Dive Brief:
- Enterprises need a strong data foundation to scale AI agents, a report from Google Cloud and MIT Technology Review Insights published Wednesday found. The report is based on a global survey of 300 CIOs, CTOs and other IT and data executives.
- Nearly all surveyed enterprises plan to use AI agents, with more than two-thirds planning to deploy agents within the next two years, according to the report. However, only 10% of companies today deploy agentic AI widely across the business.
- “Without a deep understanding of the full data estate, including unstructured dark data, you do not have the quality and trust to activate agents at scale,” the report’s foreword said.
Dive Insight:
Limited access to enterprise data — along with necessary overhauls to business processes, the workforce and governance policies — pose challenges to scaling agentic AI.
Only 15% of companies have successfully scaled multiagent systems, according to a Deloitte report. IT leaders surveyed for the report said their organizations were, at a minimum, three to four years away from redesigning processes and workflows around agentic AI.
For long-term success with agentic AI, data access is key, according to the Google and MIT report. Today, AI has access to just 45% of enterprise data on average, according to surveyed organizations. Additionally, only half of organizations trust that AI agent decisions are relevant and accurate, which the report said is a direct reflection of an enterprise’s data readiness.
Global IT spend is projected to reach $6.31 trillion this year as enterprises pour significant resources into the latest AI developments in pursuit of operational efficiency and productivity gains. To reach those gains, the Google and MIT report said IT leaders will need to focus on the data foundation and updating legacy systems, which can further hamper AI’s access to data.
It’s a tack The Magnum Ice Cream Company is taking as it builds its tech stack from scratch, Michael Friedlander, CIO of the Americas, told CIO Dive in a previous interview. A clean data foundation to support future AI capabilities is the cornerstone of Friedlander’s approach.
“The shift from answering questions to taking actions means AI agents need data from across the enterprise, in all its structured and unstructured forms, and with the right business context,” the report said. “To make decisions and act in real time, agents also need frictionless access to the organization’s operational systems — for example, those storing its supply chain, point-of-sale, or human resources data.”
