A successful AI strategy typically rests on two pillars: a programmatic process that aligns stakeholders and prioritizes high-value use cases, and an architectural foundation that integrates hardware, software, and data in a way that can scale. Futurum Research notes that organizations without a formal AI roadmap are more likely to report minimal returns from early AI pilots—reinforcing the importance of structure, governance, and a cohesive plan from the outset.
In the latest market brief, Accelerating Enterprise AI: From Complexity to Competitive Advantage—completed in partnership with Dell Technologies—Futurum Research examines why enterprise AI can feel complex, and how an integrated approach can help simplify deployment and accelerate time-to-value. The report highlights Dell’s “AI Factory” framing, outlines key components of an end-to-end AI approach (use cases, infrastructure, data, services, and ecosystem), and shares customer examples that illustrate how organizations can operationalize AI more effectively.
In this brief, you will learn:
- Why enterprise AI initiatives often stall between pilots and production—and what to do differently
- How a programmatic AI lifecycle approach helps prioritize high-value use cases and maintain business alignment
- The core elements of an integrated AI architecture (data, infrastructure, software, services, and partners)
- How expert services can support strategy, implementation, and long-term management and scaling
- Real-world examples of organizations using AI platforms to drive efficiency, security, and measurable outcomes
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Author Information
Nick Patience is VP and Practice Lead for AI Platforms at The Futurum Group. Nick is a thought leader on AI development, deployment, and adoption - an area he has researched for 25 years. Before Futurum, Nick was a Managing Analyst with S&P Global Market Intelligence, responsible for 451 Research’s coverage of Data, AI, Analytics, Information Security, and Risk. Nick became part of S&P Global through its 2019 acquisition of 451 Research, a pioneering analyst firm that Nick co-founded in 1999. He is a sought-after speaker and advisor, known for his expertise in the drivers of AI adoption, industry use cases, and the infrastructure behind its development and deployment. Nick also spent three years as a product marketing lead at Recommind (now part of OpenText), a machine learning-driven eDiscovery software company. Nick is based in London.
