Only 18% of industrial manufacturers currently operate with highly automated key processes. By 2030, that share will reach 50%. This is not a gradual trend - it is a structural break. For plant managers, process engineers, and capital planners in metalworking and fabrication, the implications extend far beyond the shop floor.
PwC's Global Industrial Manufacturing Sector Outlook 20261Global Industrial Manufacturing Sector Outlook 2026, drawn from a survey of 443 senior executives across 24 territories, presents a definitive picture of an industry at an inflection point. The central finding: the median share of industrial manufacturers with highly automated processes is set to more than double by 2030, rising from 18% to 50%. Advanced technology adoption across entire operations - spanning production, design, business support, and after-sales - will push overall reliance on advanced technology from 26% to 68%.
The Numbers Behind the Forecast
The doubling figure is compelling on its own. The underlying data makes it more consequential.
In two value-chain areas - production and operations, and product design and development - heavy use of advanced technology will reach 76% and 72% of manufacturers respectively by 2030, up from 29% and 37% today. Even functions with comparatively low automation today are keeping pace: the extensive use of advanced technology in business support functions such as finance and HR is expected to nearly quadruple by 2030.
The survey methodology captures directional commitment rather than installed capability. Respondents are senior executives - all director-level or above - from publicly listed manufacturers across North America, South America, Europe, Asia, and the Middle East. The global industrial manufacturing sector is valued at approximately $16 trillion, and the scale of the projected transformation is consistent with a sector under simultaneous pressure from labor cost volatility, reshoring mandates, and the maturing cost curve of industrial robotics and AI.
The Divide: Future-Fit Leaders vs. Everyone Else
The most strategically significant finding in PwC's report is not the aggregate forecast - it is the widening gap between a leading cohort and the rest of the industry.
PwC identifies a "future-fit" group: the fastest, most agile, and most innovative 20% of surveyed companies. Their current automation rate stands at 29%, versus just 15% for other manufacturers. By 2030, future-fit companies expect 65% of their key processes to be highly automated, versus 45% for other manufacturers.
These leaders are also more likely to integrate advanced technology across the value chain. 46% of future-fit companies use advanced tech in product design and development, versus 34% for other companies; 37% use it in production and operations, versus 28% for others.
What separates them is not the tools they deploy - it is how those tools work together. As Ryan Hawk, Global Industrials and Services Leader at PwC US, stated: "As automation becomes ubiquitous, the advantage shifts from who has tools to who can orchestrate them across the enterprise."2"As automation becomes ubiquitous, the advantage shifts from who has tools to who can orchestrate them across the enterprise."
Future-fit companies combine clean data, interoperable systems, and organizational cultures that learn quickly. The result: they reallocate capital and adopt new applications faster than competitors - and those advantages are self-reinforcing.
| Metric | Future-Fit (Today) | Other Manufacturers (Today) | Future-Fit (2030) | Other Manufacturers (2030) |
|---|---|---|---|---|
| Highly automated processes | 29% | 15% | 65% | 45% |
| Advanced tech in product design | 46% | 34% | Projected heavy use | - |
| Advanced tech in production/ops | 37% | 28% | 76% (all) | - |
Regional Competitive Dynamics
The automation surge will not be geographically uniform. Regional differences in workforce structure, policy environment, and industrial base will shape where the gains - and the disruption - prove most acute.
North America is pursuing automation aggressively to offset skilled labor shortages and onshoring pressures. According to Grand View Research3According to Grand View Research, the region faces a persistent shortage of skilled manufacturing labor, accelerating automation adoption to fill the gap. North America also leads in cloud-based manufacturing infrastructure, accounting for nearly 50% of the global share in 20244nearly 50% of the global share in 2024.
Europe, anchored by Germany's Industry 4.0 program, focuses automation investment on quality, traceability, energy efficiency, and regulatory compliance. European manufacturers are shifting national labor policy from passive support to active retraining, with several countries restructuring public employment agencies to prioritize skills transition.
Asia-Pacific drives volume and velocity. China alone installed the majority of new industrial robots globally in 2024, and the APAC region is projected to be the fastest-growing automation market. However, skills gaps remain a material constraint5skills gaps are a material constraint: demand for control engineers, robotics specialists, and software integration experts significantly outpaces supply across the region.
The Labor Market Equation
The workforce implications of PwC's forecast extend well beyond headcount. The shift is qualitative as much as quantitative.
McKinsey research6McKinsey research projects that by 2030, time spent using advanced technological skills will increase by 50% in the United States and 41% in Europe, while demand for physical and manual skills declines. Advanced IT and programming skill requirements could grow as much as 90% between 2016 and 2030. Separately, McKinsey's future-of-work modeling7McKinsey's future of work modeling estimates that approximately 27% of current work hours in Europe and 30% in the United States could be automatable by 2030, accelerated by generative AI.
For metalworking and fabrication operations specifically, this signals role transformation more than mass displacement: CNC operators expand into process monitoring and exception management; welding technicians take on cobot supervision; quality inspectors work alongside AI-driven vision systems. The critical challenge is ensuring training programs keep pace with deployment timelines - a challenge that PwC's own data suggests many manufacturers are not yet equipped to meet.
