How to Use ChatGPT for Admin Tasks

TL;DR In January 2025, OpenAI released ‘Tasks’, a feature that allows ChatGPT to schedule reminders and recurring actions. This shifts the tool from a reactive search engine to a proactive assistant. While useful for reducing administrative noise, it remains in beta. We explain how the feature works and how to test it without risking reliability.

The Limit of On-Demand AI

Most organisations use generative AI as an on-demand service. The user types a prompt, the model provides an answer and the interaction ends.

This creates a dependency on human memory. If a manager forgets to ask for a report, the report is not generated. The friction of initiating the task often outweighs the benefit of the automation.

This limitation keeps AI in the role of a consultant rather than an assistant. It can solve problems, but it cannot manage a workflow.

How the January 2025 Update Works

The ‘Tasks’ feature began rolling out on January 14, 2025. It is designed to help users automate one-off or recurring actions.

It is currently available to paid subscribers on Plus, Team and Pro plans. To access it, users select “4o with scheduled tasks” from the model interface.

The mechanism is straightforward. You provide a specific instruction and a timeframe. You might ask for a daily summary of industry news at 7:00 AM, or a reminder to draft a weekly status email every Friday.

The system manages these requests in a dedicated list. Users can view, edit or delete items. When the scheduled time arrives, the system sends a notification to your desktop or mobile app.

The Shift to Agentic Assistants

This release is part of a broader move toward "agentic" AI.

A chatbot waits for input. An agent acts independently based on prior instructions. While the current version is limited to simple scheduling, it establishes the infrastructure for autonomy.

We expect this to evolve quickly. Future iterations will likely move beyond simple reminders to executing complex loops—such as searching for information, summarising it and emailing it to a team member without human intervention.

For now, it is a scheduled script. It follows a rote set of instructions. This makes it useful for repetitive, low-value work that distracts staff from deeper thinking.

Managing Risk in Beta Features 

The primary risk with autonomous tasks is reliability.

When a human manages a calendar, they understand the consequence of a missed meeting. When a beta software feature manages a calendar, it lacks that context.

We have seen early demonstrations of agentic AI fail to trigger or produce inaccurate data.

Organisations must distinguish between "convenience" and "criticality". If a task must happen for the business to function—such as payroll, client deliverables or compliance checks: do not give it to ChatGPT yet. Stick to established enterprise software.

If the task is helpful but optional, such as daily brainstorming prompts—it is a safe candidate.

A Protocol for Safe Implementation

We advise against rolling this out to an entire team immediately. Instead, follow this protocol to test the capability safely.

1. Identify the Administrative Noise:  Look for tasks that are repetitive, simple and purely digital. Good examples include checking a public website for updates or summarising a specific document daily.

2. Run Parallel Systems:  Do not turn off your existing reminders. Set the task in ChatGPT, but keep your standard calendar notification active. This allows you to verify that the AI triggers correctly without the risk of missing the deadline.

3. Verify the Output Quality: If the task involves generating text, review the quality for one week. Check for hallucinations or missed context. Automation is only valuable if the output is accurate.

4. Expand to Low-Risk Delegation: Once the pattern is proven, you can rely on the notification. However, keep the scope limited. Use the 10-task limit to focus on high-frequency, low-risk items that clear mental space.

Why AI Oversight Remains Essential

The goal of this technology is to reduce friction, not to remove responsibility.

A manager is still responsible for the output, regardless of who—or what—produced it. As we introduce these tools into daily workflows, the role of the operator shifts from "doing the work" to "reviewing the work".

Competence involves knowing when to automate and when to intervene. We help teams build the judgment to make that distinction.

FAQ

Q: Does this replace our project management software?

No. Dedicated tools like Asana or Jira are designed for complex dependencies and accountability. ChatGPT Tasks is for personal productivity loops and simple reminders. It lacks the structure to manage team-wide projects.

Q: How do we prevent staff from over-relying on it?

Set clear boundaries. Define "critical path" work that must remain in formal systems. Encourage the use of AI for personal organisation, but not for official business record-keeping or strict compliance deadlines.

Q: What happens if the system goes down?

This is a cloud-based feature. If OpenAI experiences an outage, the notification will likely fail. This is why we advise against using it for time-sensitive or mission-critical actions.

Q: Is data shared with the model used for training?

By default, interactions in ChatGPT may be used for training unless you are on an Enterprise plan or have opted out in settings. Be cautious about scheduling tasks that include sensitive client data or proprietary metrics.

Q: Should we mandate this for our team?

No. Allow competence to grow through experimentation. Let a few "champions" test the feature and share their results. Mandating a beta tool often creates frustration rather than efficiency.

If your organisation wants practical guidance on how to automate routine work, reduce manual prompting and build reliable agents without confusion, our No Code and Low Code AI solutions give your team a structured way to scale efficiency and capability.