Originally published in Forbes Technology Council
In a recent Forbes Technology Council article, Arango CEO Shekhar Iyer discusses how the EU Artificial Intelligence Act signals a broader shift in enterprise AI: trust is becoming the deciding factor in successful AI adoption.
As AI systems move from experimentation into enterprise decision-making, accuracy alone is no longer enough. Organizations must be able to explain how AI systems generate outcomes, what information those decisions rely on and whether the results are appropriate given the business context. Without shared business context—the underlying reality behind enterprise data—even accurate systems can struggle to earn trust at scale.
The EU AI Act reflects this growing expectation. The regulation introduces a risk-based framework requiring high-risk AI systems to meet standards around transparency, monitoring, human oversight and data quality. While these rules apply directly to companies operating in the EU, the article argues that their impact extends much further. The Act formalizes what organizations, customers and boards are already demanding: AI systems that are explainable, accountable and defensible.
Many enterprise AI initiatives still struggle because business meaning is fragmented across disconnected systems. Without a shared and auditable view of data, organizations cannot easily explain or govern AI outputs. Building a contextual data foundation—one that preserves relationships, meaning, time and provenance across enterprise data—helps address this challenge by giving AI systems the context needed to produce traceable and trustworthy results.
As AI becomes more embedded in enterprise decisions, the article concludes that trust will define the next phase of adoption. Organizations that prioritize explainability, context and accountability will be best positioned to scale AI systems that leaders can defend and organizations can rely on.
Key Takeaways
- Trust—not just accuracy—is becoming the key requirement for enterprise AI adoption.
- The EU AI Act introduces expectations around transparency, explainability, monitoring and human oversight.
- AI systems require shared business context to produce outcomes that organizations can explain and defend.
