By Ankush Jagga, Co-founder and CEO of UnfoldXR
With every major technological evolution, comes a certain level of both excitement and anxiety, and the AI revolution is no different. At every crossroads of history, when industries changed how they function, one question kept surfacing across manufacturing floors, warehouses, maintenance sites, and field operations – What happens to workers?
In the 1970s and 80s, when computers entered workplaces, many feared job loss and the pressure to adapt to unfamiliar technology. But instead of removing job roles, computers ended up creating new skills and roles, and reshaping work as a whole. The current anxiety around AI feels remarkably similar.
We forget that even in highly automated industries like manufacturing or oil & energy, operations still depend heavily on human judgement and experience. Which is why the real question today is not whether AI will enter frontline work, because it already has; the real question is – How can we use AI to not replace workers but make them more capable?
Why This AI Shift Feels Different
What makes the current AI wave different from traditional automation is where intelligence is beginning to appear. For years, intelligence largely remained confined to dashboards, reports, analytics systems, and back-office automation. It helped organisations analyse information after work had already happened.
Now, AI is moving this intelligence into the flow of work itself. Workers can receive guidance while performing tasks. Technicians can access diagnostics instantly at the site of a breakdown. Field teams can get contextual support without depending entirely on manuals, memory, or waiting for escalation.
Historically, automation aimed to remove human involvement from processes, but AI is creating a very different model from what we traditionally associate with automation. Frontline environments are rarely predictable enough to fully automate. Therefore, with Edge AI, the opportunity that we have today is not about replacing people but helping them perform better.
Productivity Without Workforce Inclusion Will Fail
With more than two decades of experience in working with frontline workers in the learning domain, I strongly believe that frontline AI adoption will fail if workers do not trust the systems being introduced.
If AI is perceived primarily as a monitoring tool or a replacement strategy, resistance is inevitable. No amount of technological sophistication can compensate for lack of workforce trust.
The organisations that will succeed with AI are the ones that use it to reduce friction for workers, not increase pressure on them. This is especially important because frontline work often comes with significant cognitive load. Workers constantly switch between systems, instructions, calls, documentation, and operational decisions while managing real-world environments. The job of Good AI should be to reduce this burden.
AI as a Skill Multiplier
As industries globally face an acute skilled labour challenge with manufacturing alone expected to face 7.9 million unfilled jobs globally by 2030, AI can become genuinely valuable. With agentic AI bringing contextual guidance and faster decision making, it does not replace workforce, but augments human capability, helping to scale expertise.
Imagine a new technician being able to perform a complex task with the support of contextual workflows and guided diagnostics. Onboarding time reduces by 30% and training happens at the moment of work with AI becoming the bridge between experience and execution.
The Ethics of Deployment
Most of ‘the ethics of AI’ are often discussed through the lens of regulation and governance. Those conversations are important, but ethics also exist in the everyday experience of workers using these systems.
Going forward, people need clarity around how AI is being used. They need transparency around data, monitoring, and decision-making. Most importantly, they need to know that human judgement still matters. AI should support decisions, not replace human agency. The best systems will always leave room for human override, contextual judgement, and operational flexibility.
The Future of AI at Work
The future of AI in frontline industries will be defined by how many workers companies remove from operations. It will be defined by how effectively organisations help people work with greater clarity, confidence, safety, and speed.
To scale sustainably, companies will need to build systems that make human capability stronger, because that is where the real productivity leap will come from.
I truly believe, the future of work is human capability, not replaced but augmented by artificial intelligence.