How Much More Efficient Should a SaaS Startup Be When Using AI?
Tomasz TunguzVenture Capitalist If you were forwarded this newsletter, and you'd like to receive it in the future, subscribe here. How Much More Efficient Should a SaaS Startup Be When Using AI?
If we assume some basic productivity gains in a typical SaaS company from AI in the next 12-24 months, how much more profitable will the business be? Sales development, content marketing, & software engineering strike me as the workstreams that will benefit immediately.
See assumptions here1 This thought experiment highlights a few ideas to validate :
This 2x2 matrix captures these ideas. Startups should focus on AI for Execs (perhaps why legal has been a heavily funded category) & AI for common workstreams (code autocompletion). There will be exceptions, especially where a user base is predominantly individual users or the willingness to pay for the software outweighs the productivity gains. A mental model like this should guide both software procurement on the buyer side & product management on the vendor side especially in an procurement environment where every software vendor must justify their cost-savings or revenue increase. 1 BDRs are often mapped to AEs at 1:1 ratio & if we assume BDRs account for 25% of sales headcount (the remainder includes AE, sales operations, post-sales, & management). Assume a 15% productivity improvement that results in a 1.5% improvement across the company. Marketing has many different disciplines of which content marketing is one. Assume content marketers represent 5% of the company & the team sees a 30%% increase in productivity, the marketing team will improve overall productivity 1.5%. Software engineering sees the greatest benefit. Comprising 40% of the company & producing 25% more output (Github says 50% of all code is now machine-generated), the startup should see a 10% overall improvement. |
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