Gartner acknowledges the growth of Decision Intelligence Platforms with the first Magic Quadrant

The business world is undergoing a profound transformation, moving from a “data-driven” mantra to one that is “decision-centric,” powered by Decision Intelligence Platforms (DIPs). This emerging segment, which recently saw its first Magic Quadrant from Gartner shows that the focus is shifting from simply analyzing data to actively growing and executing the decision-making process itself.

Earlier iterations of this type of platform, back in the late 1990s and early 2000s, were called digital decision-making platforms, which Gartner analyst Kjell Carlsson told SD Times was all about automated decision-making. Later came the idea of ​​software intelligence platforms, based on AI visualization and value stream management to detect and fix problems in the software process, and that employees are assigned the right tasks to achieve business value. “So the opportunity here is to go in and take what was effectively a traditional market, business rules engines… and now we have an opportunity to go in and add more machine learning and AI productivity capabilities and be able to really transform the way we make decisions in many areas of the organization,” he explained.

He said the policy aims to prevent catastrophic, value-destroying decisions—such as the AOL Time Warner merger or the HP-Compaq merger—by streamlining the decision process and ensuring that the right information is flowing. “Of course, if we had been able to present the right information and structure the decision-making process in a rational way, we would have been able to avoid that,” said Carlsson. “And that’s at a high level. It boils down to all the decisions we make in an organization that doesn’t have the right information. You are not doing enough analysis about it. You can’t look at past decisions and learn from them.”

Augmented decision-making involves platforms that ensure that a person has processed, integrated, and contextualized information, while managing authorizing workflows (such as coordinating sign-outs). Full automation is reserved for low-risk, high-volume processes, such as small credit decisions or quick auto insurance quotes, where the process is highly controlled and speed is important.

Carlsson noted that Decision Intelligence Platforms can track past results, reveal errors and biases in the decision-making process to make organizations better. “And now, with generative AI, we can tap into unstructured data,” he said. “We can go in and use these tools to formalize that decision-making process, and be able to track and trace its results.”

In determining which companies make it to the Magic Quadrant, Carlsson explained that Gartner looks at organizations from two levels: product or service capabilities, and the higher organization itself, but he admitted that more weight goes into critical strengths.

The retail landscape is a mix of old and new. Long-time leaders of digital decisions like FICO represent innovation, beneficial maturity and proprietary data for regulated use cases. In contrast, new, pro-code platforms such as Quantexa offer flexibility with features such as proprietary information graphs for complex construction, custom analysis applications. Ironically, both analytics giants are IBM and SAS, where decision modeling is a strong part of their advanced analytics portfolio.

However, Carlsson noted, the market is new, and adoption of productive AI in these fields is not yet strong. The market is vulnerable to potential disruption from large AI companies, such as OpenAI, if they decide to focus on specialized tooling. The main challenge, however, may be less about technology and more about human nature: the inherent reluctance of leaders and managers to use tools that track, compare, and judge the results of their personal decisions.

Here are the statistics for this space from Gartner:

By 2027, 25% of unmanaged decisions using large-scale linguistic models (LLMs) will cause financial or reputational losses due to human bias, insufficient critical thinking, and AI consensus.

By 2027, 50 percent of business decisions will be augmented or automated by AI agents to make smarter decisions.

By 2028, 25% of CDAO’s vision statements will be “decision-oriented,” surpassing “data-driven” slogans, and people’s decision-making behaviors are clearly targeted to improve the value of D&A.

By 2030, business decisions with a clear model will be five times more reliable and 80% faster than unmanaged decisions, enabled by the adoption of platform intelligence.