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Data Foundation for AI: From Experiments to Enterprise Scale
Overview:
AI investment is accelerating rapidly. Global AI spending is forecast to reach $2.7 trillion in 2026, growing 49.5% year-on-year. Yet only 22% of organisations report having successfully scaled AI across multiple business units or adopted an AI-first approach.
The gap is increasingly about data.
More than 75% of organisations are prioritising AI-ready data investments, with data readiness identified as a key barrier to AI success. Gartner also highlights that AI-ready data must evolve continuously — with context, governance and accessibility becoming critical as organisations move towards agentic AI.
For today’s CIOs, CTOs, CDOs and CAIOs, the question is no longer simply how to deploy AI, but:
How do we unlock enterprise AI at scale from the data and technology investments we already have?
This exclusive, closed-door Times Group × Denodo Think Tank brings together technology leaders across industries to explore how organisations can build an AI-ready data foundation without defaulting to large-scale replatforming — while balancing speed, governance, cost and operational risk.
The conversation will focus on:
- Accelerating AI outcomes by making existing enterprise data accessible, contextual and AI-ready.
- Scaling beyond pilots to production-grade AI and emerging agentic use cases.
- Reducing complexity and cost by leveraging existing data investments rather than continually moving and duplicating data.
- Embedding governance and trust without slowing innovation.
- Connecting data strategy to business value — faster decisions, greater productivity and measurable AI ROI.
What to Expect:
Participants will apply, operationalise, implement, integrate and demonstrate approaches to:
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1
Apply
AI-readiness frameworks to existing data environments.
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2
Operationalise
The journey from experimentation to enterprise-scale deployment.
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3
Implement
Governance, security and risk controls alongside AI innovation.
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4
Integrate
Fragmented data, context and business semantics across the enterprise.
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5
Demonstrate
How the right data foundation can accelerate measurable AI outcomes.
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