Five questions to ask before adding AI to your business

A useful AI project starts with a business decision: what needs to work better? A convincing demonstration is only a starting point. The real test is whether the system helps people complete a specific task reliably, using the information and permissions the business actually has.

Before choosing a platform, write down answers to these five questions. They give the owner, the team and the person building the system a shared definition of the job.

What should be different when the work is finished?

Describe the outcome in operational terms. “Use AI for sales” leaves too much open. “Prepare a lead summary with sources before a scheduled call” names an output someone can inspect. Separate the work the system produces from the result the business hopes to achieve. A prepared summary and a closed sale are different things.

Which information may the system use?

Identify the source records, who owns them and who is allowed to see them. Check whether information is complete enough to support the task. If a record is missing, the system needs a way to say so. Giving an assistant more information is useful only when the information belongs in that workflow and can be traced to its source.

Where does a person need to make the decision?

Drafting a message, approving its content and sending it are separate steps. The same distinction applies to a purchase, an account change or a public post. Decide which actions can happen under an agreed policy and which need a fresh review. Make that boundary visible to the person using the system.

How will exceptions get handled?

Consider an expired connection, an ambiguous customer request or a provider that accepts a request without confirming its completion. Decide who gets the issue, what information they receive and how they resume the work. A useful exception path lets a person continue from the last confirmed step without repeating a consequential action.

What evidence will show that the workflow works?

Pick a few representative tasks and define what a correct result looks like. Include missing information and a failed connection. Save the inputs, the outputs and the supporting records needed to assess each run. Time saved matters, but so do accuracy, review effort and the cost of fixing mistakes.

Choose a bounded first project

Start with a task whose sources, owner and completion criteria are clear. Learn from real use before expanding the system’s authority. Through Wolf Pack CEO, my work connects AI strategy with the processes, people and business systems that have to support it.

For a structured starting point, use the Wolf Pack CEO AI Readiness Assessment. It helps begin the conversation; its answers still need to be considered in the context of the business.

Frequently asked questions

What should I decide before choosing an AI platform?

Decide what should be different when the work is finished, which information the system may use, where a person makes the decision, how exceptions are handled and what evidence will show the workflow works.

What makes a good first AI project?

A bounded task whose sources, owner and completion criteria are clear. Learn from real use before expanding the system’s authority.

How should I judge whether an AI workflow works?

Test representative tasks, including missing information and a failed connection, and save inputs, outputs and supporting records. Look at accuracy, review effort and the cost of fixing mistakes as well as time saved.

Where does AI fit in your business?

The Wolf Pack CEO AI Readiness Assessment is a structured starting point for that conversation.

Take the AI Readiness Assessment