How to incorporate Agentic AI into business planning processes

Artificial Intelligence (AI) is here to stay, with many companies already using it to enhance business performance. The latest development in this space is Agentic AI, which is being utilized for capabilities such as scenario planning, problem-solving, automating tasks and decision-making. Organizations that ignore the potential uses of Agentic AI risk falling behind their competitors who are utilising it to differentiate themselves and gain an edge. Niels Van Hove, Customer Engagement Lead at Aera Technology and expert in decision intelligence and AI agents, shares his views on the topic and how to effectively incorporate AI into business planning processes.

Understanding Decision Intelligence
Decision Intelligence (DI) refers to the digitalization, augmentation and automation of decisions through AI. It enables businesses to digitalize data and automate decisions, helping them stay aligned with their strategic goals. For example, in supply chain operations, where organizations must continuously collaborate inventory in the supply network, AI can automate decision-making to reduce workload and help manage inventory more effectively.

Similarly, with Integrated Tactical Planning (ITP) - planning across the short-term horizon - there is a high frequency of decisions that need to be made, which can quickly become too much for people to deal with. Agentic AI can help automate decisions fast. In industries where there are high volumes of decisions required, the value of agentic AI becomes especially clear.

How to start using agentic AI
To implement AI, identify what your business wants to achieve, set goals, and provide this information to the AI platform. This allows the software to learn and support your decision-making. Start small and work collaboratively with the AI software before scaling up.

An effective way to hit the ground running is using an existing use case, which you know works and where you understand the output. Use this as proof of concept. Once AI has successfully automated that process, you can scale this to other areas of the business. This phased approach enables your team and technology to learn and adapt together.

Once you have tested AI, you can then utilize it as part of a business planning process such as Integrated Business Planning (IBP).

Agentic AI and IBP
Currently in IBP, most decisions are made in PowerPoint and Word and are yet to be digitalized. This presents a significant opportunity. By recording and analyzing these decisions with Agentic AI, businesses can learn from patterns and continuously improve.

One of the big applications I foresee for using Agentic AI alongside a business planning process such as IBP, is automating gap detection. If you are running a planning cycle and know your targets and sales revenue, you can get AI to create scenarios or present different options for closing any gaps. Whilst final decisions are likely to be made at IBP meetings, AI supports this decision-making process by providing data, detecting issues, and running simulations.

Additionally, AI can be used for data reporting. For example, you could ask the software to provide a report on deliveries from one location to another. From that, you can prompt it further: What are my biggest problems? What are your recommendations? The software will provide insights and suggested recommendations.

Of course, for AI to work effectively in these planning processes, the quality and handling of data is crucial.

Using data wisely and securely
Data is an organism, and it is always growing. Whilst it is never perfect, it’s never a reason not to do anything with it. It’s the input that matters. Use intelligence on top of various types of data, whether internal, external, unconstrained (less organized) or structured, to automate and augment it. This will allow you to engage with the software and get recommendations to execute a decision.

Avoid overloading AI with too much data – focus on what you need, rather than what you have. Define your data needs and be specific about which data supports which decisions. Sensitive data, such as customer information, will of course need to be protected. Therefore, consider data governance to protect data by establishing strategies for access, usage, and security.

Some companies are already using agentic AI to automate decisions, especially when it comes to making decisions in the short-term planning horizon. Think about what you want to achieve and your needs, so AI can understand this intelligence and provide recommendations to make your business processes more efficient.

Are you ready for AI? Listen to this episode of our Tech Transform podcast with Oliver Wight Partner Rod Hozack and Niels Van Hove.
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