Scaling agentic AI is becoming a top priority for enterprises, but success depends less on models and more on data readiness. According to McKinsey & Co., almost two-thirds of organisations have experimented with AI agents, yet fewer than 10% have scaled them to deliver measurable value. The primary barrier is data, with eight in ten companies citing data limitations as the greatest obstacle.
The urgency is growing. Gartner forecasts that global AI spending will reach $2.5 trillion in 2026, while IDC warns that companies without AI-ready data could lose up to 15% of their productivity by 2027. This highlights a clear reality: scaling agentic AI is fundamentally a data problem, not just a technology challenge.
Agentic AI relies on continuous access to high-quality, trusted data to automate workflows and make decisions. Fragmented systems and data silos reduce accuracy and limit scalability, especially as organisations move toward multi-agent environments, where systems collaborate across tasks.
- Data quality is the top barrier to scaling AI agents.
- Less than 10% of enterprises have achieved agentic AI at scale.
- AI-ready data can prevent productivity losses of up to 15%.
- Most enterprise systems remain disconnected, which limits the impact of AI.
To address this, McKinsey outlines four critical steps. First, identify high-impact workflows suitable for automation, focusing on repetitive and deterministic tasks. Second, modernise the data architecture to ensure interoperability and seamless access across systems. Third, enforce strong data quality standards, including governance, lineage, and consistency. Finally, build operating models that redefine human roles toward the supervision and orchestration of AI agents.
Ultimately, scaling agentic AI requires rethinking how work is structured across technology, data, and people. Organisations that invest in strong data foundations and governance will be able to move beyond pilots and unlock real business value, turning AI into a true competitive advantage.
ソース：
https://www.zdnet.com/article/scaling-agentic-ai-requires-strong-data-foundation/
