By Eve Davies, Azzure IT
Artificial Intelligence has been around for many years; however, it is only in more recent times that it has started to become integrated into mainstream technology and gain mainstream adoption.
Now referred to by many as machine learning, this ever-evolving piece of technology has now become an integral part of many businesses and their plans for achieving continual growth and success.
Gone are the days of science-fiction movies scaring us into being afraid of the powers of artificial intelligence, instead having advanced technology is being embraced by more and more businesses world-wide every day. The power of AI should be embraced in today’s modern, digital world businesses – not pushed away out of fear.
Today, our customers are using artificial intelligence in their everyday business operations – without which, their businesses wouldn’t be nearly as efficient, their service levels would be of lower quality, and thus, achieving the level of success they strive towards becomes a far more difficult mountain to climb. Don’t just take our word for it – here are a couple of real business-world examples of companies using AI :
Cashflow Forecasting
It’s common that customers often don’t pay to the terms on their invoices – some will pay early, some will pay on time, but in a lot of instances, payments are made late. Managing your cashflow and producing a cashflow forecast can be a huge task and is often near impossible to get accurate when there are many variables at play.
Machine learning looks at the previous payment history of both customers and suppliers to predict the payment history trends before looking at a customer’s outstanding invoices. It then uses this information to predict when a payment will be made, resulting in a more accurate cashflow forecast with no manual input.
Stock Availability
In the new world, businesses need to become more agile and able to meet the ever-changing needs of their customers. Predicting stock levels can be a time-consuming task, often resulting in lack of the right stock at the right time due to misjudgment.
Machine Learning looks at previous trends of stock usage – not just over the last few months but over a much longer period to factor in customer changes and seasonal demand changes, too, when gathering information. From this, it will search customer by customer, item by item, to create a time phased demand and forecast what demand you are most likely to expect from your customers. This will then produce a suggestion of what purchase orders should be placed and when, ensuring you have the right stock of the right products at the right time.
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