Business and technology leaders are increasingly adopting agentic AI, yet many struggle to achieve the desired return on investment. The report highlights that inadequate infrastructure and data are major obstacles to realizing the technology’s potential. AI agents require seamless access to enterprise data in various forms, including structured and unstructured data, to make real-time decisions. Legacy systems, even those updated recently, often fail to meet these demands, creating significant barriers to effective AI implementation.
The report, based on a survey of 300 data and technology executives, finds that data leaders are achieving greater success with agentic AI by ensuring access to over 70% of their data. These organizations trust their AI agents’ decisions, indicating a strong correlation between data readiness and AI reliability. In contrast, only half of the surveyed organizations trust their agents’ decisions, highlighting the critical role of a reliable data foundation in AI performance.
The report emphasizes that data access and governance are top priorities for scaling agentic AI. Over 69% of respondents expect to use agentic AI widely within two years, but without addressing data system constraints, the technology risks failing to deliver promised efficiencies. Organizations must prioritize modernizing their data environments to support the growing demands of AI agents.
Source: mittr
