From Free to Paid: Choosing the Right AI Model (with a European Lens)

Building on Ethan Mollick’s “Opinionated Guide to Using AI Right Now”

Every few months, Ethan Mollick updates his Opinionated Guide to Using AI Right Now. His latest version (October 2025) is, in my view, the clearest overview of what the major AI models can do and when it’s worth paying for them.

This article builds on his work. I’m not trying to improve it, but to translate it for a European context and for people who often ask me:

“Rob, I use AI daily. When should I start paying, and for what?”

At Schmuki, our small digital-AI agency, we work with all three leading paid systems, ChatGPT, Claude, and Gemini, each for different reasons.
What follows is both a reflection and a field note: how we use them, what we’ve learned, and what might help others choose wisely.

Quick takeaways

• Free models are fine for experimentation, learning, or light creative work.
• Paid tiers (€20–€25 per month) unlock reliability, integrations, and privacy control.
• Three ecosystems dominate: OpenAI (ChatGPT), Anthropic (Claude), and Google (Gemini).
• Europe adds nuance: pricing, privacy, data access, and multilingual use differ.
• Your choice depends not only on capability but on context: personal or business.

Why upgrade

Free AI gives you access; paid AI gives you agency. Upgrading unlocks:

• access to “thinking” or “agentic” models that plan, search, and reason in steps;
• longer context windows for sustained work;
• file uploads, code execution, and voice interaction;
• privacy settings that let you exclude your data from future training;
• team features for shared workspaces and centralised billing.

For many professionals, that alone justifies the cost: fewer errors, more continuity, and tools that fit organisational routines.

The big three: a comparative snapshot

(Grok by xAI exists but remains peripheral in professional European use — see note below.)

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A note on Grok

I’ve never used Grok seriously. It sits inside the X ecosystem and doesn’t yet connect with the tools we depend on. Perhaps it’s about product safety or about trust, but more likely it simply hasn’t offered a reason to explore.

Omissions are instructive: what we don’t use often says as much about our digital ecosystems as what we do.

How we work with them at Schmuki

At Schmuki, we maintain paid plans for all three systems. Each serves a distinct role.

ChatGPT Team is our main environment.
It doesn’t integrate with Google Workspace in a technical sense, but it coexists comfortably with it. The two can share files and links easily, and ChatGPT understands Google formats well enough to make handovers smooth.
We also appreciate the practical side: a single annual invoice in euros and clear administrative handling.

It’s where most of our writing, planning, and prototyping happens.

Claude is Maya’s preferred workspace for editorial and conceptual writing.
Its composure and linguistic precision make it ideal for sensitive or multilingual texts.

Gemini has two faces:

• as an app, for quick, visual prompts or camera-based interactions;
• as an embedded co-pilot, inside Drive, Docs, and Gmail, which we use for internal briefs and summarising materials.

But the Google heritage is a double-edged sword.

The same deep integration that makes Gemini convenient can also make it feel heavy: it tries to be everything at once, and not everything works as you expect.
That friction sometimes breaks the flow that good AI work depends on.

The result, nonetheless, is complementarity rather than redundancy. Each model contributes something distinct and together they mirror the variety of our work: strategic, creative, operational.

A European perspective

Europe adds a few pragmatic twists to Mollick’s global overview:

These subtleties shape the feel of using AI here, less about novelty, more about fit, trust, and compliance.

Personal or business?

Upgrading is not only about price; it’s about ownership of process.
For personal use, one subscription may suffice and ChatGPT Plus or Gemini Advanced will cover nearly everything.

For business, the equation changes:

• Shared memory and projects enable continuity across a team.
• Unified billing simplifies administration and auditing.
• Data-handling assurances become part of compliance.

The move from free to paid is, in that sense, a move from play to practice.

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Closing reflection

Mollick is right: the future of AI will depend less on faster models than on how people learn to use them well. In Europe, that means balancing curiosity with caution and exploring new capabilities while guarding privacy, language, and autonomy.

Paid AI is not a luxury.

It’s a way of working with intention: choosing the right environment for the task, and understanding the boundaries of trust that come with it.

Further reading
- Ethan Mollick: An Opinionated Guide to Using AI Right Now

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