Is AI killing user-based pricing? // TECHtonic Podcast

In a recent episode of TECHtonic, I had the opportunity to join host Thomas Lah for a deep dive into the transformative shifts shaping B2B software pricing in today’s AI-driven world. Drawing on the metaphor of ice melting into water, we explored how companies are navigating the murky transition from clear costs to ambiguous value. Our conversation touched on the escalating expenses of foundation models, the financial hurdles facing CFOs, and the balancing act CEOs are performing to manage AI infrastructure investments while safeguarding short-term margins. I shared practical strategies for avoiding common pitfalls and emphasized leveraging familiar pricing metrics to sustain trust and transparency.

Key topics we covered in this episode:

• Is user-based pricing dying?
• Should we all switch to outcome-based pricing metrics?
• Can AI be used for dynamically pricing our software?

Timestamped Outline

05:09 Navigating growth challenges with new customer segments.

07:58 Researching pricing strategies for technology services, AI.

11:52 AI used as scapegoat for declining revenue.

19:12 Microsoft AI Copilot for Office pricing.

20:36 Outcome-based pricing.

26:02 AI for enterprise customer support.

26:59 Exploring AI pricing strategies: inclusion or enhancement?

31:13 B2B software AI integration unclear value proposition.

35:02 Per-user pricing models face evolving pressures.

39:07 Reevaluate pricing metrics to align with value.

44:16 Friction from complex pricing structures.

45:40 Evolving B2B software pricing models using AI.

50:25 B2B software pricing models will evolve significantly.

Potent Quotables

AI as a Scapegoat:

“AI, I think, has become a little bit of a scapegoat for a lot of these user-based companies to say, look what AI is doing to us.”
— Dan Balcauski

The Importance of Pricing Metrics:

“For a lot of companies, it may be time for them to have a serious view of what the appropriate price metric is, given the value that they have.”
— Dan Balcauski

AI in Customer Support:

“I think some of the most successful enterprise use cases are in the customer support case because it’s already structured in a way like, if most companies will have level 1, level 2, level 3 support escalation paths, level 1 is pretty much your brand new support rep, probably offshore, paid very little just to answer questions that have been answered a bunch of times with the person who’s too lazy to to search the knowledge base, for 10 seconds. And so AI is super good at deflecting all those questions.”
— Dan Balcauski

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