Manufacturing is becoming a technology sector. How could this affect your next career move?

The benefits can be unevenly distributed and initially focused on the bottom line. This means that many organizations have yet to exploit AI’s top line potential as a growth engine. As we’ll discuss, understanding where the true value lies can transform a defensive legacy organization into a dynamic disruptor.  

CXOs and NEDs must be courageous and creative, says Sandy McKenzie, a Managing Partner at Amrop UK and co-leader of Amrop’s Global Industrial Practice. And boards must be ready to welcome new thinking. 

Manufacturing is a vast, evolving arena. As in any innovation curve, 5-20% of players lead, a big middle section of cautious adopters milk the status quo, and a substantial group play catch-up. But the gaps are widening. As an incoming leader, where can you expect to drive change, and under what conditions? 

For executives seeking a career move, we see three broad categories of organization. 

Experimental startups are agile, digital‑native, and able to deploy AI rapidly – if they can secure the funding to grow, and even reach coveted unicorn status. New entrants are springing up everywhere: despite splits in AI uptake between the global north and south,ii the machines have leveled the geographical field.  

Consider Estonia – a smaller, entrepreneurial country on the move to become a technology powerhouse and investment target. Its Eesti.ai program, targeting GDP growth and innovative solutions, aims to double productivity by 2035.iii Moreover, corporate culture mirrors national culture: Estonia’s Stargate Hydrogen, an advanced clean‑tech manufacturing company, combines deep scientific R&D with industrial‑scale hardware production. 

Larger players face their own barriers: heavy decision-making, complex operations, legacy IT systems, talent shortages, all wrapped up in cultural inertia. Listed firms, tied to shareholder returns, have an additional problem - short-termism. On the upside, their big balance sheets and data pools don’t just boost the prediction, optimization, and automation of high‑value, repeatable decisions, they offer room for controlled experimentation. Siemens has deeply embedded AI into its manufacturing systems. GE is a pioneer in using AI for predictive maintenance. Toyota has integrated AI to culturally align with its lean production philosophy. 

Family‑owned businesses, free of shareholder pressure, can take a longer-term view. But many are naturally cautious. Lagging digital investment makes them an acquisition target for private‑equity firms eager to unlock value by modernizing the firm - and its management team. AI-enabled transformation is becoming a bigger theme.   

I’ve had more conversations about Chief Transformation Officers in the last six months, than in the previous six.  

There are also big differences in sub-sectors. AI brings its fastest gains in high‑volume, repetitive processes: chemicals, logistics, food. More complex, high‑stakes environments – especially those where customer safety is paramount, such as automotive, machinery, and components - face bigger trust and adoption barriers.  

Cross‑fertilization is essential.  

Across all sectors, there are serious concerns about the maturity of human capital. We argue for a set of non-negotiables: curiosity, adaptability, comfort with ambiguity. Digital and data skills matter as much as industrial expertise does. As in all sectors, leaders must create digital-literate cultures. They must also install cross‑functional collaboration between HR, finance and operations, engineering, technology, and as we’ll see, commercial. AI adoption is strengthening the flow from back‑end cost reduction to front‑end revenue growth. 

Unsurprisingly, Chief Digital, Technology, and Data Officers are in hot demand. To find them, we emphasize cross‑border search strategies: retail leaders, for example, are skilled in AI-enabled segmentation and pricing. Diversity drives performance, whether in terms of a candidate’s (sub-) sector, market, or technological background. We have a simple piece of advice for hiring organizations: don’t just recruit people who look like you. This opens yet more opportunities for forward-thinking candidates. 

AI can change purpose and revenue models. But it requires open minds. 

In a real case, a team of brilliant scientists founded a fusion‑energy business. They built an AI to design a cutting-edge device. But it was failing to deliver financial returns fast enough. We observed that the value lay not in the device, but in the AI that built the device. The firm needed to recruit commercial executives to sell the concept.  

To escape the comfort zone, boards and executive teams need courage and creativity. On one end, we find the progressives who honestly question, learn, and act. On the other, the protectionists who are clinging to the legacy or marking time to retirement or a sell-out - often with a two-year strategic horizon. Before joining, CXO candidates need to understand that agenda. 

A new leadership mandate is emerging.  

As AI reshapes industrial manufacturing, executives and NEDs must pair strategic courage with creative, cross‑functional thinking. The winners will read the real value signals, challenge legacy mindsets, and build digitally fluent, diverse teams. Candidates must perform due diligence to understand the organization’s true appetite for transformation. 

For boards, the task is clear - hire for curiosity, adaptability, and the imagination to redefine the business.