The AI context gap: Enterprise AI organizations have a trust problem, not a retrieval problem — and most are still building the fix
Source: VentureBeat AI
Summary
- A recent survey of 101 enterprises showed that the infrastructure feeding AI agents their business context is being built faster than it can be trusted.
- This has resulted in a majority of enterprises experiencing AI agents producing confident but wrong answers due to missing or inconsistent context.
- A governed semantic layer is emerging as the fix for this issue, but most enterprises are still in the process of building it.
- The field is converging on hybrid retrieval, and provider-native tools are leading the market in practice, but a plurality of enterprises intend to keep best-of-breed tools instead of consolidating onto a provider's native context stack.
Why It Matters
- Most enterprises are struggling to trust the information their AI agents are providing, which can lead to business decisions being made based on incorrect information.
- This can be costly and damage a company's reputation.
- The solution to this problem is a governed semantic layer, which can provide a reliable source of context for AI agents.
- However, building this infrastructure takes time and resources, and most enterprises are still in the process of doing so.
- The lack of trust in AI agents can also lead to missed opportunities for businesses, as they may be hesitant to rely on AI-driven decisions.
- This can limit the potential of AI to drive business growth and innovation.
- Furthermore, the market is consolidating in a way that may not be in the best interest of enterprises, with provider-native tools leading the market but a plurality of enterprises intending to keep best-of-breed tools.
GenAI EXPLAINED
A governed semantic layer is a type of infrastructure that provides a reliable source of context for AI agents. It is essentially a layer of information that can be trusted and relied upon by AI systems. Think of it like a dictionary or a database that contains accurate and up-to-date information. A governed semantic layer can help to prevent AI agents from producing confident but wrong answers due to missing or inconsistent context.
Hybrid retrieval is a type of retrieval system that combines multiple approaches to retrieve information. It is a more robust and reliable approach to retrieval than provider-native tools or dedicated vector databases. Hybrid retrieval can provide more accurate and relevant results, which can help to reduce the context gap and improve the trustworthiness of AI agents.
Provider-native tools are software solutions that are developed and provided by a specific company, such as OpenAI or Google. These tools are often leading the market in practice, but a plurality of enterprises intend to keep best-of-breed tools instead of consolidating onto a provider's native context stack. This may be due to concerns about vendor lock-in or the desire to maintain independence and flexibility in their technology choices.
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