Imagine a manufacturing company. On the factory floor, machines whirl and grind, torches flare up as welding helmets click closed, and parts and products fall off the line and into waiting hands or boxes, ready to be shipped to customers. Elsewhere, through several doors and a long hallway, you leave the cacophony of the shop floor for the quiet hum of the office. Computers ping with new emails while fingers clickety-clack across the keyboard. Occasionally, a printer whirs to life while forcing someone to raise their voice as they talk to a customer on the other end of the phone.
Now, imagine that you ask each person whether AI and automation will positively or negatively affect their jobs. Who will champion new technology and who will resist it?
Most people expect automation acceptance to be separated by the long hallway, with the office workers welcoming while the factory workers resist.
Most people are wrong.
The Business Case for Problem-Solving Job Design
Last week, I wrote about findings from an MIT study that indicated that trust, not technology, is the leading indicator of whether workers will adopt new AI and automation tools.
But there’s more to the story than that. Researchers found that the type of work people do has a bigger influence on automation perception than where they do it. Specifically, people who engage in work requiring high levels of complex problem-solving alongside routine work are more likely to see the benefit of automation than any other group.
Or, to put it more simply
While it’s not surprising that people who perform mostly routine tasks are more resistant than those who engage in complex tasks, it is surprising that this holds true for both office-based and production-floor employees.
Even more notable, this positive perception is significantly higher for complex problem solvers vs. the average across all workers::
- Safety: 43% and 41% net positive for office and physical workers, respectively (vs. 32% avg)
- Pay: 27% and 25% net positive for physical and office workers, respectively (vs. 3.9% avg)
- Autonomy: 33% net positive for office workers (vs. 18% average)
- Job security: 25% and 22% net positive for office and physical workers, respectively (vs. 3.5%)
Or, to put it more simply, blend problem-solving into routine-heavy roles, and you’ll transform potential technology resistors into champions.
3 Ways to Build Problem-Solving Into Any Role
The importance of incorporating problem-solving into every job isn’t just a theory – it’s one of the core principles of the Toyota Production System (TPS). Jidoka, or the union of automation with human intelligence, is best exemplified by the andon cord system, where employees can stop manufacturing if they perceive a quality issue.
But you don’t need to be a Six-Sigma black belt to build human intelligence into each role:
- Create troubleshooting teams with decision authority
Workers who actively diagnose and fix process issues develop a nuanced understanding of where technology helps versus hinders. Cross-functional troubleshooting creates the perfect conditions for technology champions to emerge. - Design financial incentives around problem resolution
The MIT study’s embedded experiment showed that financial incentives significantly improved workers’ perception of new technologies while opportunities for input alone did not. When workers see personal benefit in solving problems with technology, adoption accelerates. - Establish learning pathways connected to problem complexity
Workers motivated by career growth (+33.9% positive view on automation’s impact on upward mobility) actively seek out technologies that help them tackle increasingly complex problems. Create visible advancement paths tied to problem-solving mastery.
Innovation’s Human Catalyst
The most powerful lever for technology adoption isn’t better technology—it’s better job design. By restructuring roles to include meaningful problem-solving, you transform the innovation equation.
So here’s the million-dollar question every executive should be asking: Are you designing jobs that create automation champions, or are you merely automating jobs as they currently exist?