Investors need to look beyond the hype of generative artificial intelligence (AI) to identify the companies with the right pricing strategy to profit from the technology.
As commercial uses of generative AI start to emerge and spending on AI-related software, services and infrastructure is expected to surge in the coming years, the path to profitably monetising the technology remains unclear.
In general, James Tierney Jr, chief investment officer for concentrated US growth at AB, believes companies can make money from generative AI in several ways.
“Users of the technology can find ways to improve productivity with AI. Providers of the technology to those users – the ‘platforms’ – will profit if they can achieve favourable price points,” he said. “And ‘picks and shovels’ suppliers sell the underlying hardware needed to run the technology. These paths to monetisation are intricately linked.”
How the technology is priced as it develops is a key factor for investors to consider, added Michael Walker, portfolio manager and senior research analyst for concentrated growth at AB.
“With a roadmap of monetisation strategies at hand, investors will be better equipped to separate companies that are proficient at puffery from those poised to generate AI-driven profits that can support investment returns.”
Being productive
While the performance year-to-date of Nvidia, which makes graphics processing units (GPUs), reflects the market’s view of ‘picks and shovels’ players, there is less clarity about how to identify winning strategies among platforms.
The key here, believes AB, is to turn productivity gains into profits. “Some companies have predicted that AI could unlock productivity improvements of 20% to 30%,” Tierney said.
A popular approach is to focus on helping companies across all sectors increase output with the same employee base. An obvious way for AI to achieve this is to perform many menial, time-consuming tasks, in turn freeing up professionals to add more value for employers.
At the same time, the value proposition in delivering productivity gains will depend on the cost of the technology.
“As a result, at this stage of the technology’s evolution, many investors are concentrating their attention on how AI vendors will price the technology,” added Walker.
For AI platforms, he believes finding the right price point is partly dictated by the cost of computing infrastructure. Yet AI-enabling technology is very expensive amid the limited supply of critical infrastructure such as GPUs. “AI vendors must balance their customers’ productivity expectations against their own cost of servicing them.”
Different pricing strategies
Despite the early stage of commercialisation of AI, Tierney pinpoints three key pricing strategies that can help investors assess whether different types of companies are on track to profit from the technology.
The first is subscriptions. Companies that can integrate AI features to enhance existing products will have instant access to a potentially lucrative customer base, he explained.
Another option is an ‘a la carte’ strategy. AB believes that as the number of companies adopting AI technologies grows, so will demand for computing infrastructure to run AI queries, with many likely to choose to leverage the native AI platforms of cloud vendors such as Amazon, Google and Microsoft.
“Because their usage may be sporadic, and because AI infrastructure costs so much, the cloud vendors will likely charge them on an a la carte model” added Tierney.
A third approach is pricing AI as a ‘feature’. This would apply to those AI providers which integrate AI capabilities into products to enhance their value but without initially charging for this. “Eventually, the company might impose across-the-board price increases, justified by the value that has been added,” explained Walker.
Where companies are less likely to create meaningful profits via AI as a new source of revenue, however, is via consumer-facing chatbots.
This is due to the fact that basic query-and-response engines such as ChatGPT and Google’s Bard are already becoming commoditised. Adding value for consumers will therefore be challenging, said Walker, explaining that such products will more likely serve targeted ads as an add-on within vendors’ ecosystems.
