As AI brokers grow to be embedded extra broadly in enterprise operations, the necessity to overcome the restrictions of legacy knowledge methods grows extra pressing. If Gartner’s prediction that AI brokers will increase or automate 50% of enterprise selections by 2027 proves appropriate, organizations should remove bottlenecks or danger depriving brokers of the info they should make the suitable selections at velocity.
This report, based mostly on a survey of 300 knowledge and know-how executives, explores how legacy methods are limiting the effectiveness of AI brokers in lots of organizations. It finds {that a} handful of organizations—the info leaders—are having better success with agentic AI and experiencing fewer knowledge limitations because of legacy methods. These leaders provide a information to creating the suitable knowledge atmosphere for brokers to flourish and trusted methods to scale.
Key findings from the report embrace:
Few firms at present present agentic AI with ample entry to enterprise knowledge. Throughout all of the surveyed organizations, AI solely has entry to a median of 45% of firm knowledge. That quantity falls to 30% or much less in organizations categorized as “knowledge laggards”. A choose group, nevertheless, ensures entry to over 70% of their knowledge. These “knowledge leaders” are having better success with their brokers than the remaining.
Belief in agent selections is a mirrored image of knowledge readiness. At present, solely round half of surveyed organizations belief that the selections their AI brokers make are correct and related. Against this, 100% of the info leaders belief their brokers’ selections, a powerful indicator that dependable AI requires a dependable knowledge basis.
Knowledge leaders discover it simpler to attain agent scale and velocity. Two-thirds of knowledge laggards say legacy knowledge methods restrict AI agent scaling (66%) and stop brokers from making selections at velocity (68%). Having largely overcome legacy knowledge constraints, the leaders have principally cleared these roadblocks, with simply 8% reporting both constraint.
The stress is on to make knowledge estates agent-ready. Inside two years, 100% of respondents plan to be utilizing agentic AI, with 69% anticipating to make use of it broadly. With out eradicating knowledge system constraints, agentic AI will fail to ship the specified velocity and efficiencies it guarantees.
Knowledge entry and context are prime priorities. Crucial initiative to allow scaling amongst all respondents is enhancing entry to structured and unstructured knowledge for AI brokers. Additionally excessive on the record is enhancing knowledge and AI governance with enterprise context. Knowledge leaders are additionally focusing closely on the automation of knowledge administration.
