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As IT leaders weigh the risks and benefits of generative AI tools, the next wave of products incorporating this technology is already gaining traction.
According to a recent report from Productboard, 9 out of 10 venture capital-backed companies plan to implement generative AI in their products, and nearly two-thirds expect to do so by the end of the year. I am aiming.
The product management platform company, which introduced its own new AI solution on Thursday, surveyed more than 300 CEOs, founders, product and technical heads of venture-backed technology companies in April and May.
The report found that efforts are underway to bring features to market quickly. One in 10 of his respondents said their company had already implemented a generative AI product, and 19% said they were planning to release a new tool this quarter.
VC funding is in AI/ML startups, according to a May report from Bessemer Venture Partners. Nearly all of the company’s 60 partners said they are prioritizing investments in AI and ML technology companies.
Some of the innovation has come from companies that were active in the space before its recent boom, Ilya Fushman, a partner at VC firm Kleiner Perkins and former head of product at Dropbox, told CIO Dive. rice field.
“Our portfolio includes AI companies that we backed four or five years ago,” Huschman said, referring to Glean, an enterprise search startup that has been backed by Kleiner Perkins since its founding in 2019. . Glean introduced a generative AI search feature in April, similar to his ChatGPT interface earlier this month that added functionality.
Fushman said his company is primarily focused on companies using AI to improve existing products, but also evaluates companies that are in a position to provide the GPU processing infrastructure needed to support training models. said it does.
The industrial sector is also ripe for innovation, Huschman said.
Large markets in traditional sectors such as transportation, supply chain, healthcare, and financial services offer opportunities for AI solutions that provide better data insights and improve existing processes.
“If you have an existing business with great unit economics and you can leverage AI to make it even better, that’s a clear advantage,” says Fushman.
The report found that most of the companies surveyed (9 out of 10) assign engineers and product developers to generative AI projects. Just over half of those companies are redeploying existing team members to AI projects, and 3 in 10 plan to hire new talent.
The first wave of enterprise use cases came via hyperscalers. Microsoft, Google Cloud, and AWS had the infrastructure and talent to rapidly deliver generative AI through accessible APIs.
Leading enterprise software and service providers who partnered with hyperscalers such as Salesforce, Snowflake and Stack Overflow soon followed.
Several providers also support generative AI projects through accelerators and funds. Salesforce Ventures doubled its initial $250 million generative AI fund to his $500 million earlier this month. AWS has doubled the size of its generative AI startup accelerator cohort, reaching a total of 21 startups.
New enterprise capabilities emerge as access to open source and proprietary models expands.
“Everybody is doing hackathons with ChatGPT to see how they can implement this technology internally,” says Fushman. “They are trying to integrate AI and are keeping the wallet open to AI.”
