Artificial Intelligence is Ready for Business; Are Businesses Ready for AI?
AI is now seemingly everywhere. In the past few years, the necessary ingredients have come together to propel AI beyond the research labs into the marketplace: powerful, inexpensive computer technologies; advanced algorithms and models; and most important, oceans and oceans of data.
“Artificial intelligence is getting ready for business, but are businesses ready for AI?,” asks McKinsey in a recently published report - Artificial Intelligence: the Next Digital Frontier. “AI adoption outside of the tech sector is at an early, often experimental stage,” is the report’s succinct answer. “Few firms have deployed it at scale.”
The report is based on a survey of over 3,000 AI-aware C-level executives across 10 countries and 14 sectors. Only 20 percent of respondents had adopted AI at scale in a core part of their business. 40 percent were partial adopters or experimenters, while another 40 percent were essentially contemplators.
AI encompasses a broad rage of technologies and application. It’s often viewed as the leading edge of IT. As soon as AI is successfully applied to a problem, the problem is no longer a part of AI. The McKinsey report is focused on five technologies being increasingly deployed in business, that most everyone agrees are part of AI: robotics and autonomous vehicles, computer vision, language, virtual agents, and machine learning.
“AI’s dependence on a digital foundation and the fact that it often must be trained on unique data mean that there are no shortcuts for firms. Companies cannot delay advancing their digital journeys, including AI. Early adopters are already creating competitive advantages, and the gap with the laggards looks set to grow. A successful program requires firms to address many elements of a digital and analytics transformation: identify the business case, set up the right data ecosystem, build or buy appropriate AI tools, and adapt workflow processes, capabilities, and culture.”
A common theme throughout the report is that the same players who were leaders in the earlier waves of digitization and analytics are now leading in the AI wave. Early AI adopters share six common features:
- They’re close to the digital frontier. Each new generation of tech builds on the previous one, making it increasingly difficult for laggards to catch up.
- The bigger the bolder. Large companies invest faster at scale, while small and mid-sized businesses generally lag.
- They tend to adopt multiple AI technologies depending on the specific use case.
- They invest in applications close to their core business, such as customer service, operations and product development.
- They see AI-driven innovation as driving increased revenues and higher productivity rather than just cutting costs.
- They have strong executive leadership support for the new technologies and applications.
High tech, telecom, financial services and automotive and assembly are the sectors with the highest AI adoption. In the middle are less digitized sectors, including retail, media and entertainment, consumer package goods and resources and utilities. Education, health care and travel and tourism are at the bottom of the AI adoption pack.
To better understand how AI creates business value across different sectors, The report includes five fairly detailed case studies. The five chosen sectors, - retail, electric utilities, manufacturing, health care and education, - span a range of activities, from labor-intensive services to asset-heavy operations. In addition, McKinsey analyzed all the different ways in which AI creates value across these different sectors and categorized them into four main areas.
Demand forecasting, supply chain optimization, and improved product design and productivity. “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.”
In retail, for example, AI helps anticipate demand trends, so companies can order more of the soon-to-be-popular items and avoid overstocking items that aren’t likely to be in demand. In health care, analysis of public health data can help predict and prevent the spread of disease, including major epidemics. AI can help electric utilities better match supply and demand based on real time weather forecasts, as well as anticipate and get ready for the concrete impacts of hurricanes and other major weather events.
Higher productivity, lower costs and minimized maintenance and repairs. AI can help create value in production “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.” Beyond replacing humans through automation, AI can complement teams of people by embedding AI-based tools and robotics in the core of a company’s operations. One of the most important innovations in robots is their ability to work alongside humans without fear of hurting them. That means that you don’t need an expensive safety cage around the robot, making it easier to move and reprogram the robot to whatever unique processes are required to fill new orders.
In asset-heavy businesses, - e.g, jet engines, elevators, turbines, MRI machines, - AI can detect potential problems by analyzing data from sensors and scheduling preventive maintenance. Similarly AI enables the application of preventive maintenance to people, through its ability to remotely monitor individuals with serious health issues, anticipate potential problems and alert medical personnel as appropriate. In education, AI can assist teachers through virtual tutors that can track the individual progress of each student and alert the teacher as needed.
Products and services at the right price, with the right message, to the right targets. “Armed with enough of the right kind of data, 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… 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.”
Similarly, electric utilities can use dynamic pricing to better balance the supply and demand for electricity, charging more for periods of peak demand, and less when the demand is lower, thus reducing the need to add power plants to satisfy peak demands.
Enriched, personalized, and convenient user experience. “The fourth area where AI can create value is in enhancing the user experience and creating new sources of value to make it richer, more tailored, and more convenient. 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.”
In healthcare, AI can assist physicians in make personalized treatment decisions based on the sophisticated analysis of many sources of data, including the individual’s medical history, recent tests, complex biomarkers, genomic data, and the vast scientific knowledge in books and journals. In education, AI-based adaptive learning can help address the limitations of conventional classrooms by crafting custom lessons based on the knowledge and progress of each individual student.
“After decades of hopes and disappointment, AI is back and could be set to drive profound changes in the global economy…” notes the report in conclusion. “We are already seeing examples of real-life business benefits for early-adopting firms. However, adoption of AI technologies remains largely at an experimental stage. Indeed, the gap between early adopters and the rest is set to grow. While many companies have yet to be convinced of AI’s benefits, frontier firms are charging ahead. Significant gains are there for the taking. For many companies, this means accelerating the digital transformation journey. They will have to put the right digital assets and skills in place to be able to effectively deploy AI.”