Editor’s note: In 2023, Crunchbase News interviewed active startup investors in artificial intelligence. Below, we publish highlights from those interviews. Read the full interviews with General Catalyst, Bessemer Venture Partners, Accel, Insight Partners, Index Ventures, Sequoia Capital, Section 32, M12 and Sapphire Ventures.

Over the past year, we’ve chatted with more than a half-dozen leading investors about the AI space and where they are focusing their efforts.

For many, the foundation-level models — unless you are an early investor — are challenging for venture funding due to the vast sums of capital required. That’s because it costs billions of dollars to develop foundation models.

But the tools required to manage these models and data are garnering investor interest. And the application-layer software applying these models for consumers and businesses is a use case that will play out over the next decade.

Repeatedly, what we heard from investors is that the immediate and massive adoption by consumers of AI tools like ChatGPT and image-generation models in the past year was a critical off-to-the-races moment for this industry.

‘Attention is all you need’

We’ve now had four or five eras of artificial intelligence, Jai Das, president at Sapphire Ventures, told us recently. This latest is undoubtedly the generative AI era, he said: “We are just in the first innings of what generative AI can do.”

“ChatGPT is a meaningful step forward,” Deep Nishar, a managing director at venture capital firm General Catalyst, told us in our far-ranging conversation earlier this year.

More important than the technology, he said, “it has fired up the imaginations of nontechnical people. It’s probably the fastest thing that ever got 100 million users using it all at once.”

For Erin Price-Wright, a partner at Index Ventures, the technology was not a surprise — it’s been around for a few years — but she was surprised at how quickly ChatGPT took off, and then made its way into the boardroom. Index Ventures is an investor in Cohere, one of the foundation model companies that found the market flung wide open up after the launch of ChatGPT.

Meanwhile, from the corporate side, Microsoft had first invested in ChatGPT developer OpenAI in 2019.

“We were already looking for uses of generative AI before the whole thing exploded,” Michael Stewart, a partner at M12, the software giant’s venture fund, told us.

The moment that drove home the value of this technology for Stewart was not the public launch of OpenAI’s GPT 3.5 just over a year ago. It was earlier in 2022, when Jasper connected the power of GPT-3, a prior version, in a highly automated marketing tech platform that got marketers very excited.

The current technology evolution is driven by the continued evolution in AI models, Andy Harrison, a partner at  Section 32, told us in our conversation earlier this year. “The storage and processing power has been getting cheaper,” he said. “The models get better, the chipsets and the processing power get cheaper, and then the storage gets cheaper. That’s created a flywheel here that’s allowed these massively trained LLMs that have caught everyone’s imagination.”

However, “in the end the stuff is just software,” he said.

Adoption cycles

The “adoption curve on this one will be mind-blowingly fast,” Sameer Dholakia, a partner at Bessemer Venture Partners, told us — predicting that AI will be easier to adopt than previous platform shifts like mobile and cloud computing. “This time it’s an API call to a large language model.”

Stephanie Zhan, a partner at Sequoia Capital, spoke about the firm’s strategy to follow developers and talent.

The firm has seen more AI companies forming, she said. “We’ve seen the rise in early-stage AI investing — most notably, pre-seed and seed-stage AI companies that we’re actively investing in right now.”

Price-Wright, who previously worked at Palantir and partnered with organizations to manage and understand their data, said the opportunity has expanded to incorporating AI.

“There’s this similar challenge over the next decade of how existing enterprises with large data sets and large customer bases and complex operations start to incorporate AI to make their products better, to make their operations more efficient, to make them more streamlined, to make them faster and more nimble at decision-making,” she said.

“How effectively organizations are able to really leverage data and decision-making; I think we’re still in that transition,” she added.

George Mathew from New York-based investment firm Insight Partners told us the firm is seeking out “companies that are building domain-specific models on top of private data sets with great user experiences and workflows.”

Harrison of Section 32 noted that “it’s expensive software because of the compute and because of the talent required. So it has to be that much better. Or it has to do something we couldn’t previously do with software in order to drive high margins. Otherwise it’s low-margin software.”

He predicts the GPU crunch will alleviate itself in the next 12 to 18 months and the costs of the models will come down.

Daniel Levine, a partner at Accel, predicted that AI will have a dramatic impact on many existing companies. “You’ll see new companies for which AI makes the difference between the product being so-so and potentially [being] a game changer in its category,” he said.

He predicted: “You’ll see a lot of companies that in hindsight will look like they’ve replaced existing software players.”

Related Crunchbase Pro queries

• General Catalyst’s AI Portfolio Companies
• Bessemer Venture Partners’ AI Portfolio Companies
• Accel’s AI Portfolio Companies
• Insight Partners AI Portfolio
• Index Ventures AI Portfolio Companies
• Sequoia Capital AI Portfolio Companies
• Section 32 AI Portfolio Companies
• Microsoft’s M12 AI Portfolio Companies
• Sapphire Ventures’ AI Portfolio Companies

Illustration: Dom Guzman