To fulfill the expectations being heaped upon it, artificial intelligence (AI) will need to deliver applications that significantly reduce costs, increase revenue and enhance asset utilization, according to McKinsey Global Institute, which recently surveyed more than 3,000 senior executives across ten countries and 14 sectors, on the use of AI technologies.
McKinsey also reviewed more than 160 use cases and shared its insight in a recent discussion, Artificial intelligence: The next digital frontier? The research was conducted jointly with Digital McKinsey, a global practice that helps companies design and implement digital transformations.
“Early evidence suggests that AI can deliver real value to serious adopters and can be a powerful force for disruption,” the report states. “In our survey, early AI adopters that combine strong digital capability with proactive strategies have higher profit margins and expect the performance gap with other firms to widen in the future.”
The report categorized the ways in which AI can create value in four areas:
- enabling companies to better project and forecast to anticipate demand, optimize R&D, and improve sourcing;
- increasing companies’ ability to produce goods and services at lower cost and higher quality;
- helping promote offerings at the right price, with the right message, and to the right target customers; and
- allowing them to provide rich, personal, and convenient user experiences.
1. Projection and forecasting
The report asserts that organizations need to constantly anticipate the future to gain competitive advantage. AI allows businesses to provide better forecasts for their supply chain and design better offerings. Reliably forecasting demand is a way to use AI’s ability to digest disparate data and automatically adjust to new information. It can discern trends and patterns that can be acted on. Businesses use this tool in a number of ways, such as forecasting demand to stock only the specific quantities of specific products they will sell and thus minimize waste, and anticipating sales trends so they can order more soon-to-be-popular items.
The benefits of projecting demand go beyond traditional business sectors. For example, by using sophisticated algorithms, health systems increasingly can predict—and prevent— major epidemics. The report’s review of use cases found that AI-based approaches to demand forecasting are expected to reduce forecasting errors by 30-50 percent over conventional approaches.
Lost sales due to product unavailability can be reduced by up to 65 percent. Costs related to transportation and warehousing and supply chain administration are expected to decrease by 5-10 percent and 25-40 percent, respectively. With AI, overall inventory reductions of 20-50 percent are feasible.
2. Getting more from machines
AI can help businesses produce by continually optimizing assets and processes, assembling the best teams of people and robots, improving quality and reliability, and preventing downtime for maintenance— all of which increase productivity.
“The obvious role for AI is to replace humans through automation,” the report states. “However, in some situations, AI is complementing teams of people.”
The paper gives the example of Ocado, the UK online supermarket, which illustrates how this happens when a company embeds AI and robotics at the core of its operations. In the retailer’s warehouse, robots steer thousands of product-filled bins over a maze of conveyor belts and deliver them to human packers just in time to fill shopping bags. Other robots whisk the bags to delivery vans whose drivers are guided to customers’ homes by an AI application that picks the best route based on traffic conditions and weather.
3. Promotion/marketing offerings
Armed with enough of the right kind of data, the paper states that companies can use artificial intelligence to price goods and services dynamically, raising prices when demand rises or a consumer appears willing to pay more, and lowering them when the opposite happens. Yield management programs have been dynamically pricing airline seats, hotel rooms, and other perishables for years, but AI will allow sellers to extend dynamic pricing to the rest of the marketplace.
Today, the requirements of intelligent price management are high: Customers expect a good price, and price transparency for brand-name products is close to 100 percent. The basic question to ask for each item is: What price is the customer willing to pay? Hyperconnected consumers continuously redefine value by comparing prices online, even when browsing in a brick-and-mortar store. The optimal price for a product depends on many factors: the day of the week, season, time of day, weather, channel and device, competitors’ prices, and much more.
The challenge is to set the optimal price in relation to time. The right price at the right time increases customer satisfaction and leads to more sales and higher profit. AI can determine the price elasticity for every item and automatically adjust prices according to the chosen product strategy.
4. Enhancing the user experience
Making your best customers feel special and welcome is one way to foster loyalty and increase revenue, but it is difficult and expensive to do and so is often reserved for only the most lucrative clients. AI technologies like computer vision and machine learning can open a scaled-down version of the experience to many more people.
If, for example, a regular supermarket shopper puts a bunch of bananas in his cart, cameras or sensors could relay the information to an AI application that would have a good idea of what the shopper likes based on previous purchases.
The app could then, via a video screen in the cart, suggest that bananas would be delicious with a chocolate fondue, which the purchase history suggests the shopper likes, and remind the shopper of where to find the right ingredients. Or a runner could download an app from an athletic shoe company, which would monitor their exercise regimen and recommend footwear tailored to their routine and running paths they may like.
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