Noticed your credit card creeping up?

Let’s talk about the elephant in the room: the cost of becoming AI-native.

Businesses need to stay profitable AND relevant in the AI era. That’s a double challenge–an exciting one, but still a cost center.

A simple way to frame the cost side:

» There’s a new category of spend: AI tools.

» A 10% learning-time allocation per employee may be too low.

You can’t become AI-native without AI tools. Some are on subscriptions, some on credit-based usage, many are hybrid. But the real investment isn’t the tools–it’s the time and capability building.

Should work time be spent learning AI tools and practices?

IMO–yes. Implementations should benefit the business directly, and there’s no better way to learn than doing: using LLMs and assistants, building automations, and shipping agentic workflows.

THE NEW COSTS (order-of-magnitude)

€1,000-2,000€ per employee / year in AI tools

~€10,000 per employee / year more in learning time*

*If investing 20% instead of 10. Varies by role, salary levels, and current AI skill level.

In other words, you may be doubling down on software and learning investments—at a minimum.

Why It’s Worth It

This investment is non-negotiable to stay competitive. The payoff: enormous time savings in the long run, better UX/CX/EX, and ultimately, revenue lift.

Example from my credit card bills:

2023: Miro, Slack, Figma, Dropbox, Audible, LinkedIn, Spotify

2025-2026, also: Suno, V0, Notion AI, ChatGPT, OpenAI API, N8N. Also Cursor now added to the list. AI fewer taking over 🤒

hashtag#AI hashtag#AINative