Artificial intelligence and machine learning requires huge amounts of processing capacity and data storage, making the cloud the preferred option. That raises the specter of a few cloud giants dominating AI applications and platforms. Could the tech giants take control of the AI narrative and reduce choices for enterprises?
Not necessarily, but with some caveats, AI experts emphasize. But the large cloud providers are definitely in a position to control the AI narrative from several perspectives.
There's more to AI than cloud. The complexity and diversity of AI applications go well beyond the cloud environments where they are run -- and therefore reduce the dominance of a few cloud giants.
Certainly, "AI will require more capacity in storage, of the information flow," says Bughin. At the same time, "cloud is only one part of the total pie of the platform. It's part of infrastructure, but the platform layer is what you develop in house and through a third party. This integration is going to be hybrid, even more important than the cloud itself. Let's be very clear, it's not about operation, it's a lot of algorithms, it's a lot of different data, that integration piece, that will require system integration, architecture and design. That means that different types of firms will be involved in that work."
What Bughin worries about more is the innovation potential from AI startups that may be squashed by larger players gobbling up smaller companies and startups through mergers and acquisitions. "Companies like the big internet or AI guys are going and buying a lot of very small and very clever AI firms."
At the same time, Sadun points out that smaller companies may be in a better position to leverage AI innovations -- but need help with training and education to prepare them. "This issue of who benefits from AI is really important," she says. "On the one hand, we might think the smaller firms may be able to use these technologies more effectively, because they are more nimble, more agile. Companies that have already digital can exploit and scale AI."
Where the large cloud providers may also make their dominance felt is in the monopolization of the data that feeds AI systems, says Acemoglu. Cloud architecture itself can be based on price-sensitive and competitive cloud services, he explains. "But the cloud architecture will not enable you to exploit data. The area, where I worry about the future of AI technologies are those that enable firms to monopolize data. That's where firms have an oversized effect on the future direction of technology. That means a few people in a boardroom are going to determine where a technology's going to go. We want more people focused and people-centric AI. That's not going to be possible if a few firms that have a different business model dominate the future of technology. "
The value of an AI-driven enterprise "does not reside in the cloud that enables it," Bughin believes. "I think there's enough of competition for the price point not to destroy the value. The value will come from the fact that you have integrated these technologies where you work, and the way your company works, in your own back end. The back end is not going to be the battlefield. The value is from generating productivity and revenue, at a rate faster than what we've seen in traditional digital transformations."
And, for the first time, we see the terms traditional and digital transformation used together in the same sentence. As these thought leaders relate, such transformations are moving to the next phase, enabling autonomous, software-driven operations and innovation through AI. It's a question of whether large tech vendors control the momentum, or if it remains a market and practice with a diversity of choices. Stay tuned.