Venture capitalists are sure they have found their next big investment advantage. This uses AI to narrow down the margins like software from traditional labor-intensive services businesses. This strategy involves acquiring mature professional services companies, automating tasks to implement AI, and rolling up more companies with improved cash flow.
The general catalyst (GC) leads the bill. This is dedicated to the latest fundraising called the “creation” strategy, which focuses on incubuted AI native software companies in a particular industry, and to those that focus on buying established companies and their customers in the same sector using the company as an acquisition vehicle. GC has bets on seven industries, ranging from legal services to IT management, and plans to fully expand to up to 20 sectors.
“Services worldwide are revenues of $16 trillion a year across the globe,” said Marc Bhargava in a recent interview with TechCrunch, which leads GC’s related efforts. “By comparison, software is only $1 trillion worldwide,” he said, adding that the appeal of software investments is always a higher margin. “As we expand our software, there is little marginal cost and a huge marginal revenue.”
If you can automate your service business too, he said – working on 30% to 50% of companies with AI, and in the case of call centers, even automating up to 70% of those core tasks, maths starts to look attractive.
The game plan appears to be working. Check out Titan MSP, one of General Catalyst’s portfolio companies. The investment company provided $74 million over two tranches to help develop AI tools for managed service providers, and later acquired RFA, a well-known IT services company. According to Balgava, through the pilot program, Titan has demonstrated that 38% of typical MSP tasks can be automated. The company is currently planning to use improved margins to obtain additional MSPs with classic rollup strategies.
Similarly, the company incubated Eudia, which focuses on the internal legal department rather than the law firm. Eudia has signed up for Fortune 100 clients, including Chevron, Southwest Airlines and Stripe, offering fixed-rate legal services powered by AI rather than traditional hourly billing. The company recently acquired Johnson Hanna, an alternative legal service provider, to expand its reach.
General Catalyst expects it to be at least twice as much.
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That way of thinking isn’t the only company in the big country. Venture company Mayfield has specifically cited $100 million in its “AI Teammate” investment for “AI Teammate” investments, including an IT consulting startup that has acquired a $5 million security consulting company, according to its founder.
“If 80% of the work is done by AI, you can get 80% to 90% gross profit,” Mayfield’s Managing Director Navin Chaddha told TechCrunch this summer. “We were able to blend a margin of 60% to 70% and generate a net profit of 20% to 30%.”
Solo Investor Elad Gil has been pursuing a similar strategy for three years, helping companies acquire mature businesses and transform their AI. “If you own an asset, you can (convert) it much faster than if you were selling software as a vendor,” Gill said in an interview with TechCrunch this spring.
However, early warning signs suggest that this whole service industry pervert may be more complicated than VCs expect. A recent survey by researchers at Stanford Social Media Lab and Betterup Labs found that 1,150 full-time employees have been surveyed across the industry. 40% of these employees are doing more work, refined, but without substance, producing more work (and headaches) because it is what researchers call “Workslop.”
This trend is hitting the organization. Employees involved in the investigation say they spend an average of nearly two hours dealing with each instance of Workslop, deciphering it first and deciding whether to send it back and whether to send it back just to fix it.
The study authors estimate that worklops have an invisible tax of $186 per person per month, based on estimates of the time spent along with their self-reported salary. “Given the estimated prevalence of workslop, for an organization of 10,000 workers, this is a decline in productivity, exceeding $9 million a year,” they wrote in a new Harvard Business Review article.
Bhargava challenges the notion that AI is exaggerated and instead argues that all of these implementation obstacles actually test the general catalytic approach. “I think it shows an opportunity that applying AI technology to these businesses is not easy,” he said. “If all Fortune 100 and all these people can bring in consulting companies, slap AI, sign a deal with Openai and transform our business, obviously our paper (our papers are a little less robust. But the reality is, changing AI and the company is really difficult.”
He pointed out that the technical refinement required in AI is necessary as the most important missing puzzle piece. “There are a variety of technologies, and it’s great at a variety,” he said. “We really need these applied AI engineers from places like rip rings and ramps, figmas and scales, who work with different models to understand the nuances, what suits what, and how to wrap them in software.” The complexity, he argued, is why Catalyst’s general strategy of combining AI professionals with industry experts makes sense.
Still, there is no denying that Workslop is threatening to undermine the core economics of strategy to some degree. Even if a holding company is created as a starting point, as the AI efficiency paper suggests, fewer people will be able to catch and correct AI generation errors when the acquired company cuts down staff. If companies maintain current staffing levels to handle additional work created by problematic AI outputs, the large margins VCs rely on may not be realized.
Perhaps these scenarios are central to VCS rollup strategies and should slow down scaling plans that potentially undermine the numbers that make these transactions attractive. But let’s face it. Slowing down most Silicon Valley investors requires one or more research.
In fact, they usually acquire companies with existing cash flow, so General Catalyst says that their “creation strategy” companies are already profitable. It is also a welcome change for the limited partners behind venture companies, banking years of losses in companies that have never reached profitability.
“As AI technology continues to improve, as far as we can see this massive investment and improvement in our models,” Bhargava said.
