Why Boring Is Cool in the Age of AI
Randall Woods, SVP @ SBS Comms
Unlike some other tech booms, AI will transform our economy and businesses will adapt.
That’s boosting the need for “boring” tech like chips, cloud networks and database software.
Deep-tech companies need to show how their work ties into this AI boom.
Critics who question AI’s ability to transform our economy in coming years have reason to be skeptical, as many industries are often slow to adopt the latest technological advances. For example, shipping and logistics companies still rely to a large degree on paper documentation, while many general practitioners share medical records via fax.
At the risk of sounding naive, this time will be different, and the only real impediment to widespread adoption of AI will be our ability to build the technological infrastructure that can support this boom.
Unprecedented Demand
Businesses from publishers to law offices and drugmakers are scrambling to integrate AI into corporate workstreams, as they know the technology is simply too impactful for them to ignore, and there’s a risk of permanently falling behind peers that embrace the change. AI-leaning competitors will be able to uncover game changing efficiencies, and identify future trends, customer behaviors and potential challenges that will give them an edge.
The opportunity isn’t lost on developers, and they’re pushing to adapt large language models for use cases that will help industries integrate AI. Investors are standing by eager to assist. Industry insiders know that this boom will require a massive funding push – not just to finance these new use cases, but to support development of the infrastructure underpinning them.
In fact, these technologies are facing unprecedented demand, as the unexpected boom in AI is putting pressure on tools that allow AI systems to collect, organize and infer from massive amounts of data. Technologies that once appeared boring are suddenly cool – not to mention instrumental in laying the foundations for our new economy.
CTOs suddenly need to bring on tools that allow them to store and manage data in fresh ways, and adopt new network systems, monitoring and management tools, security and scaling solutions, edge infrastructure – the list goes on.
And even now in the early days of the Generative AI craze, businesses are running short on the GPUs that train large language models, and the need for cloud capacity required to run applications is expected to surge.
Infrastructure Crunch
Policy makers are taking note of this infrastructure crunch, with the Biden Administration stimulating chip development in the U.S. and mulling efforts to restrict China’s access to cloud computing. In effect, the infrastructure for AI is becoming as strategically important as the highways and railroads that support our cars and trains.
This is undoubtedly positive for businesses that create the deep tech that underpins AI, though they must know how to connect with investors and potential customers if they want to seize the moment. The technology can appear wonky and opaque, meaning these businesses need to make the case for their importance, and how they will allow customers to adopt AI. Investors are paying attention – as are policymakers and the general public – so clear messaging that cuts through the noise and presents a solid use case is key.
A lot of work remains to lay down this infrastructure, and in the chip space alone it could take years for manufacturers to catch up with demand. That will somewhat slow integration of AI, which on the plus side gives policymakers time to understand the phenomenon and potential vulnerabilities in the supply chain. The lag also will give motivated workers breathing space to understand how they can use AI to boost their productivity, reducing the odds that it will replace their jobs.
Despite these delays, AI will eventually transform our economy in ways we can and cannot anticipate. And the race is on to lay the foundation to support this new world order.