The Next Frontier for Generative AI: Business Decision Making

As companies evaluate how to derive value from generative AI initiatives, IDC predicts a major paradigm shift in its use — with 35% of enterprises worldwide using GenAI to co-develop digital products and services by 2025, potentially doubling their revenue growth compared to their competitors.*

While much has been said about the value of ChatGPT and other GenAI tools for content creation and search, the use case that I want to highlight is GenAI’s ability to help us engage with data, make better decisions, and by doing so deliver greater value to the enterprise.

The growing discipline of decision intelligence addresses the business need for greater velocity and accuracy by using AI to harmonize data, identify patterns, and deliver recommended actions that optimize for desired results. Today, we can benefit from AI-powered recommendations that can be executed autonomously in order to generate revenue, avoid risk, reduce CO2 emissions, and balance sustainability with service levels.

Now, advancements in GenAI make it even easier to engage with data and make decisions by streamlining the process.

Stronger together: Predictive, prescriptive, and generative AI

Although ChatGPT and other generative AIs are powerful tools, they have limited value in addressing business problems. The large language models (LLMs) that power them lack structured data-processing capabilities, specific domain and market knowledge, and the context necessary to make reliable and accurate recommendations and automate processes.

However, by combining a trained LLM with predictive and prescriptive AI models that are purpose-built to analyze massive amounts of data and address specific tasks, it becomes possible to identify risks and opportunities, deliver recommendations, and execute decisions through conversational interactions.

For example, let’s assume a logistics manager has questions about route performance. A tool like ChatGPT cannot give an answer to this question, but decision intelligence can. Using AI models designed with business knowledge and context, an LLM-powered digital agent can understand the question, then respond with relevant information and visuals in dialogue with the user.

That platform can go even further by delivering real-time recommendations, then executing them in response to the manager’s instructions – seamlessly writing back to systems of record and data sources as a result of that conversational interaction.

In this way, GenAI and LLMs become the gateway to data, recommendations, and execution. Instead of spreadsheets or static charts that leave the burden on people, AI makes it possible to engage with a platform conversationally in order to make better, faster decisions. This type of contextual human/machine interaction has been dreamed about for decades. Today, it is a reality.

No “hallucinations,” only facts

One concern with GenAI has been accuracy. You may have read stories of AI-created “hallucinations” – generated content that seems plausible, but isn’t factual.

It’s natural to be cautious about trusting GenAI with critical business needs – you can’t afford to risk a “hallucination” impacting your supply chain, manufacturing, or customer service.

When used with predictive and prescriptive AI, an LLM can only return accurate results because it only analyzes information imported directly from the client’s systems of record and data sources.

This needs to be emphasized, because it is crucial to understand that we can build trust in GenAI as a business solution. An LLM interface adds a new and intuitive way of engaging with data and decisions, creating a solution that is more powerful than the individual components alone.

The future is AI-powered

A recent IDC study** revealed that enterprises actively using AI to accelerate and improve decision making experienced improvements across a number of metrics – including product or service innovation, employee retention, customer retention, and risk management.

As the value of AI-powered decision making becomes clear, we will see more organizations joining the ranks of leaders by adopting this technology. All of this means we can look forward to a more promising future where business decisions are easier to make and execute, thanks to AI innovation.