A Challenge to SaaS Orthodoxy

Venture
Booking.com

Klarna, the Swedish fintech giant, is making waves by churning from industry-standard software like Salesforce and Workday in favor of building its own internal systems with AI.
After their success with AI customer support automation which manages 2/3 of their customer inquiries, Klarna is now doubling down on this strategy.
Klarna is betting AI-enabled software is the future of internal tools. The corollary : the overall cost of building internal software with AI is lower than buying off-the-shelf solutions.
What is the break-even point for this kind of financial decision?
Let’s make a hypothetical example of MongoDB :

Field
Value (rounded)
Source

Employees
7,000
LinkedIn

Sales personnel
1,250
LinkedIn

Salesforce cost per salesperson
$175/month
salesforce.com list price

All-in sales software cost per person (est.)
$600/month
Estimate

Annual spend on sales software alone
$9 million
Math

Additional spend for administration
A few million
Estimate

Total yearly expense
$12-15m
Math

Over the course of a decade, the software spend could easily exceed $100 million. With the cost of software production falling1 & the cost of data storage also decreasing,2 the break-even point for building internal software is likely lower than ever.
How good of a CRM could a software company build with a $10m annual budget & with AI? It’s the equivalent bet to funding a startup with a $20-30m Series A & a big design partner.
Technology is always commoditizing itself. Perhaps bespoke software will have the same impact in sales as in customer support. That would provide Klarna a sustainable competitive advantage over time.
It’s also a forcing function to require the organization to rethink their workflows in the age of AI. More than just changing software, burning the boats & forcing a company to reimagine workflows with a blank slate can be a powerful way to drive innovation.
However, this approach isn’t without risks. Building and maintaining complex systems requires significant engineering talent and ongoing investment. Many companies have built internal systems only to eventually buy commercial offerings later after incurring significant expense.
If Klarna succeeds, the market for enterprise software could be upended with a fundamentally different architecture : data lake -> AI -> bespoke software.
Audio Version

1 Microsoft and ServiceNow have both reported 50-70% increases in software productivity as a result of AI. Amazon saved $700m in refactoring code with AI.
2 The major clouds have cut all data egress fees and the migration of data storage to standard formats like Iceberg on S3 plus the cost reductions of data sets create a deflationary environment for data costs. Not to mention anything about the scale discounts afforded to the largest users of cloud infrastructure.

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