While 53% of C-suite barometer respondents in the manufacturing sector name artificial intelligence (AI) as their top investment priority, adoption should mirror business needs to add value and secure a return on investment (ROI). Prioritising the interconnectivity of good-quality data and adopting robust governance frameworks is key if manufacturers are to avoid costly risks and regulatory challenges.
Such challenges are compounded by the fact that manufacturing companies are at various stages of AI adoption. Some have heavily leaned into AI on projects such as quality control to reduce manufacturing defects to virtually zero, while other companies are just trying to figure out how to implement more basic technology.
While the desire to lean into AI and automation is clear, the lack of good-quality data is slowing progress. Initial internal steps are required to improve customer, costing and manufacturing data to leverage automation and AI tools more effectively and improve trust in transformation projects.
"Technology transformation often causes paralysis, not progress. As advisors, part of our job is to move clients from planning to action. By motivating clients to take small, actionable steps, daunting technology plans can be turned into achievable goals — taking that first step is vital.”
Frank Jungblut Partner, Head of Manufacturing, Forvis Mazars Group
In addition, many companies are overwhelmed by the size of technology transformation and AI-led projects. However, often small steps can be taken to achieve substantial wins. Simple projects such as automating manual payment processes and integrating data into enterprise resource planning (ERP) systems help improve processes. Starting with small, incremental technology projects that highlight the benefits of change can help build confidence and demonstrate value before stepping up transformation projects.
The race to implement AI is reshaping businesses in the sector both top-down and bottom-up. Two-thirds of manufacturing C-suite leaders say that AI is having a major impact on their company, up 16 points since 2025. Four in five have already restructured their teams to implement AI.
Uptake of AI across companies is strong, with operational optimisation and automation the primary AI drivers for manufacturing leaders. However, many are still navigating early-stage implementation.
To progress efficiently, manufacturers should focus on developing targeted use cases that align with core business needs, proving value before scaling up. Taking a strategic and cautious approach to AI adoption also helps avoid costly mistakes.
C-suite barometer results show that manufacturing leaders’ main supply chain investment priorities are the integration of new technologies and the growth of operations in current markets.
Following lessons from the Covid pandemic, the need for manufacturers to diversify suppliers and reduce dependence on single or hostile regions continues as pressure from geopolitical tensions, tariffs and global events builds. To counteract disruption and mitigate risks, nearshoring and building local supplier networks are growing trends.
Rising costs are also taking their toll. While many manufacturers are having to pass increased supplier costs on to customers, they are also seeking efficiencies and redesigning products to manage price pressures and reduce reliance on a single supplier where possible.
Although slightly down from previous C-suite barometer results, optimism on growth prospects remains relatively high among manufacturing leaders. The most challenging external trends to growth are economic uncertainty and increased competition. Diversifying resources is the key operational shift in reaction to global trade disruption for leaders in the sector. More than half of companies are also pursuing services consolidation.
For many companies, it’s a question of survival: learning to live in a business environment constantly underpinned by uncertainty. As a result, some manufacturers are taking a conservative approach and pulling back from expansion goals to protect balance sheets.
However, where growth pockets remain strong, manufacturers are expanding and actively seeking mergers and acquisitions. Specifically, large infrastructure projects in the technology, AI and energy sectors continue to create opportunities for manufacturers. Increasingly, however, executives are adopting a cautious approach to counteract an expected pullback in infrastructure spending.
As the manufacturing landscape evolves, gaining a competitive advantage demands hyper-agility and targeted, strategic change. Rising costs and the risk of AI-driven obsolescence require a smart approach. In this environment, being on the 'bleeding edge' can be a liability.
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Manufacturing leaders need to rethink their approach to technology transformation. Being competitive is no longer about simply acquiring cutting-edge technology: it’s about acquiring the agility to adapt emerging technology once it has been flushed out. Adapting proven digital solutions not only adds operational resilience but also helps to avoid expensive failures.” Bryan Wright, Partner and National Manufacturing Sector Leader, Forvis Mazars US |
Success now hinges on balancing strategic technology adoption with calculated caution and peer benchmarking. A robust digital blueprint is essential to guide manufacturing leaders through their technology transformation journey.
Every year, we conduct research to understand the priorities and issues at the heart of our clients’ businesses. Our C-suite barometer gathers the views of executives from all over the world, giving us valuable insight into key topics on their agenda, the trends and transformations they expect to impact their company, the challenges and opportunities they are facing and their outlook for the year...
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