Building Trusted Data Foundation for Scalable AI
Scaling AI Starts with Data Readiness
AI has moved from experimentation to the boardroom agenda—nearly 90% of enterprises see it as a strategic priority. Yet most are still stuck at the starting line. Legacy infrastructure, siloed data, poor governance, and talent shortages continue to stall enterprise-scale adoption. The reality? Only 28% of organizations consider themselves advanced in data readiness.
Now, with Gen AI and agentic AI reshaping expectations and fueling investments, the execution gap has never been more urgent. Enterprises are discovering that the real barrier to AI at scale isn’t the model—it’s the data.
About the report
In collaboration with Everest Group, this report uncovers how enterprises are rebuilding their data foundations to enable AI at scale. Drawing from a survey of 120+ enterprises and in-depth interviews with senior data and AI leaders, it delivers:
Why the AI imperative has made data readiness non-negotiable
The current enterprise data landscape and its biggest gaps in readiness
Seven core pillars for building a scalable, trusted data foundation
How leading enterprises are operationalizing readiness with technology, talent, governance, and organizational enablers
Practical lessons and best practices to accelerate enterprise AI adoption
Who should read this report
CXOs, business unit heads, CDOs, and data and AI leaders will find clear, actionable insights to:
- Diagnose readiness gaps across systems, people, and processes
- Prioritize investments that align data efforts with AI and business outcomes
- Build a roadmap where data becomes a catalyst not a constraint for enterprise-scale AI
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