Essential Insights
- Most companies only give AI access to about 45% of their data, with data leaders accessing over 70%, resulting in better AI success.
- Trust in AI decisions correlates with data quality; data leaders fully trust their AI, unlike laggards, highlighting the importance of a reliable data foundation.
- Legacy data systems significantly hinder AI scaling and speed, with most laggards citing these limitations, while data leaders have mostly overcome them.
- Nearly all organizations plan to adopt agentic AI soon, emphasizing the urgent need to remove data system barriers and improve data access and governance for success.
Overcoming Legacy Data Barriers
As AI agents become more common in businesses, many companies face a major hurdle: outdated data systems. These legacy systems limit how much data AI can access. Currently, most organizations give AI access to only about 45% of their data. In contrast, data leaders — the organizations leading in AI use — provide over 70%. This gap impacts what AI can do. Without better data access, AI cannot reach its full potential. To succeed, companies must modernize their data infrastructure and remove bottlenecks. This way, AI agents can make smarter, quicker decisions.
The Trust Factor in AI Decisions
Trust is key when it comes to AI. If organizations don’t believe in their AI’s decisions, they won’t rely on them. Today, only half of surveyed companies trust their AI decisions. However, all data leaders trust theirs. This shows that a strong data foundation leads to better confidence in AI. When data is reliable and comprehensive, AI makes relevant, accurate choices. Trustworthy decisions help scale AI use and improve overall outcomes. Building this trust requires clear data governance and ensuring AI always gets the right context.
Preparing Data for the Future
The push to adopt agentic AI is clear: nearly everyone plans to use it within two years. Still, many companies worry about lagging behind if they don’t improve their data systems. Without better data access, AI can’t operate at high speed or scale, which limits its benefits. The top priority now is automating how companies manage and update data. Improving access to both structured and unstructured data is crucial. As organizations focus on these efforts, those who lead will likely see faster, more reliable AI that truly transforms their business.
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