Applying AI to Business: Lessons from Different Industries

Artificial intelligence has been introduced into companies around the world, with some good results and some waste of resources. At this point we can see trends that will help business leaders implement valuable efforts. The best use cases vary from industry to industry, but the commonalities are many. Businesses can benefit by looking beyond their industry or function to see what has proven useful elsewhere. Many good use cases will work in other sectors as well.

McKinsey has recently written about nine different sectors, complementing the articles I’ve written on industries and business functions. Let’s get the good ideas out of this whole working group.

AI for time-consuming tasks

A great example that McKinsey and I have both highlighted shows huge benefits that can be implemented quickly. Our specific case is AI-supported healthcare writing, but managers in other industries can also benefit from the concept. Doctors and nurses use electronic medical records to document patient visits, as well as access information such as past visits and test results. Writing visit summaries is a time-consuming and tedious task performed by highly paid workers. AI tools can listen to a conversation and prepare a summary in the appropriate format. (This works best when the doctor is used to speaking out loud about signs, such as “your lungs sound clear.”) The practitioner then reviews and modifies as needed, usually in a fraction of the time that would be necessary to write.visit summary.

Where does a company have employees spending time on tasks that an AI can do quickly? It could be sales reps recording calls, service technicians documenting tests, compliance officers checking documents. McKinsey writers argue for improving existing processes first, and then tackling major innovations. This is good advice.

In many of these use cases, employees do not enjoy the particular task. Doctors don’t like to write patient visits, but they know they have to. Good salespeople take notes because it helps, not because they like it. So a company can gain in efficiency and also employee job satisfaction.

AI to improve customer service

Help for customer service representatives spans several of McKinsey’s surveyed industries. It is a large and ubiquitous business function, which I described as “The most hanging and fattest fruit in the whole orchard.” Imagine a call to a customer service representative, with an AI-enhanced system that listens. AI can pull the customer’s history, even if the customer doesn’t know which model they own. The AI ​​can prompt the representative with questions to ask (“Did this problem arise suddenly or gradually?”). And when it’s useful, AI will pull up company policies, service manuals or troubleshooting tips. This app is especially valuable for less experienced reps.

AI for compiling information

In a number of industries, employees must gather information together from multiple sources. The McKinsey article on pharmaceuticals, for example, describes regulatory applications that rely on academic publications, databases, trial data, and patents. Generative AI is great for gathering information from various sources.

This concept can be applied in many cases. An application in a very different industry was developed by WFG National Title Company (a client of mine). Closing real estate deals requires the drafting of numerous documents, including the purchase agreement, mortgage, various disclosures and title insurance. An AI application feeds on documents. He examines and categorizes them, checking for signatures and initials. The application then routes the documents to an existing system to create the final signature packages. One study found that for a typical home sale, the names and addresses of buyers and sellers appear 80 times on various documents. The WFG chairman asks, “What are the odds that the names and addresses will be entered correctly all 80 times?” The company has found that the time devoted to closings has been cut by an average of 30 minutes. Multiply that time savings by thousands of closings per month.

The concept can also be applied to engineering designs, real estate development applications, and financial risk assessments. The AI ​​can be shown the correct format for the final product and asked to use different sources to write the document. It will have to be checked for errors by humans, but that’s easier than writing it by hand.

The energy and materials article mentions the integration of various data on physical assets (utility systems, machinery), such as sensors, past physical inspections, and automated image capture. The end result is failure prediction and maintenance planning. Thinking beyond drug approval requirements, the general concept is that AI currently works well when multiple sources of data need to be integrated into a prescription or plan.

Business Applications for AI Imaging

Large language patterns have led to image innovations, with business applications beginning to arrive. In consumer sales, one can take pictures of a living room and use AI to add a black leather couch to see how it would look in that particular space. Or a new home can be visualized with a potential buyer’s furniture. The backyard can be imagined with the maple tree that has grown 20 feet above. The view of the kitchen window may appear at 9:00 a.m. on a winter morning.

Retailers can record how customers move through a store and then visualize the paths with different screens and devices. Visualization will be increasingly used in a wide variety of applications.

AI for consumer-based businesses

McKinsey’s travel article highlighted an important fact for anyone working with consumers. “… every customer gives a story. They drop digital snippets of their likes and dislikes when they leave a dot-com site when they’re shopping; when they abandon a cart; when they return less often to search; when they arrive at a site just to check a single route on a single day, for a single fare, instead of browsing for 20 minutes.” This has enabled websites to serve ads to potential buyers, but it can also empower consumers themselves to use an app with access to all of their information – not just browsing history, but credit card statements, too. emails and calendar items – to get better shopping options.

An AI application with this information can create a vacation based on my past vacations, typical price points, loyalty programs, and calendar availability—in seconds. Although the example relates to travel destinations, it can be applied to any purchase, from clothing to cars to home furnishings.

Business leaders looking for opportunities to serve customers better, at lower costs, should browse widely through AI applications across a number of industries and business functions.

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