Google's Gemini Spark: an AI agent that works in the background instead of you

Google has introduced Gemini Spark — a new AI agent that can work 24/7 and perform complex tasks in the background while you sleep or go about your business. The agent can be "shockingly good" at executing tasks, but journalists and experts question whether it justifies its financial cost and potential privacy risks.

What is Gemini Spark

Gemini Spark is a new AI agent that Google positions as a personal assistant for automating complex tasks. The company claims the agent is "always under your control," "only activates at your request," and is "designed to check with you before performing critical actions." This means Spark won't simply do whatever it wants without your involvement — it should operate under your supervision.

Google gave Verge journalists access to Spark for a week of independent testing. From direct interaction with the agent, it became clear that Spark has quite broad capabilities for modern AI automation.

The agent's capabilities include:

• Background operation without requiring constant user presence
• Execution of multi-step tasks and complex action chains
• Continued operation even when you've closed the app or stepped away from the computer
• Action execution with advance notification to the user before critical operations
• Task processing in 24/7 mode with continuous availability

How Spark Works in Practice

When Verge experts tested the agent in real-world conditions, the results turned out to be frankly mixed. On one hand, Spark can indeed be surprisingly effective. The agent handles several types of tasks assigned to it by the user and can work on them autonomously. On the other hand, work quality heavily depends on how clearly you formulate your instructions and the type of task you set for the agent.

Spark performs some tasks excellently, and the results of your instructions come out exactly as you envisioned them. But on other tasks, you can catch the agent making errors or misinterpreting your instructions. It's like a situation where you hire a new team member and don't yet know their weaknesses and blind spots.

There are also questions about how often Spark will "check in" with you before taking action. If it requires confirmation for every step, automation efficiency will be significantly reduced. If it acts too independently, it increases the risk of errors.

"Spark can be shockingly good at what you ask it to do,"

Verge says of its first impression of the agent.

Price and Privacy Risk

The main skepticism toward Gemini Spark stems from two key questions that concern both experts and potential users. The first is the financial cost Google charges for such functionality in the form of a subscription. The second, and more serious, concerns privacy and personal data security.

When an AI agent works in the background on your behalf, it potentially sees a lot of personal information: your accounts and passwords, financial data and payment histories, private messages and correspondence, and information about your interests and preferences. Google insists the agent operates locally and doesn't send your personal data to servers, but it's difficult to fully verify this promise independently.

Verge journalists note that despite Google's claims about control and security, the risk remains substantial. It's not entirely clear how Google will handle data collected by the agent during its operation, or what will happen if the agent makes a mistake or is compromised by an attack.

What This Means

The emergence of Gemini Spark marks the transition of browser-based AI agents and automation from laboratory conditions to real consumer products. This is a technology that seems useful and even revolutionary on paper, but in reality remains insufficiently reliable and transparent for mass adoption without additional security measures. Spark will likely find users among those willing to accept risks for convenience. But for most people, it would be wiser to wait for Google to significantly improve security, transparency, and data handling before trusting the agent with critical tasks.