Too many companies still rely on manual forecasting because they think AI requires better quality data than they have available. Nowadays, that’s a costly mistake. In a year defined by historical inflation and pandemic-induced disruptions, the spotlight is on demand forecasting and inventory planning.
In 2022, McKinsey reported that 73% of supply chain leaders relied on spreadsheets for planning, with a promising 43% looking to adopt AI and machine learning for some planning activities. This shift signifies a long-due move from conventional methods to leveraging tech, potentially reducing human bias and running multiple predictive scenarios simultaneously. The transformative potential of generative AI is no longer a subject of debate. CEOs should see it as a requisite area of exploration.
Generative AI’s tangible benefits are increasingly apparent across sectors, making it a strategic imperative for businesses. While costs and risks vary based on the use case, starting with a solid business case can help navigate the adoption journey. However, the need for accurate forecasting in operations seems here to stay. The question is not whether to adopt, but rather how deeply and where to employ AI’s capabilities.
