Artificial intelligence is expected to revolutionize businesses across the globe, and those in the sharing economy are no exception. All told, there is a nearly $6 trillion in revenue opportunity from AI across the internet industry, a March report from Morgan Stanley found. The latest AI craze — generative AI — has companies across the country looking to capitalize on the trend. “Every single company faces the challenge today of deciding how to distribute its IT budgets such that it can get enough artificial intelligence to deliver improvement in costs, improvement in revenue operational value and open an avenue to transformation,” Gartner analyst Whit Andrews said. “Every single company — there is nobody who gets a pass at this point.” For companies in the sharing economy, like Uber , Lyft and DoorDash , AI is already a way of life. People call up a ride or a food order on an app and they are matched with drivers to either take them to their destination or deliver their food. Yet the impact of the technology is just beginning. “UBER/LYFT/DASH already use ML [machine learning] in their matching algorithms (matching rides/eaters with drivers/couriers),” Morgan Stanley wrote in its report. “That said, we see further improvements in fleet utilization and matching … lower wait times and pricing and higher profitability.” AI tailwind for Uber Uber has both its ride-sharing service and UberEats food delivery business. When the company reported earnings earlier this month, CEO Dara Khosrowshahi said Uber has a “significant data advantage” that allows it to employ AI solutions and is already using AI to predict “highly accurate” arrival times for rides and deliveries. Even still, it’s early innings. “We are just starting to understand the capabilities of AI and we are a long way from understanding its potential,” Khosrowshahi told CNBC after the earnings report. UBER mountain 2019-05-10 Uber’s performance since is May 10, 2019 IPO The earliest and most significant effect of AI will be on its developer productivity, the company said on its earnings call. You’ll also have more chatbots powering experiences, which saves on costs. “Then we will look to surprise and delight. ‘Pick me up at the airport. I’m arriving on American flight 260 on Tuesday,'” Khosrowshahi said. “We will know who you are, where your home is, what kind of cars you like, et cetera.” According to Morgan Stanley, AI and machine learning will be a tailwind to network efficiency. On the rider side, every 1% increase in rider frequency and 20 basis points increase in the rides take rate would lead to 1% incremental company revenue and 3% of incremental company earnings before interest, taxes, depreciation and amortization (EBITDA). On the delivery side, every 1% increase in rider frequency and 5 basis point increase in the rides take rate would lead to 0.4% incremental company revenue and 1% of incremental company EBITDA. For investor Sarat Sethi, who owns shares of Uber, the company’s use of the technology helped them become efficient and puts them ahead of the competition. “They were really on the forefront,” said Sethi, portfolio manager at Douglas C. Lane & Associates. “Now we’ve seen the results over the last few quarters, where the efficiencies are really coming through. And Uber is just understanding more and more of the customer and the more and more data they get.” Tech investor Gene Munster, partner at Deepwater Asset Management, is also bullish on Uber’s ride-sharing and UberEats business because he believes the company has persistent growth. One of the reasons he’s really excited about its AI prospects is the autonomous deliveries and transportation opportunities. He sees a move towards autonomy, although not the entire fleet, which brings the potential for higher margins. He also thinks customers will be willing to book autonomous cars if it saves them money. “Autonomy will drive down the cost per mile for the customer, which will increase use, but it should increase margin at the same time, which is pretty unique,” said Munster, whose firm owns shares of Uber. AI’s impact on the sharing economy There are several ways AI can boost ridership or food delivery orders for those in the sharing economy. More accurate natural language processing could help with search and help create better recommendations for users, Morgan Stanley said. AI will also be able to better anticipate consumer behavior. “For the Rideshare businesses, this could take the form of better allocation of supply to meet rider demand as algorithms are better able to predict where influx of demand will next occur and point drivers in that direction,” the firm said. For the delivery businesses, it could mean better suggestions or automatic orders for groceries. AI may also help in the generation of new business opportunities, particularly in delivery, Morgan Stanley’s analysts said. “Greater ability to predict customer behavior potentially minimizes the initial capital investment risk for companies looking to build their own supply and adds