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Don’t Call it a Come Back
Financial analysts have long turned their noses up at professional services revenue.
It’s (usually) one time
It’s (often) sold at cost or heavily discounted
It’s (reluctantly) purchased by the customer who wishes this damn thing would just work out of the box
Professional Services are a necessary evil.
I spoke to Jeff Cooper, CFO of Guidewire, one of the most valuable vertical software companies. They serve the insurance industry, and are trading at more than 10x forward revenues. They successfully incorporate professional services into their offering.
He explained how it’s a tightrope walk, where you need to ensure your customers are successful, especially when there's a CIO betting their career on the outcome of an implementation, while also thinking about the long-term durability of your revenue.
“These programs are super complicated, and literally the landscape is littered with failed core system modernization projects. And one of the things that has differentiated Guidewire over the years is this commitment to “no customer left behind: 100% success on successful projects.” We don't have 100% success, but we have bar none the best track record in the industry, and that was critical to building our momentum and building our market leadership position. So services for us are highly strategic.”
While Cooper's insights focus on traditional software implementations, there's a clear parallel to be drawn within the AI space, where professional tuning will be required to realize better efficiency.
Similar to how you have an implementation specialist configure your NetSuite or Workday integration, you’ll need an AI specialist to configure your LLMs.
Remember - these models can get extremely costly if you don’t set them up right…
Cloud and Compute Costs
Data Storage and Management
Energy
And not to mention the people who run them.
You can already tell there will be a plethora of AI integrations that result in organizational concussions.
Unlike traditional one-time software integrations, AI implementations require continuous recalibration. As models evolve, their performance can degrade, making regular adjustments necessary. This recurring need for services to optimize models could blend into more predictable, maintenance-like revenue streams.
(Sound familiar to a largely extinct era of software sales?)
And metrics to track how much revenue comes from one-off services vs. recurring value vs re-ocurring calibration will be crucial for understanding the sustainability of revenue streams, and therefore valuations.
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