Manufacturing technology is moving toward software that helps teams decide what to do, not only record what has happened. In an industry analysis, Paul Lachance argues that artificial intelligence is helping manufacturers connect information across operations and respond sooner to problems.
The change does not mean replacing enterprise resource planning, manufacturing execution, maintenance or asset management systems. Those platforms remain the operational foundation, storing inventory, production history, maintenance records, financial information and other business data.
Instead, Lachance describes a progression from software that records activity to systems that make information visible, support action and help coordinate decisions. The industry analysis of manufacturing software frames AI as one tool for making existing operational data more useful.
Manufacturing Technology Builds on Core Systems
Manufacturers first built systems of record to replace spreadsheets, paper files and disconnected applications. Dashboards and reporting tools later made that information easier to see, but people still had to decide how to respond.
Workflow automation, scheduling and maintenance coordination added ways to act on what teams learned. Lachance says the next stage brings intelligence and orchestration, with software recognizing patterns and connecting context across people, equipment and facilities.
He illustrates that idea with a predictive maintenance scenario. Vibration data could indicate that a critical production asset may fail within several days. Software could then alert maintenance, identify a production window for repairs, check whether replacement parts are available, consider customer delivery commitments in the ERP system and recommend a less disruptive schedule.
The example depends on connected systems and reliable information. It describes how software could coordinate a response, rather than reporting a particular factory deployment or a newly announced product.
AI Must Work Within Manufacturing Conditions
Lachance calls manufacturing a demanding test for AI because operations involve physical processes, exceptions and competing requirements. Decisions can affect machines, materials, workers, maintenance schedules, quality requirements, customer commitments and production deadlines.
He argues that manufacturers judge technology by operational results. Relevant questions include whether a system improves throughput or uptime, reduces manual work, helps teams respond to disruptions, supports maintenance planning or gives managers clearer visibility into constraints.
Broad claims may not survive plant conditions, he writes. Incomplete information, production variability and competing priorities can expose gaps that a product demonstration does not show. Software also depends on systems sharing information effectively across an operation.
That emphasis on practical use connects with other coverage of AI and technology across industries. At an AI conference at FIU, speakers discussed applications ranging from business operations to transportation and engineering. A separate Shanghai council discussion considered AI use in manufacturing, services and medical care.
Manufacturers Need Connected Decisions
The analysis also points to semiconductor manufacturing as another area where software and industrial technology meet. Smartech Daily reported that SUSS partnered with Ignite Next to connect with startups and deep-tech innovators. That story concerns a separate company partnership, but it reflects the broader role of technology in manufacturing operations.
Lachance’s central point is that AI alone is not the value proposition. Software must help manufacturers operate efficiently, make decisions and respond to changing conditions. The systems of record remain in place, while the next challenge is connecting their information well enough to address small operational issues before they grow.
Paul Lachance is identified in the source as chief industry strategist, technologist and evangelist at Software Equity Group. The source says he advises software founders, executives, private equity firms and strategic acquirers on growth strategy, AI, market positioning and mergers and acquisitions.
