How Much More Efficient Should a SaaS Startup Be When Using AI?
an old manual cash register spitting out cash from its drawer pencil sketch via Midjourney

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.

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See assumptions below

This thought experiment highlights a few ideas to validate :

  1. AI initiatives focused on cost-reduction should start with engineering. AI’s contribution to engineering productivity is 5x+ greater than other teams because of the scale of the gain & the company’s team composition.
  2. A quantum leap of productivity in less common workstreams doesn’t materially change the financial profile of the company (though it may for the department). Workstreams within SaaS companies are specialized : content marketing, a valuable GTM strategy for many businesses, represents a low-single digit percentage of the employee population.
  3. AI startups building next-generation offerings should prioritize common workflows shared across a significant fraction of the employee population or workflows for highly paid employees.

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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.

Aicha Laamouri

Project Consultant // ReONA Project Manager

1 年

This is a good demonstration of how much SaaS companies benefit from AI and how this affects productivity of each team! Thank you.?

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Hermain G.

Creative Content Writer with Marketing and Entrepreneurial Skills

1 年

It's difficult to estimate the exact amount of profit, but AI can optimize operations, reduce costs, and enhance customer experience, leading to significant growth and competitiveness in the industry. Exciting times ahead!

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?? Victor Adefuye

Founder & CEO at Dana Consulting | Pioneering Superintelligent Sales | AI-Powered B2B Sales Transformation | Author of the Superintelligent Sales Blog

1 年

Increased productivity of BDRs and marketing, because they are the leading edge of sales, will have downstream effects throughout the organization that may produce more than 1.5% efficiency gains across the company. More leads produce more opportunities, then more deals, then more customers to service and upsell. Of course, this assumes increased content marketing productivity = more leads, but let’s grant that for the sake of argument.

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Shaahed Ahmadian

Business Thinker | Researcher

1 年

Thanks very much Tomasz. I'm gradually gaining a systematic view from reading your posts.

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