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Finance leaders face the challenge of effectively integrating emerging technologies like AI and ML into their planning processes. With the abundance of hype surrounding these technologies, it's crucial to separate the noise from the strategies that truly deliver measurable value. In this blog, we will explore the top five cross-functional AI use cases that Finance should own and drive, focusing on how to begin leveraging AI to produce results. By incorporating these strategic initiatives into the planning process, Finance teams can gain valuable insights and drive outcomes that positively impact the organization's success.

Demand planning is a critical cross-functional process, which helps to align and forecast customer demand for a product or business. It aids to optimize inventory management, avoid supply chain disruptions, and minimize supply chain inefficiencies. It also helps to increase overall customer service level, customer satisfaction, efficiency, and profitability. Demand planning compliments sales and operation strategy by providing direction and forward-looking guidance. Demand planning, including demand sensing, should be a continuous process to support effective decision making at all levels.

In traditional budgeting environments planning demand and thus revenues, has typically been a semi manual process. For example, an insurance company might model premium income by starting with policies currently in force, estimating attrition rates, forecasting new policies due to marketing efforts, and adding in the impact of increased  or decreased premiums, in order to come up with projected policy volumes and premium income. This process relies upon the subjective judgment of someone who is reasonably expert in the particular insurance market.