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October 2023 / VIDEO

Big Data and AI: Risk and Opportunity in Infrastructure Software

Key Insights

  • As software and AI automate more processes, the volume, variety, and speed of data should increase.
  • Harnessing this flood in productive ways requires a revolution in data infrastructure.
  • These trends may bode well for some innovative data platforms.

Transcript

Hi, I’m Sam Johnson. The industry I cover—infrastructure software—is evolving rapidly, especially with the emergence of generative artificial intelligence, or AI that can create new content.

Databases are foundational building blocks of all things digital. Data management is also one of the largest markets in software, and it should grow at a strong clip in the coming years.

Here’s why.

As software automates more processes, the volume, variety, and speed of data should increase.

Harnessing this flood, and using it in productive ways, requires a revolution in data infrastructure.

Let me explain.

Think of a patient intake form or a customer purchase order. These produce consistent data that can be neatly organized in so-called relational databases—the kind that have dominated for decades.

Now think about social media, e-commerce, streaming video, or generative AI.

Here, the underlying infrastructure must accommodate an array of data types. These apps require highly flexible filing systems for storage and retrieval.

Scale is also critical. These systems handle massive amounts of data and respond quickly to a nonstop avalanche of database queries.

The cloud makes this possible by providing low-cost storage and computing power that can flex up and down as usage ebbs or flows.

What could generative AI mean for the companies I cover?

The AI revolution could help to accelerate software creation by making coders more efficient. And the technology itself could enable a new wave of applications.

More software should equal more demand for modern data management solutions.

But advanced AI could also be disruptive for companies that specialize in analyzing big data. I’m watching that closely.

I’m also spending a lot of time focusing on what the development process might look like for advanced AI. My goal is to try to identify the companies that have the potential to be the biggest players in these markets.

History shows that size matters in software.

The companies that have captured the most market share have tended to enjoy strong margins. That’s because the additional spending needed for each incremental sale is often minimal.

And the dominant player in a space is usually better positioned to enter adjacent markets.

How do I identify companies with the potential to go big?

I try to understand how developers and chief technical officers view and deploy these products.

For each company, I read a few textbooks about their core product. I can also walk down a few flights of stairs and talk to the talented professionals that run information technology at our global firm.

I go to conferences around the country, which gives me a lot of opportunities to talk to the professionals that use these data platforms. Hearing what excites them can be a very important source of insights.

Bottom Line: The AI revolution could be a tailwind for infrastructure software. I’ll try to stay ahead of the curve by seeking on-the-ground intelligence about emerging risks and opportunities.

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