85% of SMEs already use AI. Only 31% know what for.

The initial data sounds like good news: 85% of Argentine SMEs already use artificial intelligence in some process of their operation. 87% reported productivity improvements. At first glance, it seems that technological adoption has finally reached the missing scale.

But there is a second piece of data that changes the reading: only 31% have a clear adoption strategy.

That means that almost 7 out of 10 companies using AI do so without prior diagnosis, without defined success metrics, and without real integration into the workflow. The tool is there, working, generating some perceptible improvement — but no one can say precisely what problem it solved, nor how to measure it if it stopped working tomorrow.

The gap is not technological

Hiring a ChatGPT plan or connecting a bot to the CRM does not require any special capability. Any company can do it in an afternoon. Technology stopped being the barrier a long time ago.

The real barrier is criteria: understanding what problem you are solving, in what part of the process the tool acts, and how you know — with data, not with feeling — that it worked.

Without those three answers, what you have is not an AI strategy. It's just another tool, added to a process that already had other unsolved problems.

What changes when there is a diagnosis first

An adoption strategy is not an extensive document or a twelve-month roadmap. It is, at a minimum, being clear about:

• Where the bottleneck that AI will attack is (not "in general", but in what specific step of the commercial or operational process).
• What metric defines if it worked — time, conversion, cost, human error — before implementing, not after.
• How it integrates into the existing workflow, instead of being added as a parallel tool that the team ends up abandoning after two months.

Without these three points, the 87% productivity improvement reported in surveys is usually perception, not measurement. And perception does not sustain an investment decision next year.

How we work on this at Verzeen

At Verzeen, we don't start with the tool. We start with the diagnosis: understanding how the business works, where the real bottlenecks are, and what metric matters before proposing any solution — whether it's AI, automation, or a process change.

Then comes the strategy: what is implemented, in what order, with what measurable goal.

Only then, the execution.

That order is what avoids burning budget on implementations that generate noise but no results.

A question for your business

Has your company already adopted any AI tool? Before doing so, did you have a diagnosis and a defined success metric, or was it a more organic decision, resolved on the fly?

If the answer is the latter, it's probably worth an audit of your digital channels before adding the next tool.