At the digital event "Artificial Intelligence and its Application in Controlling" CoPlanner was invited to present a concrete application for AI in controlling:

Artificial intelligence will take a firm place in controlling

Where are the concrete application areas for AI in controlling? Which goals should be formulated for the application? Under which conditions can AI be used sensibly? At the W&P Digital Event " Artificial Intelligence and its Application in Controlling", W&P gave the attending medium-sized managers recommendations for action for a decision-oriented controlling of the future.

"Artificial intelligence will take a permanent place in controlling and is already making a significant contribution to improving controlling tools," says host Dr. Günter Lubos, member of the management board of Dr. Wieselhuber & Partner (W&P).

As a result of AI, controlling will become faster, more efficient and more meaningful, making targeted and effective corporate management possible in the first place.

Dr. Wolfgang Doneit, AI expert at W&P, adds: "Especially in an environment with many influencing factors, the use of AI is worthwhile in order to manage complex tasks".

He also recommends a step-by-step optimization of controlling processes, starting with routine tasks. The first step is to integrate AI algorithms into software solutions: "Delegating routine tasks to AI algorithms frees up resources for value-adding tasks.

Automated AI forecasts are often surprisingly close to manually created ones - but cost much less time," says Heinrich Nordsieck, CEO of the software provider CoPlanner.

Focus of AI in the area of controlling: The use in the analytical area to improve the informative value of the controlling output. Here, AI offers tools that can be used to improve the accuracy of planning. Plan-actual deviations are analyzed more quickly for their cause, clusters and anomalies in large amounts of data are detected. From the ongoing project support at customers, W&P knows that more than 70 percent of a data-driven project takes place in the explorative data analysis, data cleansing and preprocessing.

Accordingly, "AI projects in controlling will never be a sure-fire success - you need high data quality for reliable information quality!" concludes Lubos.

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