Enterprise AI organizations have a trust problem, not a retrieval problem — and most are still building the fix

The trust issue affects the reliability of AI systems, which may deter enterprise adoption.

While there is a growing reliance on cloud-native solutions, concerns about data handling persist.

Startups aiming to provide independent solutions may find opportunities but also face challenges.

Leads in provider-native retrieval tools that enterprises rely on.

Offers competitive retrieval solutions through Vertex AI.

Conducted the survey providing insights into enterprise AI challenges.

Potential vulnerabilities in AI systems if context layers are not securely managed.

Inconsistent data feeding AI could expose organizations to governance and compliance risks.

AI generating unreliable outputs could tarnish the credibility of organizations.

The ambition to create a governed semantic layer entails significant technical challenges.

The rapid buildout of AI context layers could face implementation hurdles.

No immediate geopolitical factors affecting the technology landscape are identified.

Growing scrutiny on data handling and AI transparency may lead to new regulations.

No significant supply chain disruptions reported in AI context infrastructure.

The shifting landscape may require new skill sets, impacting existing job roles.

Organizations may face liability for decisions made based on faulty AI outputs.