Online shopping, enterprise software and video gaming all have the potential to be disrupted by generative AI.
Since generative artificial intelligence stormed onto the tech scene just a year ago, its ability to take droves of information and churn out text, speech, videos, images and complex computer code with human-like fluency has sparked questions about the remarkable technology’s potential for disruption and opportunity.
This potential spans industries and economies. For example, the evolution of AI tools could deliver a $6 trillion opportunity across advertising, e-commerce, travel, the shared economy and the cloud, based on their ability to digitize untapped offline spending. On a macroeconomic level, Morgan Stanley Research expects that more than 40% of occupations, with associated labor costs of $4.1 trillion in the U.S. alone, will be affected by generative AI in the next three years.
Analysts in technology, media and telecom have been closely monitoring trends and insights to glean the near- and long-term impacts of generative AI across the sector. Here are some key trends for investors to watch.
AI as a Personal Shopper
U.S. consumers are stepping up their use of generative-AI powered chatbots, according to the results of a recent Morgan Stanley survey. Most important, in terms of e-commerce monetization, they are using generative-AI tools to shop and to compare prices. “We think these early applications could lead to more durable growth in online ad revenue for leading search and social platforms,” says U.S. Internet Analyst Brian Nowak. “Incremental growth will be important as we head into 2024, but it is encouraging that some industry experts already speak to mid-to-high single digit conversion lifts on social media from incorporating generative AI and a double-digit lift on search.” This trend is still in its infancy, as use of generative AI has been highest among users aged 16 to 34 and is mainly for research or educational purposes, according to the survey of roughly 2,000 U.S. consumers aged 16 and older. To broaden adoption, generative AI will need to have more utility beyond shopping and research to appeal to a wider range of consumers, Nowak says.
Embedding AI in Enterprise Software
Companies across industries are exploring how generative AI can make them more efficient and more productive—and what sorts of reskilling investments they will need to help their workforce use the tools effectively. “Beyond how consumers may use the technology, we think generative AI’s foundational opportunity lies in how enterprise software can be leveraged to expand and automate work,” says Keith Weiss, Head of Morgan Stanley’s U.S. Software Team. “As such, we think adoption of generative AI could drive an additional $150 billion in revenue opportunity for software companies in the next three years.”
Current generative AI innovations, such as large language models, are most likely to have an impact on jobs that involve retrieving and distributing information—for example, billing clerks, proofreaders and switchboard operators. As generative AI applications become more focused and sophisticated over the next few years, more specialized roles, such as operations management or registered nurses, could be affected. For investors looking for generative-AI alpha in the enterprise software space, Weiss urges patience. “With long expected adoption timelines, legal and regulatory considerations, and data protection, among other hurdles, we think generative AI remains in the early stages of opportunity.”
AI Disruptions in Gaming
Building video games involves many different disciplines, including software development, creative work and writing, that could become more automated with AI. That puts the video game industry in a unique position for transformation–particularly because consumers globally are on track to spend roughly $300 billion on mobile, personal computer and console video games in 2023, and the video-gaming industry is expected to reinvest a third of that revenue. The combination of that investment and AI-driven efficiency could result in more complex and ambitious product offerings, potentially boosting engagement and in-game spending.
“Automation from AI could help, say, best-of-genre AAA publishers build and operate bigger and better titles more quickly and up to 15% cheaper,” says Matt Cost, an analyst with the U.S. Internet team. “But AI will also lower the barrier to entry for competition, which will ultimately put pressure on incumbents to differentiate.” Small game publishers may be most challenged by AI, with minimal expected gains in efficiency and significant opportunity for new entrants. Meanwhile, the platforms that consumers use to play games are less exposed to potential AI efficiencies but should be more insulated from downside risks: “Many of these game platforms are likely to be key gatekeepers that put AI tools into their customers’ hands. This makes them well positioned to benefit from adoption of AI tools in the industry,” Cost says.
