The Resilient Entrepreneur, Edition #130
Hi there
I hope you had a great week!
Here are the topics in today's edition:
- Should You Set AI Targets for Your Company?
- A New Way to Realize Deep Sell for Enterprise SaaS
Please reach out with comments, questions, or suggestions for articles!
Talk soon,
Tom
TACTICS FOR RESILIENT ENTREPRENEURS
Should You Set AI Targets for Your Company?
AI is possibly as transformative as electrification in the 1880s. In contrast to AI, I doubt leaders set electricity consumption targets.
Every year, a good friend of mine who works in big tech and I spend a weekend hiking in the mountains. And during the hikes, we constantly talk about tech. Two engineers set loose, one working in big tech, the other running his own B2B SaaS company.
This year, we mainly talked about Artificial Intelligence. But despite all the hype you might see online, we talked about the leadership aspects of AI. More specifically, about the sense and nonsense of setting AI targets in your company.
The Setting
My friend in big tech enjoys a generous token budget of a few hundred dollars per day and employee.
At Yonder, the B2B SaaS company I co-founded, there isn’t a token budget; we tightly manage AI costs. I’m convinced token costs will explode in the near future. Therefore, I don’t want to make the entire company too dependent on large token budgets.
Even my friend in big tech says daily token budgets are a stupid idea. Some people don’t use them at all, while other people spend half their time building AI tools just for the sake of it.
Why Do You Need AI Targets?
Here are two questions: First, why do you need AI targets at all? And second, is a daily token budget the right metric for AI targets?
It’s quite simple. You need the AI targets to make sure even the traditionalists and backwoods people in your team start exploring AI. Here is the classic normal distribution of your team’s AI eagerness:
- 5% of your team use AI even for tasks that could be done more efficiently without AI. These people are geeks, and they need clear leadership guidelines on what to do with AI and what not. They see the AI targets you set as a baseline, not a ceiling to aim for.
- 90% of your team have already found some tangible AI use cases for their field of activity. Those people could happily do without AI targets. They just do with AI what is sensible, without the pressure exerted by AI targets.
- The last 5% on your team are laggards, and they need a push to adapt to the world of AI. With all the healthy scepticism against AI, it’s impossible to claim that you cannot find an AI use case for your field of activity when you’re working in tech in 2026. This small group of people is the reason AI targets exist for your entire company.
Disillusionment. You’re bothering your entire team with AI targets when only 5% of your team need clear guidance.
And because AI euphoria is still stronger than AI scepticism, companies dole out ample token budgets and shout “adopt AI in every process and team of the organization!”
You could do much better (and much more cheaply) if you focused on your leadership role with the 5% geeks and the 5% laggards in your team. The remaining 90% could then just do their work as they already do it today – involving AI wherever it makes sense.
Conclusion: AI Needs an ROI
AI is just a tool. It’s a very powerful tool, possibly as transformative as the electrification of industry 150 years ago.
I wasn’t around in the 1880s, but I doubt leaders set electricity consumption targets, as electricity was scarce and expensive in the beginning. Rather, leaders looked at electrification as an investment in tomorrow’s productivity.
And that’s how we should look at AI targets today: AI needs to have a return-on-investment (ROI) and make us more productive in the future.
Not more, and not less.
STRATEGIES FOR RESILIENT ENTREPRENEURS
A New Way to Realize Deep Sell for Enterprise SaaS
Selling SaaS means no longer just demonstrating exciting features. Non-functional features have gained importance. And you can make money from them.
Despite the era of AI, SaaS is not dead. Customers still pay SaaS companies to fix bugs, upgrade components, apply security patches, and restore their data at 2 am when disaster strikes.
And SaaS product managers still spend lots of time talking to customers about new features, feature improvements, and edge cases. There is nothing wrong with that; that’s also what we do at Yonder, the SaaS company I co-founded.
However, product managers should keep one more thing in mind. In RFPs, there is usually a section called “non-functional requirements”, and that section has grown in length over the last few years. And even customers who procure directly often ask for non-functional requirements after the initial sale. During the initial sale, those non-functional requirements are often overlooked, because it’s hard to demonstrate them in sales demos, and because they are usually less visible than functional requirements.
But they are getting ever more important. And there is money to be made from them.
Let’s look into some real-life examples.
Customers pay for IT security features
It’s no secret that the internet has become a dangerous place, and that enterprise customers want to protect themselves. Yet they still buy SaaS tools, well aware that the underlying IT infrastructure of all those SaaS providers is not fully under their control.
5–10 years ago, it was enough to send through your ISO 27001 certificate, and IT security would shut up. No longer so. Nowadays, IT security departments ask for SIEM integration, IP whitelisting, and user provisioning/deprovisioning via SCIM.
None of these requirements is super-exciting. The exciting thing about those requirements is that enterprise customers are willing to pay good money for such requirements.
Customers pay for data sovereignty
Geopolitics is usually bad for a company doing business worldwide, but in one respect it’s a helper: Data sovereignty has come back into fashion. Not the old way, when people stacked servers in basements and under the boss’s table, but rather a way in which SaaS providers are asked to store customer data in a certain country.
Although this carries some overhead in IT infrastructure, thanks to orchestration tools like Kubernetes, this is even doable for an SME. And it’s not just doable, it’s also monetizable.
Customers pay for interfaces
Connectivity to other SaaS and AI tools is common nowadays. However, there are still a multitude of legacy IT tools in enterprise organizations: custom backup services, internal business intelligence tools, and the like.
If you can build those custom interfaces for your customers, you can tap yet another revenue stream.
Conclusion
I’m not saying that functional requirements don’t matter for SaaS companies. But if you’re selling to enterprise customers, you can make additional money with non-functional requirements.
Of course, you need a team to build those non-functional requirements in a secure and scalable way. However, you need a different attitude towards sales and product management: On top of the “regular” product and sales teams who demonstrate and design features, you need a technical sales team.
About Me
I’m a tech entrepreneur, active reserve officer, and father of three — writing about entrepreneurship, leadership, and crisis management from hard-won experience. No AI, no fluff, no promos. Just plain-text insights for people building and leading under pressure.
When I’m not solving problems, I find clarity in the mountains around Zermatt.
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