... Access Insights Already a Gartner client? AI pricing uncertainty is a material enterprise risk. As vendors blend subscriptions, consumption and outcomes, costs become harder to predict at scale. CIOs must understand trade-offs and actively manage pricing to protect value, predictability and trust. Strategic ...
Analyst(s): Hannah Decker | Shruthi Shankel | Andy Rowsell-Jones | Bill Ryan | Akanksha Pandey | John Santoro
Get more from Gartner
Interested in receiving proven business and technology insights, analyst guidance, benchmarks, diagnostics and more? Connect with a Gartner representative to learn more about becoming a Gartner client.
... This AI briefing examines three important updates: market consolidation in AI-ready data infrastructure, IBM’s new Red Hat AI Inference service, and Microsoft’s DELEGATE-52 research on systemic agentic AI vulnerabilities. Insights at a Glance Strategic Planning Assumption Issue Impact More Detail Gartner ...
Analyst(s): Shubhangi Jena | Auria Asadsangabi | Lucas Kobat
... Access Insights Already a Gartner client? Traditional agent observability creates a blind spot. AI agents meet service level agreements while drifting from business intent or compliance. To ensure compliance, trust, and control, monitor reasoning drift — tracking how decisions are made, not just outcomes ...
Analyst(s): Antonia Roesler | Priya Sundararaman | Ben Yan
... For AI products priced using AI units, customers need consumption controls to increase adoption. Because so few AI providers offer effective controls, product leaders can differentiate model-agnostic AI products by allowing customers to manage inference tiering, user-volume limits and task-volume limits ...
Analyst(s): Bill Ryan | Ron Burns | John Santoro | Will Sommer | Mike Tucciarone
... Access Insights Already a Gartner client? AI-free will bifurcate the market into products that integrate AI and those that omit AI as the primary focus. Product leaders should pursue unexpected market opportunities with “AI-free,” focusing on high-risk use cases where trust, predictability, and human ...
... Artificial intelligence leaders are responsible for accelerating AI-driven transformation and innovation across business units and functions. This job description highlights the need for an AI Leader and defines the role’s responsibilities. When to Use Directions for Use Gartner Research ...
... adopts GenAI, marketing analytics teams must ensure data is AI-ready, redefine analyst roles and enable AI-driven decisions. This session introduces a data-readiness framework for marketing, outlining five key milestones on the journey to advanced AI enablement. You will also learn how to evolve marketing ...
... Insights Already a Gartner client? AI agent management platforms unlock new revenue potential by creating demand to address challenges across scalability, reliability, privacy and agent sprawl. To capture agentic AI leadership, product leaders must transition from building AI agents to provide comprehensive ...
Analyst(s): Ethan Cai | Christine Tenneson | Aakanksha Bansal | Alfredo Ramirez IV | Kiumarse Zamanian
... finance AI initiatives stall because of persistent manual workflows, opaque algorithms and low trust. Driver maps give CFOs a practical way to embed business logic in management reporting and financial planning, setting the stage for scaling finance AI. Insights at a Glance Challenges in Scaling AI Without ...