BUSINESS MATTERS
AI AND AUTOMATION: DEBUNKING THE 5 MOST COMMON MYTHS
the experimental or piloting stages, with just a small percentage actually deriving value from it. In industrial settings, mindset is proving a barrier to greater adoption. The 2025 Edelman Trust Barometer found that trust in AI is lowest in developed economies like the UK, Germany and the US . This represents a real challenge because trust is fundamental to achieving the support – from boardroom to factory floor – that is needed to integrate AI in a meaningful way. Mistrust of new technology is something
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the automation sector is used to dealing with. For years, industrial robots faced resistance from human workers who perceived them as a threat to their livelihoods. However, over time it has been proven that these fears are unfounded. In 2022, the Institute of Labor Economics studied the effect of robots on the labour market in 16 European countries and concluded that robot adoption actually increased employment and reduced
I use continues to expand in the global workplace, but most businesses are still in
unemployment in most markets. Just as fears about robots have
been allayed, the key to building trust in AI is similarly rooted in education, information and transparency. Here, we debunk some of the most common myths surrounding AI and automation…
Myth #1: AI will take my job Picture a world without Word or Excel – it’s unimaginable. Think of AI in a similar vein, as a tool that helps people to do their jobs more efficiently by automating repetitive and mundane tasks, generating insights and intelligence that can inform decision making, accelerating lengthy testing and design processes, and making predictions that can eliminate risks. Faced with an ageing workforce
and chronic labour shortages, the manufacturing sector can also harness AI to supplement and bolster scarce expertise. Difficult-to-fill roles that involve repetitive, manual and routine tasks will be replaced by more skilled jobs that require critical thinking and analysis; AI-augmented technicians, analysts who interpret data to
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optimise production schedules, and AI-model builders, for example. It is worth remembering that AI is
rarely a standalone solution. In fact, companies only really unlock its value when they enable employees with real-world domain experience to interact with AI at strategic points. The synergy between AI solutions, human judgement and workplace expertise is what creates hybrid intelligence superpowers and real value capture. In robotics, for example, AI is expanding
the opportunities for collaborative applications. By embedding AI, perception and real-time reasoning – components of physical AI – robots can interpret voice commands, respond to dynamic environments and work safely alongside human operators.
Myth #2: AI puts our company’s data at risk As with any data-based technology, there is a requirement to protect AI models, the data they process, and the broader systems they integrate with, against cyber threats, data interception
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