Business Reporter says AI value depends on trust and governance

Business Reporter published an article arguing that enterprise AI is moving from adoption to measurable outcomes, with trust, context and accountable data governance becoming the main tests of success. The piece says the EU AI Act reinforces that shift and points to DataGalaxy as a governed context layer for AI agents.

Why it matters: - Enterprise AI adoption is no longer the main challenge; proving business value is. - In regulated sectors such as banking, insurance, healthcare and critical infrastructure, AI decisions must be transparent and accountable before employees and customers can trust them. - The article argues that closing the AI velocity gap depends on governance, not more experimentation.

What happened: - Business Reporter published an article by Nicolas Averseng, Chief Product Officer at DataGalaxy, on July 17, 2026. - The article says the key bottleneck in enterprise AI is the gap between AI promises and the value organizations are realizing. - The piece says business leaders now want outcomes instead of more pilots. - Business Reporter points readers to the article for more information.

The details: - The article says the biggest barriers to AI success are inconsistent data maintenance, unclear ownership of business-critical information, and AI-driven decisions that cannot be traced back to their source. - Employees hesitate to rely on AI recommendations when accountability is unclear. - The EU AI Act is cited as evidence that trust, explainability and accountability are becoming central to AI deployments. - Organizations must show how AI systems reach decisions and identify who is responsible for them. - Edosa Odaro, author of The Values of Artificial Intelligence, says success comes from measuring business outcomes, not simply AI adoption. - The article says every business-critical data asset should have a defined owner, an agreed business definition and measurable quality. - Organizations should continuously review AI initiatives and retire those that do not deliver proven business value. - DataGalaxy describes itself as a governed context layer for AI agents that helps organizations create context, enforce trust and track the value of data and AI initiatives from one place. - DataGalaxy says it was founded in France and is expanding across Europe and the United States. - The company says more than 200 global enterprises use DataGalaxy, including Dior, Airbus, SNCF and SwissLife.

Between the lines: - The article frames AI governance as a business operating discipline rather than a compliance afterthought. - The shift in emphasis suggests many enterprises have already learned that model performance alone does not produce usable or trusted AI outcomes. - The regulatory backdrop is pushing companies to connect AI outputs to data ownership, decision logic and measurable impact.

What's next: - Enterprises are expected to keep tightening AI governance as they move from pilots to production use. - Companies that cannot show measurable value may face pressure to cut or retire underperforming AI initiatives. - The article suggests future AI investment will increasingly favor systems that can prove context, trust and business impact.