Will AI Replace Employees or Make Them More Productive?

AI can help employees spend less time on repetitive tasks, but no responsible answer can promise what will happen to every job. SGM’s position is to design AI around employee productivity while people remain responsible for important decisions.

A job usually involves more than producing text or moving data. Judgment, relationships, expertise and accountability still matter. Before changing a role, understand the work a person actually does, including the exceptions and informal checks that keep a process running.

Consider a staff member who answers recurring questions. An assistant could retrieve relevant approved information or prepare a draft. The employee can check the answer, understand the customer’s situation and handle the conversation. The value depends on whether retrieval and drafting save effort after review is included.

For reporting, AI might prepare a summary from authorized records. A person still needs to check the underlying figures, decide what matters and approve any action. For documents, extracted information can be presented for review before it reaches an operational system.

These are examples of possible workflows, not claims about completed SGM projects. The right design depends on your information, systems, risk and staff needs.

“The computer made the decision” is not a useful accountability model. Decide who can approve an action, who checks exceptions and who can stop the automation. Make those responsibilities part of the process rather than an assumption.

An approval should happen at the point where it can prevent a mistake. Reviewing a message after it has already been sent does not provide the same control as approving it before sending. Staff also need enough context and authority to disagree with a suggestion.

• Define which tasks AI may prepare, suggest or perform.
• Require appropriate approval for actions with material customer, financial or operational consequences.
• Provide a clear way to escalate uncertainty or missing information.
• Record changes and decisions where appropriate for the workflow.
• Keep a person responsible for checking performance and responding to problems.

Employees can explain where the written procedure differs from daily reality. Involve them while mapping the workflow and testing the pilot. Ask which steps are repetitive, which need judgment and where an incorrect result would cause trouble.

Training should cover the system’s limits as well as its features. People need to know which information they may enter, how to verify output and when to return to the manual process. Treat corrections and staff feedback as evidence for improving the design.

Measure the whole workflow. A system that produces drafts quickly but creates more checking, rework or confused handovers may not improve productivity. Compare the pilot with the previous process using agreed measures before expanding it.

Choose one repeated task and identify how staff would use the time if it became easier. Then define the boundaries, review requirements and success measures for a small pilot. This makes the discussion concrete without relying on predictions about the future labor market.

SGM can help you understand where AI may fit and where people should stay involved. Start by explaining your current process and the problem employees most want to solve.

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