The proven capacity of artificial intelligence (AI) technologies to accurately forecast stock requirements offers transformative power to a business. By using AI to analyse sales trends and forecast demand, the business can satisfy customer demand in a timely way, eliminating the stock-outs and excess inventory costs that could otherwise result in dissatisfied customers and lost sales.
By continuously monitoring stock levels, automated systems are able to initiate replenishment orders when stock levels fall below predetermined thresholds. This automation minimises the necessity for manual stock checks, helps the business run smoothly, and saves time and resources.
AI-driven stock management frees up capital otherwise locked up in unsold product
An AI-driven stock management system not only mitigates the extra storage expenses associated with overstocking and the sales lost by understocking, it also frees up capital that would otherwise be locked up in unsold product for investment in growth opportunities, debt repayments or other business areas.
AI-based stock management increases productivity within the organisation. The time and effort previously required for stock-related tasks can be redirected into value-added activities, including customer service and sales. It also reduces the risk of errors associated with incorrect orders or misplaced items.
Another beneficiary is supplier relationship management. For instance, if a supplier delivers an order late, the delivery terms can be modified in subsequent orders to mitigate the risk of stock-out.
Challenges
While AI’s advantages are clear, integrating it into stock management systems presents numerous obstacles, not least the integration of data from multiple sources. AI’s efficacy is contingent on the accuracy and quality of the stock data, which makes a robust data management system and processes essential.
To ensure a seamless transition to AI, businesses must invest in change management strategies. Employee training programmes will help discourage staff resistance to modifications to existing processes.
Perhaps the biggest challenge of all is that the initial AI investment can be substantial. With the primary objective of technological adaptation being financial gains, a thorough assessment of the expected benefits should be conducted in advance to ensure they outweigh the associated costs. Only once this has been completed and approved should the green light be given to proceed with the project.
