One of the most dramatic effects of generative artificial intelligence is on its way, as businesses apply the revolutionary technology to understanding and acting on business itself.

In 2023 the world felt the gen AI revolution through computers that responded to ordinary language and produced original text, images, music and software code. This was possible through large language models, which used deep learning technology to plow through masses of structured and unstructured data, intuiting likely patterns in the data and leveraging that understanding to generate new creations. 

On the basis of its breakthroughs, we are seeing exceptional amounts of innovation throughout the process. New LLMs offer greater choice and use cases, data technologies are being optimized for gen AI, companies are grounding results in better-managed proprietary data, and there are emerging new skills such as prompt engineering. Such refinements mean better results, understanding of cost to value, and greater deployments across business.

The new virtual colleague

That is less the end than the beginning. Better gen AI will interact with people less like a traditional spreadsheet, graph or traditional business intelligence dashboard, and more like a healthy expert community, interacting with its operator in a dynamic conversation that can understand questions and offer insightful, context-aware responses.

It may be something like working alongside a knowledgeable colleague, sparking and informing a conversation about, say, why sales numbers are moving the way they are, how recent changes in the commission model seem to have affected this, and next steps that might be taken to improve margins. 

Moreover, putting gen AI in the background of this process will expand the function and utility of a BI dashboard. One popular social media platform is effective partly by offering short videos, but even more from a background algorithm that puts in front of the user new videos they don’t know about but will like. The BI equivalent would be other data the human hasn’t asked to see that is relevant to their job and questions, or even notifications of other questions the person might want to ask.

Clearly, this is much more than a simple chatbot welded to a BI dashboard, or another incremental productivity improvement: It is a new system of insight and action. And, most importantly, it will scale insight in both the human and computational axes. 

Scaling human and computational insight

Since gen AI interacts with people in natural language, it is a democratization of access to computing on a par with the personal computer, the internet or the mobile app. Anyone can use it, in an increasing number of use cases. Already, we are seeing gen AI used by the most advanced data scientists and by sales personnel on the retail floor.

All of these individual questions, across a vast series of roles and contexts, can be aggregated. That means people can see how others found successful answers to questions, what kinds of questions are trending across a business, and which interactions have had the greatest impact over a day, a quarter or a year.

That is a hitherto unknown insight, and a new kind of virtual collaboration across the company. It will meet the greatest success through a secure, transparent system that protects personal privacy and rewards healthy information sharing.

In addition to this scaled human insight, gen AI may also scale itself, aggregating siloed information into an overall depiction of the business in all its complexities and dependencies, such as the production process, supply chains or external economic events. Insights from one part of the company, such as marketing or manufacturing, can be scaled to a new type of collective insight. 

The future is here, awaiting even distribution

A future BI prompt might well be, “Explain my business in five charts, and tell me what I should learn next.” This may not remove the level of complexity involved in managing a business, but it’s certain to lead to greater insight, greater efficiency, greater value and more time on meaningful work, one of the greatest rewards possible.

The most astonishing thing in this scenario is that very little of it is far in the future or requires yet-unseen innovation. Many of the parts are already in place, and will be assembled and refined in the coming year, with more to follow. As usual, the best way to learn more is to engage with what’s going on, and share your learning.

Danny Lange is vice president of engineering at Google Cloud. He wrote this article for SiliconANGLE.

Image: graphixmade/Pixabay