State of GenAI Data Readiness in 2024 - Survey results are in!

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State of the Market Survey

GenAI adoption 2024:
Challenges with enterprise data

As organizations dive into the world of generative AI, many are hitting a roadblock: their data isn't ready.

We surveyed 300 enterprises that are implementing GenAI to discover their top challenges and how they're overcoming them.

LLM augmentation: A must-have for 86% of organizations

When looking at GenAI adoption, the overwhelming majority—86%—are opting to augment their LLMs, using frameworks like Retrieval Augmented Generation (RAG), recognizing that out-of-the-box models often lack the customization needed to meet specific business needs.

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86% Use augmented LLMs
14% Use generic LLMs

Status of RAG adoption

We see a strong momentum in adopting RAG for pilot projects, particularly in industries where data privacy and response accuracy are critical. The transition to full production is still limited, reflecting the complexities of scaling these technologies.

Health & Pharma

75%

Financial Services

61%

Retail + Telco

57%

Travel & Hospitality

29%

Top concerns in leveraging enterprise data for RAG

The survey reveals a unique set of challenges specific to enterprise application data, including scalability, data quality, and real-time access. Organizations have yet to fully address these unique challenges.

48%

Scalability and Performance

46%

Data quality and consistency

43%

Data security and privacy

46%

Real-time data integration and access

44%

Data governance and compliance

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