Aera Technology has unveiled research from IDC showing that decision intelligence is boosted by AI agents. The research entitled, Accelerating enterprise decision intelligence with AI agents shows how AI has bridged the gap between insights and action. It follows on from an earlier paper by the two vendors in 2023. Since that paper went live, IDC says that the rise of AI agents brings “reasoning and orchestration, enabling systems that can plan, decide, and act within defined parameters.”
Fred Laluyaux, Co-Founder, President, and CEO of Aera Technology, said, “We’re at a clear inflection point as companies adopt, scale, and choose to run their operations with decision intelligence.
“The technology is proven, customers are scaling it, and the ecosystem is ready. Decision intelligence is rapidly becoming the new operating model for the AI-powered enterprise — and today at AeraHUB, we’re showcasing what comes next: the rise of agentic decision intelligence.”
What did IDC uncover?
While shifts in technology are often overhyped, and real change takes time to occur, that is not the case here. Although IDC states that leveraging AI for insight and action is evident among early adopters, it goes on to say that AI agent–powered decision intelligence represents a structural change in how organisations think, decide and act.
Importantly, the use of AI in decision intelligence is taking a different path from the often observed rush to use Gen AI. Instead of employee replacement, it is showing improvements across a number of defined key business metrics. Those metrics include areas such as customer satisfaction, employee retention, operational efficiency, and risk management.
Six competencies of decision intelligence
At the core of those metrics are six measures of decision intelligence. Each is a separate step that builds towards success, and early adopters are at different points on that journey. However, when treated as a closed loop, it results in higher quality and increased speed.
- Acquisition and organization of data into a form that makes data available for analysis
- Analysis of data, including identifying trends and anomalies and reviewing KPIs, etc., using descriptive and predictive methods
- Performing simulations, which involves performing what-if scenario analyses and simulations
- Recommending a decision by predicting likely outcomes, evaluating, and recommending optimal alternatives
- Executing decisions (i.e., acting based on the decision made)
- Monitoring, evaluating, and continuously learning from decisions, actions, results, and simulations
While IDC talks about a closed loop, that does not mean this is a one-and-done. It is a continuous process, as step six shows. In recent briefings by Aera Technology, it has talked about how customers develop what it calls skills. Each of those skills comes from customers identifying an area where they want to apply AI agents, and by going through the processes above.
An increased cadence of review is necessary
The report also looks at the frequency with which review cycles take place. For this to be effective, it has to be weekly, rather than the monthly or quarterly cycles often used. That frequency of review requires the use of AI agents within the process.
The advantage of using agents is the continuous monitoring that they deliver. According to the study, “AI agents can continuously sense changes in demand, risk, or opportunity, simulate outcomes, and execute approved actions in real time.”
It goes on to cite examples of how AI-driven decision intelligence has been used by organisations. At AeraHub London, earlier this year, Sam Mulligan, Senior Director of Digital & Lean, Clinical Manufacturing and Supply at AstraZeneca, spoke on stage about challenges with supply chain waste. In this video, he talks about how Aera Skills play a significant part in decision intelligence.
What else did we learn from the research?
There are a lot of numbers in the research. Importantly, they show an increasing shift towards AI-driven decision intelligence. It claims 88% of enterprises have either implemented or plan to pilot decision intelligence initiatives. 70% of leaders have already deployed such systems. Additionally, 84% of enterprises surveyed are using AI to support decisions, with 40% viewing AI agents as key to accelerating speed, scale, and impact.
This is also about making AI core to the enterprise, and 83% are already on an AI transformation journey. Interestingly, it does not distinguish between Gen AI and decision intelligence use.
The research also looked at the breadth of tools that organisations use in their decision-making. Unsurprisingly, 86.8% use spreadsheets, with 75.6% using data integration and governance software. What AI-driven decision intelligence does is better integrate that data and provide a coherent workflow. This is a significant change in terms of accountability and trust.
Another benefit of using AI, as shown by the research, is the increased speed of decision-making. This is partly about the data acquisition, as mentioned above, and also the ability to perform simulations and collaborations. It removes the need to build complex spreadsheets and makes it possible to share data and achieve consensus across the business.
Enterprise Times: What does this mean?
Few research reports these days deliver anything new. Most are a rehash of the obvious with quantitative statistics. This report, however, delivers more detail and justification for its conclusions. While there are a lot of statistics throughout, they have been put into context, making them usable.
What it also does is show that decision intelligence has come of age. It is at the point of moving from niche usage to widespread adoption. Importantly, it does that without the random loss of institutional knowledge that firing staff for Gen AI brings. Instead, it uses human knowledge of systems to help build skills and bring greater awareness of what is happening in the business.
It will be interesting to see how this feeds into future business for Aera Technology. The company now has multiple customers prepared to talk about the benefits they are seeing. In every case, there is cost reduction and significant improvements in decision intelligence.
