78% of organizations now use AI in at least one business function, and 71% report using Generative AI — yet the gap between adoption and measurable value has never been wider. McKinsey & Company data confirms that Gen AI has reached virtually every boardroom. At the same time, Gartner projects that businesses adopting Generative AI could achieve 15.7% cost savings. The opportunity is clear. The question is whether organizations are pursuing it with the right structure in place.
Most are not. 74% of companies struggle to scale AI initiatives beyond the pilot phase — not because the technology fails them, but because their data foundations, technical infrastructure, and organizational workflows aren't ready. Only 37% of business leaders say their infrastructure and data strategy are actually prepared. And 30% of Generative AI projects are predicted to be abandoned after proof of concept by the end of 2026, due to poor data quality, inadequate risk controls, or unclear business value. Ambition without structure is costly.
This guide from N-iX, authored by Yaroslav Mota, Head of AI and Engineering Excellence at N-iX, maps out five concrete steps organizations can follow to build a reliable, governance-ready AI implementation roadmap: assessing business needs and ROI potential, establishing a strong data foundation, conducting a technical infrastructure assessment, capitalizing on data governance (including GDPR and CCPA compliance), and integrating and scaling AI solutions across production workflows. It's a framework built for teams that have moved past exploration and are ready to commit to execution.
Discover how to assess readiness, govern data, and scale Gen AI from pilot to production: get the full analysis in this guide!
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97% of executives believe Generative AI will benefit their business, but only 37% have the infrastructure to ensure it. Explore five steps to assess readiness, govern data, and scale AI in this guide!
