Valiantys

AI investment is increasing. Measurable transformation outcomes are not keeping pace. Only 28% of organisations surveyed say they are achieving their desired outcomes from AI and digital transformation. For technology leaders, the question is shifting from: “Are we doing enough with AI?” to: “Can we prove that our transformation is creating value?”

A successful AI pilot is evidence that something is possible. It is not evidence that the organisation can scale it. Scaling requires repeatable architecture, trusted data, governance, skills, adoption and outcome measurement. Without those elements, organisations risk accumulating pilots without creating enterprise value.

AI adoption is not the same as AI readiness. 98% have at least one AI initiative. Only 3% feel fully ready for AI disruption. Activity measures whether initiatives exist. Readiness measures whether the organisation can scale them. Readiness depends on foundations, governance, skills and outcomes. Where does your organisation sit? Read the research.

The market often frames AI readiness as a tooling problem. In practice, the harder questions are usually organisational: · Can teams work across fragmented systems? · Is data accessible and governed? · Are transformation outcomes clearly defined? · Can the operating model support scale? AI can expose weaknesses that already exist in the technology estate. The organisations that succeed will address those foundations alongside their AI initiatives. Read the Omdia research.

98% of organisations are already running at least one AI initiative. Only 3% believe they are fully ready for the disruption AI may create. The challenge is no longer starting an AI project. It is building the foundations, governance and operating model required to scale AI across the enterprise. New research with Omdia explores the gap between AI ambition and transformation readiness. Read the research.

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