Editorial September 2023

Software is eating the world, and AI is eating software. And now, generative AI is changing the menu.

In the innovation era, the demand for data-driven insights has surged. Businesses are eager to hop on to the generative AI bandwagon and use large language models (LLMs) to their advantage. And truly, these tools hold the promise of unlocking new levels of innovation, efficiency and strategic insights. But while public LLMs are excellent for using widely available data, they fail to meet the unique needs of individual companies.

This limitation highlights the need for a fresh approach, where businesses leverage generative AI to glean insights from their proprietary and unique data. But the challenge is that to do that companies must either invest in significant customization or train an LLM from scratch.

Additionally, they must tackle the problem of scattered data “puddles” that block holistic insights.

The solution lies in an Intelligent Data Mesh. A dynamic, digital fabric that connects the dots across tools and teams in real time. This federated system enables enterprises to take a public LLM and fine-tune it with proprietary, fine-grained, enriched data that provides the needed context.

By providing LLMs with relevant information and potential risks tied to various outputs, organizations ensure informed, intelligent decision-making aligned with their goals. In this rapidly evolving landscape, the marriage of LLMs, the Intelligent Data Mesh, and context-aware analytics stands as a transformative force, reshaping how organizations harness data and drive innovation.