PwC's report flags skills gaps, fragmented data infrastructure, and organizational friction as the primary headwinds slowing adoption for manufacturers outside the future-fit cohort.
Headwinds: Cybersecurity, Skills, and Capital Access
Three structural constraints threaten to widen the gap between leaders and laggards.
Cybersecurity has emerged as the most acute operational risk accompanying automation scale-up. Manufacturing accounted for 27.7% of all cybersecurity incidents in 2025, marking the fifth consecutive year the sector led all industries, according to IBM's 2026 X-Force Threat Intelligence Index. The IT/OT convergence that enables connected, data-driven production also creates new attack surfaces. A September 2025 cyberattack on Jaguar Land Rover4nearly 50% of the global share in 2024 halted production for a month, generating an estimated $260 million in cybersecurity costs alongside hundreds of millions in production losses. In 2025, 51% of manufacturers fell prey to ransomware, with the average ransom reaching $1 million and average recovery costs (excluding the ransom) approaching $1.3 million.
Skills gaps remain the most commonly cited barrier to automation deployment. Demand for control engineers, robotics integration specialists, and data analysts continues to outpace supply across all major manufacturing regions. Workforce dynamics in North America8Workforce dynamics in North America are pushing companies to rethink production models, but training pipelines remain underdeveloped relative to the pace of investment.
Capital access disadvantages mid-market manufacturers most acutely. Global incumbents can absorb multi-year automation capex cycles and sustain parallel investment in cybersecurity and workforce development. Smaller and mid-market fabricators often cannot. For these operators, the near-term imperative is phased investment prioritization: targeting automation at the highest-impact process steps first, rather than attempting enterprise-wide transformation simultaneously.
What Executives Should Monitor Now
The PwC forecast implies a near-term planning horizon - not a 2029 problem. Three areas warrant immediate attention:
Capex planning and phasing. 70% of executives in PwC's survey rated "developing new capabilities internally" as their top means of accessing growth opportunities. Capital plans should sequence automation investments alongside data infrastructure upgrades - deploying robotics into fragmented legacy environments without integration capability will limit returns.
Training program architecture. The skills required to operate and maintain highly automated environments differ substantially from current workforce profiles. Organizations that begin structured upskilling now - in PLC programming, cobot operation, data interpretation, and OT cybersecurity basics - will retain competitive staffing advantages as the labor market for these roles tightens further.
Vendor ecosystem selection. As manufacturers increasingly position themselves as providers of integrated solutions combining hardware, software, data, and services, vendor interoperability becomes a strategic criterion, not merely a procurement consideration. 44% of total industrial manufacturer revenue is projected to come from outside traditional product manufacturing by 2030, per PwC. Vendor ecosystems that support outcome-based models and data-sharing architectures align better with this trajectory.
For a detailed analysis of how automation adoption is reshaping ROI calculations and investment return timelines in metalworking specifically, see our coverage on automation ROI, skills, and policy implications.
The Bottom Line
PwC's forecast does not predict smooth, universal progress. It forecasts divergence. Manufacturers that treat AI and automation as an integrated enterprise capability - not a set of isolated projects - will capture compound advantages in productivity, talent, and market positioning. Those that delay, or invest without the data infrastructure and workforce readiness to extract value, risk falling into a laggard tier from which recovery becomes progressively harder.
The doubling of automation by 2030 is, in that sense, less a technology story than a strategic execution story. The question for every plant manager, production engineer, and capital allocator is not whether the transformation is coming - it is whether their organization is positioned to lead it or respond to it.
FAQ
What exactly does PwC mean by "highly automated processes"? PwC's survey defines highly automated processes as those in which advanced technologies - including industrial robotics, AI-driven analytics, and integrated control systems - manage the majority of operations with limited manual intervention. This spans physical production, data capture, quality inspection, and back-office functions.
How does the 2030 automation forecast affect mid-market fabricators differently than large OEMs? Mid-market manufacturers face the same competitive pressure but with more constrained capital budgets and thinner internal IT/OT capabilities. The practical implication is a need for more selective, phased investment - prioritizing the highest-return process steps first - and greater reliance on external system integrators and vendor-managed automation solutions.
What skills will be most in demand as factory automation expands? According to McKinsey research, advanced IT and programming skills will see the fastest demand growth, potentially increasing 90% by 2030. For shop floor roles specifically, the highest-priority capabilities include PLC and cobot programming, industrial data analysis, vision-system operation, and OT cybersecurity awareness.
Is cybersecurity investment a prerequisite for automation expansion? Operationally, yes. As IT and OT systems converge through automation upgrades, the attack surface grows substantially. IBM's 2026 threat data shows manufacturing as the most-targeted sector for five consecutive years. Organizations scaling automation without a concurrent OT security program materially increase their operational and financial risk exposure.
What should executives prioritize in the next 12 months given this forecast? PwC's data and supporting research point to three immediate priorities: (1) audit current automation and data infrastructure maturity against 2030 targets; (2) design and fund a structured workforce upskilling program tied directly to planned automation deployments; and (3) conduct an OT cybersecurity assessment to identify and remediate the highest-risk vulnerabilities before new connected systems go online.
