AI sales rep startups are booming. So why are VCs wary?


When you actually ask venture capitalists about investing in AI startups, they will tell you that companies are experimenting a lot but are very slow to add AI solutions to their ongoing business processes.

But there are some exceptions. And one of them appears to be a field known as AI Sales Development Representatives, or AI SDRs. These use extended language models (LLM) and voice technology to create personalized outreach emails and make automated calls to potential customers.

“In some markets, we’re seeing five to 10 companies succeed in a fairly short period of time,” Shardul Shah, partner at Index Ventures, said of the AI ​​SDR boom.

While it’s certainly not uncommon for multiple startups to target the same problem, it’s rare to see them all experience rapid growth. But that’s apparently the case for startups that automate content creation for sales teams, investors say.

“When we study one of the [these startups] individually, it’s like ‘wow, this is a perfect product-market fit,’” Shah said. “When all 10 of them have perfect product-market fit, it’s hard to answer, ‘How is this going to play out?’ »

Index has not yet invested in any of these companies, many of which are less than a year old. Even though the whole category is on fire and customers are using them, it’s still too early to know if their growth will continue in the long term or if they will be abandoned like so many other AI pilot projects once the wow effect passed, because they prove no more effective than human awareness.

Small Businesses Love AI Sales LLMs

Arjun Pillai, founder of Docket, a startup that trains sales engineers in AI, believes that the adoption of AI SDR is high because small and medium businesses can easily experiment with these tools. Prior to Docket, Pillai was chief data officer at sales lead generation platform ZoomInfo.

“Over the last two years, the response rate to cold emails has dropped by at least 50%,” Pillai said. “Now that a number of companies claim to be able to improve on this rate, everyone is ready to try their service.”

Best-known AI SDR startups include Regie.ai, AiSDR, Artisan, and 11x.ai, but incumbent ZoomInfo has also released a co-pilot which competes with these startups and other virtual sales agents.

Even though these companies are experiencing rapid revenue growth, it is unclear whether they are actually helping businesses sell more effectively.

According to Tomasz Tunguz, founder of Theory Ventures, a chief revenue officer at a publicly traded company revealed to him that while an AI SDR helped generate a substantial volume of leads over a nine-month period, it did not. leads to real sales.

“So that doesn’t mean AI won’t work. This is to say that many of us [still] I don’t know how to use AI”, Tounguz said on stage at a SaaStr conference in September.

Will the incumbents crush them?

Chris Farmer, partner and CEO at venture capital firm SignalFire, said he believes AI applied to sales and marketing is a big opportunity, but without access to differentiated data, AI SDR startups risk losing be overtaken by historical players like Salesforce, HubSpot and ZoomInfo. The main products of these companies are the guardians of their customers’ data. So if they offered bots that allowed their customers to access their own data, those bots could be more effective.

Another VC firm that has studied this market but has not yet invested said his firm looked at several AI SDR startups and they all had $1 million in ARR in less than a year. year. The startups’ impressive growth was appealing, she said, but like Farmer, she worried that their solutions could eventually be offered for free by established competitors.

Jasper, a copywriting startup that was last valued at $1.5 billion but ran into speed bumps and had to lay off 30% of its staff after the introduction of ChatGPT, constitutes a warning for some investors.

Investors are not surprised by the rapid adoption of AI SDRs; they just doubt adoption will be sticky.

Update: This story was originally published on August 22 and was updated on December 26 with comments from Tomasz Tunguz.

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