Before you buy AI: What manufacturers need to get right first
From NZ Manufacturer magazine – May issue By Sean Doherty, Manufacturing Commentator | NZ Industry Trends There is no doubt that AI will be a game changer for manufacturers, and early adoption will give many firms a competitive advantage because manufacturing is both data-rich and operationally complex. But beware: AI only creates value when it is applied to the right problems. Too many manufacturers get distracted by the demo and find out too late that their data is poor, the tool does not fit the workflow, or ownership of the outcome is unclear. In 2026, the manufacturers most likely to succeed with AI will be those that treat it like any other investment decision. Define the need, test the assumptions, manage the risks, and measure the potential return. Before buying any AI tool, there are four practical basics to get right: the problem, the data, governance, and the pilot. Start with the problem Start by defining the problem in plain language. A manufacturer should be able to say exactly what it wants to improve: machine uptime, planning speed, forecast accuracy, scrap rates, or quality checks. “We need AI” is not a business case. It is noise. Before speaking to vendors, define success. What metric needs to move, and by how much? If the goal is less downtime, what is the baseline, and what improvement would justify the investment? If the issue is quality, is the target fewer defects, faster inspection, or less rework? Clear objectives make it much easier to spot a valuable tool and avoid an expensive distraction. Mapping the current workflow also helps. Where are decisions slow, manual, repetitive, or error-prone? Where does information stall, and what information is needed to move things forward? A simple process map can quickly reveal whether the problem is poor process design, […]