Data and AI Trends 2024
Trend4
2.5 minute read
Operational data will unlock gen AI potential for enterprise apps.
71% of organizations plan to use databases integrated with gen AI.
Why should you care?
1
Large language models are great, but not always a good fit for business needs.
2
2024 will see a rise in enterprise gen AI applications that rely on operational databases.
3
Databases that can’t integrate gen AI capabilities are quickly becoming redundant.
For organizations who are able to integrate operational data with gen AI, the rewards will be huge. Successful databases will deliver real-time, hyper-personalized, and contextually-relevant experiences across enterprise applications.
Databases that fail to integrate gen AI capabilities will quickly become obsolete. This pressure is leading to rapid advancements to infuse AI capabilities into existing data platforms.
“Many of our customers have started to innovate with gen AI capabilities by leveraging off-the-shelf large language models. However, they are finding that large language models on their own are insufficient for building high quality and non-hallucinating enterprise gen AI apps. Databases bridge that gap by grounding the LLMs and the applications in the actual enterprise data to provide accurate, domain-specific experiences. That is why we are seeing increased interest in enterprise-ready databases with vector capabilities and their integration with orchestration frameworks.”
“Many of our customers have started to innovate with gen AI capabilities by leveraging off-the-shelf large language models. However, they are finding that large language models on their own are insufficient for building high quality and non-hallucinating enterprise gen AI apps. Databases bridge that gap by grounding the LLMs and the applications in the actual enterprise data to provide accurate, domain-specific experiences. That is why we are seeing increased interest in enterprise-ready databases with vector capabilities and their integration with orchestration frameworks.”
“Customers are looking to leverage the power of LLMs by augmenting them with their domain knowledge and enterprise data. To support these new use cases, cloud-based database solutions that also embrace open-source Gen AI orchestration frameworks will provide application developers with the capabilities to help them quickly and more efficiently build Retrieval Augmented Generation (RAG) applications.”
“Customers are looking to leverage the power of LLMs by augmenting them with their domain knowledge and enterprise data. To support these new use cases, cloud-based database solutions that also embrace open-source Gen AI orchestration frameworks will provide application developers with the capabilities to help them quickly and more efficiently build Retrieval Augmented Generation (RAG) applications.”
Inside our one-of-a-kind approach.
Google Cloud helps organizations unify data and connect it with groundbreaking AI to unleash transformative insights and personalized experiences.
By harnessing the simplicity, scalability, security, and intelligence of Google's unified data and AI approach, businesses can unlock the full potential of their data in a single, streamlined solution.
Because Google Data Cloud consolidates workloads and manages the entire data life cycle, data teams are empowered to develop modern, data-driven applications using popular open-source engines and models.