depth of vendor capabilities and match platform sweet spots to highest-value and most imminent use cases
- Evaluate deep integration with enterprise knowledge, context, and processes that turns AI into completed work
- Consider the platform as a bet on which vendor can carry you into the agentic future, not just a tool for current use cases
Q: How has the AI Platforms market evolved in 2026?
A:
- AI platform strategy shifting from monolithic to portfolio approach with vendors having distinct sweet spots
- Workflows and execution becoming the value driver over insights in agentic AI applications
- Deep integration with enterprise knowledge, context, and processes critical for turning AI into completed work
- Agentic AI reshaping enterprise structure as digital workers take on entire functions
- Platform selection becoming a bet on which vendor can carry enterprises into the agentic future
- Vendor capabilities widening rather than narrowing as new entrants join the market
- Emphasis on how well platforms model and execute processes, not just predict or explain
Q: What differentiates Strength of Offering vs. Strength of Strategy?
A: Strength of Offering evaluates current platform capabilities across technical dimensions including data handling, model development, agent building, user experience, governance, and infrastructure. Strength of Strategy assesses forward-looking elements including vendor vision for the market, innovation capacity, product roadmap, ecosystem partnerships, community engagement, and support services.
Reference
- Forrester, The Forrester Wave™: AI Platforms, Q3 2026, 13-Aug-2026, ID f7b6e35e
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