Google's new Gemini AI agent is only as good as the real workflow behind the demo

Google is entering a new AI era with Gemini Spark, an advanced agent meant to work as a 24/7 personal assistant. The promise is attractive: a tool that carries out multi-step tasks on its own instead of only answering questions.

Early hands-on tests, however, show a classic problem with new agents: the demo is not the same thing as real use. The agent can understand complex instructions and try to execute them, but in real work it quickly runs into exceptions, ambiguous context, and edge cases that were absent from the marketing presentation.

For a small business, the more important question is whether such an agent saves real time without adding risk. In practice, it only starts making sense once the process is already organized, the source of the data is clear, and the limits of agent autonomy are defined. Without that, an interesting experiment can easily become an expensive layer of chaos.

The second question is privacy and price. An agent that plans, filters, and acts in the background needs deep access to calendars, email, and other data. That creates a real trust cost. If Google does not show a clear control model and sensible pricing, broad adoption will stay limited.

From MorenaTech's perspective, the interesting part is not the generic phrase 'AI agent' but the parts of the workflow that can be extracted into something controlled. In a small business, an agent usually works better when it supports one concrete stage: screening requests, drafting a response, planning follow-up, or checking missing data. A human in the loop still matters.

More detail is available in The Verge hands-on report.