Reimagining Enterprise AI strategy : The case for Full Stack Enterprise AI Platforms

The enterprise AI market is experiencing unprecedented investment, with nearly 80% of companies deploying generative AI technologies in 2024. However, this enthusiasm has yet to translate into meaningful business impact, creating what McKinsey terms the “AI paradox” – high adoption but minimal bottom-line results.

With 42% of AI projects failing to reach production and Gartner predicting 40% of agentic AI projects will be canceled by 2027, enterprises are recognizing that piecemeal approaches are insufficient for sustained value creation.

Unlike conventional AI tools that merely assist existing workflows, agentic AI systems autonomously perceive, reason, plan, and execute complex business processes end-to-end. The solution lies in full-stack agentic AI platforms. Organizations that succeed in this new paradigm will be those that can structure their enterprise knowledge, orchestrate multi-agent workflows, optimize model selection dynamically, and embed governance by design across all AI operations.

This whitepaper outlines how full-stack Enterprise AI platforms are uniquely positioned to help organizations break out of the AI paradox. Built on four core components – knowledge management, multi-agent orchestration, model optimization, and enterprise governance – these platforms deliver measurable business outcomes, operational efficiency, and scalable AI transformation.

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