... on budgets, procurement strategies and infrastructure planning Extreme demand for AI infrastructure is creating unprecedented shortages in DRAM and NAND supply, driving significant increases in server and storage prices. With hardware costs rising sharply and supply constraints impacting infrastructure ...
Analyst(s): Chandra Mukhyala
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... •Identify the AI agent delivery and management capabilities that matter most and how to prioritize investments •Understand how leading organizations are developing these capabilities in practice •Evaluate the platforms and operating model components that support AI agents at enterprise scale CEOs and ...
... next phase of AI infrastructure growth •How the shift from AI training to inference and agentic AI is changing demand •Why token economics are becoming a critical measure of AI infrastructure value •How technology investments can align with emerging AI workload requirements As the market shifts from training ...
... models influences purchase likelihood •Identify where AI is shaping behavior across the customer journey and how to respond •Evaluate the role of branded platforms in an AI-mediated buying environment Customers are rapidly incorporating generative AI into their buying journeys and are expected to increase ...
... •How to select and prioritize AI value metrics that align with growth, margin improvement, workforce productivity and client experience •How to build an executive-level AI dashboard using leading and lagging indicators •How to evaluate AI investments across growth, efficiency, adoption and client outcomes ...
... •Leverage AI for cybersecurity strategically without falling for vendor hype •Prioritize securing the AI you buy, build and consume, including AI embedded in products and services •Develop an adaptive roadmap that enables AI innovation while managing trust, risk and security over time AI is reshaping ...
... foundation models, AI platforms and rapidly evolving agentic capabilities. Yet while some organizations are moving AI from experimentation to production and enterprise scale, many remain stuck in pilot mode. The difference is not the model itself. It’s how the enterprise is engineered around AI. Drawing on ...
... opportunities for physical AI adoption across business operations •Build and execute effective physical AI exploration programs and proofs of concept •Techniques to evaluate readiness for scaling physical AI beyond pilot initiatives •Integrate and operationalize physical AI solutions to deliver measurable ...
... •Identify where AI can create the greatest enterprise value and focus workforce investments on the business outcomes that matter most •Accelerate work redesign, capability development and access to expertise to help the organization move at the speed of AI •Reinvest AI-enabled workforce capacity into ...