The Den uses AI to support business expansion

The Den Family Social, a family club in Denver, is using ChatGPT Work to reduce its administrative workload as it prepares to open a second location. According to a case study published by OpenAI on October 1, 2026, the leadership team says the tool saves around 10-15 hours a week, mainly by helping gather information, prepare paperwork and develop options before making decisions.

What stands out is not that AI runs the business itself. In this case, AI handles some of the preparation, while people check the results and remain ultimately responsible. This is a concrete example of using AI to support business expansion without handing all decision-making authority over to the tool.

As a business expands, scattered information becomes a burden

The Den combines hospitality, community activities, work and play, aiming to create a space where parents can participate alongside their children. In preparing the second location, the team had to turn its experience at the first into an actionable, repeatable plan.

The challenge is not just writing more documents. The information needed is spread across emails, internal conversations and stored files. The person responsible has to find the right versions, identify what is missing and assemble everything into a consistent set of documents.

According to OpenAI’s case study on The Den, the business uses connections to Gmail, Slack and Google Drive to help gather and analyze information and suggest next steps. The team still reviews the output before using it.

This highlights an often-overlooked bottleneck: a business may already have enough information but lack the time to turn it into clearly defined work.

What do the time-saving figures tell us?

OpenAI highlights two examples from The Den’s experience:

Liquor license application: the work of finding, organizing, formatting and assembling documents was described as falling from four days to three hours, leaving the team to review and finalize them.
Grant application: preparation time reportedly fell from three days to two hours.

For the license application, the need for a quick turnaround arose when the business had an opportunity to attend an earlier hearing. AI helped assemble documents, identify missing items and convert files into the required format.

However, application preparation time is not the time it takes to obtain a license or receive a grant. The tool does not replace the reviewing authority or guarantee that an application will be approved.

The figures above are results reported by the business in material published by the provider. The article does not offer an independent assessment or a sufficiently detailed measurement method to treat these savings as typical for every business.

The value lies in preparing for decisions

Beyond administrative paperwork, The Den uses AI to develop proposals before bringing issues to the leadership team for discussion.

One example is designing an approach to working with partners. The person responsible shares what has worked, what has not and why, then uses ChatGPT to develop a partnership structure for the team to consider.

On the operations side, managers gather reports from accounting along with sales and inventory data, then use AI to organize the information into a format that is easier to follow. The aim is to support discussions about inventory needs, purchasing and operations across the two locations.

The division of work here is fairly clear: AI helps organize data and develop options; people check assumptions, consider the context and make decisions. This is also an important principle in getting started with AI to support work.

What can small businesses learn from this case?

Choose one set of documents, not the whole business

A useful trial could begin with partner documentation, documents for opening a location or regular internal reports. The output should be specific: a document checklist, a table of missing information or a draft for the person responsible to review.

The clearer the scope, the easier it is for a business to identify where the tool is helping and where it is creating extra work. Do not start with an overly broad request, such as having AI manage the entire expansion.

Ask for traceable supporting information

For each important item, ask AI to identify the supporting file or passage, if the tool supports this. Information it has not found should be marked as missing rather than filled in with guesses.

This approach helps reviewers return to the original documents, especially when there are multiple versions or data does not match across departments. The fact that AI produces a coherent summary does not prove that everything in it is accurate.

Keep a human approval checkpoint

Legal information, financial figures and commitments to partners need to be confirmed by the person responsible before being sent externally. For specialized matters, businesses still need an accountant, lawyer or appropriate consulting firm.

When connecting email and document repositories, also check access permissions, data processing terms and the scope of information being shared. A small trial using less sensitive documents is usually easier to control than connecting all data from the outset.

Measure effectiveness by completion time, not just drafting speed

To evaluate a similar workflow, businesses should record the total time from receiving a request to document approval. This figure needs to include time spent checking, correcting errors and tracing sources.

Other useful metrics include the number of omitted details, the number of document revisions and whether another staff member can take over the work. A draft that appears quickly but needs extensive revision does not necessarily deliver practical benefits.

This offers a more concrete view of the shift in AI from conversation to workflow support. For teams working across multiple locations, storage and handover conventions remain important, much like the principles of organizing work for distributed teams.

Conclusion

The Den’s case shows that AI can support the behind-the-scenes work of expansion: finding documents, identifying gaps, preparing paperwork and organizing information for decisions. The lesson worth applying is not to expect every business to save 10-15 hours a week, but to choose a clearly defined workflow, retain human review and measure effectiveness after accounting for the effort spent checking.

Frequently asked questions

Did The Den have AI submit the license application on its own?

The source provided describes AI helping assemble documents, identify missing items and convert formats. The Den’s team reviews and finalizes the work; the source does not indicate that AI independently takes responsibility for submitting the application or handling the entire procedure.

Can other businesses expect to save 10-15 hours a week?

These savings should not be treated as a default. Results depend on the volume of paperwork, data quality, the tool’s capabilities and review time. Test a small workflow, then compare total completion time before and after.

Do you need to connect all email and document repositories for a trial?

No. Businesses can start with a selected set of documents they are authorized to use. If using data connections, check the scope of access, internal policies and the service’s data processing terms.

How can you limit AI adding information to documents on its own?

Ask the tool to use only the documents provided, identify the supporting sources for important information and mark unverified content. Then check legal entity names, dates, figures and procedural requirements against the original sources before approval.