The generative AI in business is a market in full acceleration. According to the IDC analyst firm, by 2028 it should represent $ 632 billion.
The adoption of the generative AI (GENAI) accelerates in the business world. IA spending on the whole should more than double by 2028, when they should reach $ 632 billion, according to IDC, with an investment plan “Investi” for the EU of 200 billion euros. Generative AI expenses (Genai), specifically, should reach $ 202 billion over the next three years, representing 32% of overall IA expenses. Money will be widely spent in AIP applications, services and infrastructure, including optimized software storage for companies.
Companies are massively adopting AI chatbots to personalize the customer experience and improve their services. The development of large language models (LLM), such as Chatgpt, and small models of language (SLM) has opened a new kingdom of possibilities, in particular the use of infused Chatbots of AI to respond to requests submitted by the customers of an organization. Data storage plays a role.
However, a major problem emerges that threatens user confidence: AI hallucinations.
The problem of hallucinations IA
Imagine a familiar scenario: you consult a company’s website and an IA chatbot is committed to you for a “personalized customer experience”. You ask a complex question requiring precise information to make a purchasing decision. The chatbot provides you with a detailed, convincing response, with specific options and deadlines. You are impressed by the quality of the answer. However, there is a major problem: the information is completely false.
It is an “ia hallucination” – when AI creates connections between data without appropriate context to seem credible. The AI has assembled pieces of disparate information, inventing a plausible but erroneous response. Studies reveal that chatbots hallucinate up to 27% of the time, with factual errors present in 46% of the texts generated according to the Natural Language Processing Journal.
This situation becomes critical in sectors such as health, finance, education or manufacturing. The consequences can be dramatic: unnecessary medical procedures, bad financial decisions, supply chain breaks, or loss of confidence of students towards educational institutions.
The role of business storage infrastructure
The key to reducing AI hallucinations lies in the business storage infrastructure and the owner information it contains. Private data, updated and unique to each company, allow Chatbots to refine and validate their answers with precision.
The RAG architecture (Retrieval-Augmented Generation) represents the revolutionary solution. Deployed on business storage infrastructure, it allows AI models to access vector databases containing updated proprietary information. RAG guarantees relevant, contextualized responses and eliminates the need to constantly re-training the AI models.
Practical actions for IT teams
Companies can use their existing storage systems without specialized equipment. Key recommendations include:
• Deploy a high performance storage infrastructure with low latency and autonomous automation technology • Simplifying architecture by consolidating multiple consolidation systems in petact -optimized storage solutions to RAG • Optimizing for regular quality data regularly updated from business databases • Ensure 100% availability, automation and cost savings
This storage -centered approach allows companies to effectively mix the impact of AI hallucinations while fully exploiting the generative AI transformer potential for their business.
