A new relationship between AI, humans and machines is transforming factories. Industry is moving from humans managing machines, to co-bots supporting humans, to automated factories. The evolution is continuing, with AI bringing a new element of decision making.
“Work is moving from periodic, human-executed processes to continuous, human-orchestrated operations. Systems that previously required people to collect, reconcile and act on information are becoming capable of doing those things autonomously,” says the “Human Machine Collaboration in Industrial Operations: Activation Playbook”, a report released by the World Economic Forum (WEF). “Humans are now predominantly involved in higher value-added tasks such as decisions on what the system should optimise for, governance of systems and arbitration of consequence-heavy outcomes.”
Enterprises may not have the luxury of waiting for technology to become perfect. Neither will they have time to totally reorient their teams for new technologies. They will have to continuously experiment and adapt for relevant outcomes. Workers will have to move into judgemental roles where an AI-driven machine may not have the authority to take decisions. “Future jobs require managing shared data, shared decisions and shared accountability across networks of suppliers and partners that no single organisation owns,” the WEF report says.
ACG, a Mumbai-based pharma firm, is cited in the report for managing human-machine relationships. The company’s facility manages equipment that is more than six decades old while producing more than 5,000 stock keeping units requiring precise tolerances. Historically, machine configuration relied heavily on individual operator experience, which often led to inconsistent settings, reduced yields, quality issues, and longer lead times.
To address these challenges, the facility implemented machine learning models trained on more than two years of historical data. These models now provide prescribed, optimal settings for initial machine programming to ensure “first-time-right” results. The process has become collaborative: Operators integrate these recommendations into the machinery and continuously refine the models based on real-time outcomes. This approach ensures that the professionals running the equipment are the same ones training the underlying intelligence.
The report also talks about Schneider Electric, which is leveraging generative AI and augmented reality (AR) to streamline equipment management. To support new operators in handling expanding automation portfolios, the company has introduced AR glasses that provide immediate access to a comprehensive library of equipment data and technical manuals. By displaying real-time diagnostics and solutions directly to the user, these glasses have reduced the training period for new technicians in half, reducing the time to mastery from 18 to just nine. An important component of this success is the “calibrated trust loop,” a collaborative process where operators verify and improve AI suggestions. This approach effectively captures the deep expertise of veteran staff while building the technical confidence of new hires.
This is the trinity loop of AI, humans and machines: AI helps humans who guide machines that feed data to AI. However, not all is virtuous in the loop. The evolving relationship of human-machine collaboration is affecting employment options in factories. While workers will move up the effort value chain, the sheer number required in a factory is dropping. Fewer people are required to make judgement decisions than shop floor operators. Workers who manually operated machines or personally monitored performance are being replaced by AI bots. The traditional factory divide between white-collar managers and blue-collar labourers is blurring. Thanks to AI, factory workers are evolving into a new class of “grey-collar” professionals — hands-on operators who use real-time data and AI tools to manage and supervise the entire production line. Industry leaders and policymakers must make a fresh assessment of the impact of the human, AI and machine trinity. The quality and quantity of demand for factory workers is changing rapidly.
The writer is an economic analyst and author 
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