These questions matter whenever an AI answer becomes work that affects a customer, a budget or a team.
The tool can be useful. The decision still needs care.
Imagine a manager reviewing an AI-written report. The figures are correct, but the summary leaves out a delivery problem. The report looks ready. The decision is not ready until the manager understands that problem.
Now imagine a customer service agent that handles routine refunds. An AI agent is AI that can take actions, such as issuing a refund. It saves the team work on simple cases. Someone must still decide which refunds it can approve, which cases go to a person and whether that person has time to handle them.
These are fictional examples of ordinary management responsibilities.
A finished AI answer is only one step
The work between an AI answer and a business result has several steps. People make decisions at each one.
| Step | What happens | Example |
|---|---|---|
| AI produces something | AI drafts, summarises, recommends or acts within its permission. | It recommends a supplier. |
| A person checks what matters | Someone checks the evidence, the business conditions and the cost of being wrong. | The manager checks delivery capacity and the contract. |
| A person chooses the action | The answer is used, changed, challenged or sent to someone with authority to decide. | The manager approves a limited order and names the conditions. |
| The team carries out the decision | Someone owns the work, the exceptions and the follow-up. | Operations tracks deliveries and handles late orders. |
| The organisation sees the result | Results include customer service, quality, cost and risk. | Deliveries arrive on time, or the team corrects the plan. |
A draft may take seconds. The decision about what to do with it can affect a customer, a budget or a team. That small part of the work can have a large effect on the result.
Why this matters now
AI is already part of management decisions. Deloitte's 2026 research found that 60% of executives said they regularly use AI to support decisions. Read the research.
Answers are not always checked. KPMG and the University of Melbourne studied trust and AI use in 2025. Among employees who use AI at work, 42% said they had relied on AI output without evaluating its accuracy sometimes or more often. The full study surveyed more than 48,000 people in 47 countries. Read the report.
Checking takes work. BCG's 2026 survey covered 11,749 employees, managers and leaders in 14 markets. In that survey, 52% agreed AI had increased the time they spend reviewing and correcting AI output. Read the findings.
Employers expect people to need more than tool skills. In the World Economic Forum's 2024 survey of over 1,000 employers, analytical thinking was the top core skill for 2025. Employers expect AI and big data to grow fastest in importance by 2030. They also expect analytical, creative and systems thinking to grow in importance. Read our summary.
These studies describe the challenge. They do not measure the effect of StepSim. Read our research summaries.
What people need to practise
- Decide which evidence matters before acting.
- Use good advice, and challenge advice that does not fit the facts.
- Set limits before AI takes action.
- Ask for a decision from the person with the authority to make it.
- Review the plan when new information arrives.
These decisions are what we mean by judgment with AI. Read what judgment with AI means.
How StepSim helps
StepSim is a browser-based business simulator. A business simulator is an online exercise where you take a work role, review information and make decisions. Managers face realistic business situations with an AI partner. They review information, make decisions and see what follows.
Their record shows what they checked, accepted, challenged and changed. Then a trainer leads a discussion and helps the team agree actions for its own work.
People can learn through this practice on its own or within a trainer's wider programme. Participant certification uses a separate assessment.