certainty that there will be demand for the product once created,” they said. As AI gets smarter, it can also help boost productivity and automate tasks now performed by humans. What every company in the sharing economy is trying to sort out now is why people are involved with certain tasks, Gartner’s Andrews said. “You have to be able to answer the question. You have to be able to say there are people involved with this because it demands the creativity and the originality of human perspective,” he said. “If it lacks that, it’s going to get automated. We are in the process of taking this enormous step towards that new reality.” Companies also have to continue investing in the newest technology or risk being left behind — and it’s not cheap. “The companies have tremendous opportunity to evolve their model. Now it is just about execution,” said Baird technology strategist Ted Mortonson. DoorDash’s AI experiments Like its sharing economy peer Uber, DoorDash is also hoping to optimize its operations and improve productivity with AI in the near term, said Rohit Kulkarni, senior research analyst at Roth MKM. Looking ahead, it’s about creating a better consumer experience by using generative AI, he said. “What DoorDash can do is better content discovery, which goes back to consumer experiences and how AI can put the right content in front of the right consumer at the right time,” said Kulkarni, who has a neutral rating on the stock. His $72 price target implies 10% upside from Wednesday’s close. In fact, right now DoorDash is running different experiments internally with generative AI, said Alok Gupta, the company’s head of artificial intelligence and machine learning. “One of the things we’re trying to understand with this new wave of generative AI tools is which ones are going to best serve the needs of certain features,” he said. The company is looking at the quality of the tools, like if it gives the right answers, the price, the scalability and how it impacts data privacy, security and ethics. “We’re looking at the different generative AI vendors, we’re looking at open source models that we can host internally, and then we’ll pick and choose,” Gupta said. DASH mountain 2020-12-09 DoorDash’s performance since its Dec. 9, 2020 IPO DoorDash already uses AI and machine learning to personalize the experience for consumers, help merchants achieve their sales goals by seeing which items are trending in their neighborhoods and to refine the timing of pick ups for the drivers, or dashers. Generative AI will be able to further personalize and tailor the experience for users. Customers would see menus that better match their preferences and the interaction would be more conversational, Gupta said. It will also help with internal productivity, such as digitizing menu items, where to park and store locations. While Gupta can’t quantify the financial impact for the company, he said AI will drive growth. “We strongly believe that if we improve the quality predictability of the experience of each of our audiences, that will naturally translate into better retention for audiences and how they use us, and that will help us,” he said. However, Morgan Stanley estimates that for every 1% improvement in order frequency and 5 basis points improvement in take rate results in a $149 million, or 1.4%, uplift to company revenue and an $82 million, or 5%, improvement in earnings before interest, taxes, depreciation, and amortization. “The extent to which AI drives substantial improvements in top-line growth could lead to teens upside [for the stock],” Morgan Stanley said. Lyft’s difficulties Lyft has been struggling and losing market share to Uber. The ride-sharing company debuted on the public market in 2019 at $72 a share and is now trading below $10. Over the past year, its stock has dropped nearly 58%, plagued by disappointing earnings . Earlier this month, Lyft reported an adjusted loss of 7 cents per share for the first quarter, a penny more than expected, according to Refinitiv. The company also provided guidance for second-quarter sales and EBITDA that was less than expected. However, Lyft’s new CEO, David Risher, is trying to make changes to right the ship, including layoffs and the launch of a new airport preorder feature. ‘Biggest death star’ As companies within the ridesharing economy look to invest in the latest AI and use it to become more profitable, there may be some big competitors looking to swoop in, Baird’s Mortonson said. The “cloud titans” that have massive balance sheets and free cash flow, as well as the “massive compute scale,” could decide to move into the ridesharing or food delivery business, he said. “Their biggest death star is Amazon ,” Mortonson said. Not only does the e-commerce giant have the intellectual property that centers around AWS, it also knows all about the next-generation logistics, routing and delivery, he said. “Their extension on delivery into food or … other services … they just have to turn the switch,” he said. — CNBC’s Michael Bloom contributed reporting.
