Decision Intelligence – this is how most businesses will adopt AI
As Artificial Intelligence moves from the world of academia to commercial applications, we see the technology sector fragment into categories. Decision Intelligence (DI) is the application of AI to the decision-making process. It is industry- and department-agnostic – decisions are the one thing every function in every business has in common.
Gartner predicts that over a third of large organizations will be using DI by 2023, and pioneers like Peak are firmly of the opinion that this is the route by which most businesses will adopt AI. But what is meant by Decision Intelligence? And how can you use it to apply AI to your business?
Getting to grips with DI
Decision-making is at the center of every business, so there’s a logic in applying commercial AI there. DI helps ensure consistent, accurate and rapid decision-making by harnessing the predictive power of machine learning (ML).
In a world where only a quarter of commercial machine learning models make it into production (and even fewer have a commercial impact), the need and potential for this technology are striking. Decision Intelligence can be leveraged by just about every business in every sector to optimize the entire value chain. It can route delivery vehicles more efficiently, advise on an optimum markdown price, or even recommend associated products to website users. DI stops teams throughout an organization from making a ‘best guess.’ Instead, it provides real-time predictive analytics so they can anticipate what’s coming next.
Unique businesses need unique AI
Organizations looking to implement DI need three core things to make it happen; an AI-ready dataset, a centralized intelligence unique to their business, and a dashboard that non-technical teams can use to interact with a model and its outputs.
Leveraging a unique intelligence is a key aspect of DI. Many AI providers have focused on standardizing the technology, providing out-of-the-box solutions that can be plugged in and used to optimize anything from email marketing to website recommendations. While these generic solutions can be deployed quickly, they are not unique and provide the same benefits to you as to a competitor. Worse yet, your AI website recommendation engine doesn’t have visibility of what’s happening across the value chain, so it might, for example, heavily promote out-of-stock products, negatively impacting your customer experience.
Decision-making can’t be achieved by a generic intelligence. Every business is unique and has its own customer behaviors, logic and learnings. A standardized AI that makes the same decisions for every business that uses it would be disastrous.
“The future of commercial AI is an intelligence unique to every business. An AI that works holistically across each department so that one function is never optimized at the expense of another,” says Peak CEO and co-founder Richard Potter. “Most businesses recognize that one centralized intelligence is the end goal, and they’re working towards adopting a connected application that delivers value for everyone within the organization.”
DI adoption beyond enterprise
Gartner predicts over a third of large organizations will be using DI in a little under two years. But if this is the technology that will put AI in the hands of every business, then it’s vital to consider small-to-medium businesses and sectors that typically lag behind in AI adoption.
The applications for this technology are practically limitless. But what will its transition into the mainstream look like? Similar to the trajectory of CRMs in the early 2000s, says Peak. The approach of early adopters at that time was to build CRMs in-house. Today, you’d struggle to find a business that didn’t buy its CRM off the shelf.
Decision Intelligence is already on a similar path, with businesses moving to license DI platforms like Peak rather than investing huge sums in building AI capabilities from scratch. Doing so decreases the time to value and cost of ownership of the technology.
To discover how you can build and deploy DI, book a platform demo with Peak.
1 December 2022
30 November 2022