In light of insights from part one of Alithya’s 2026 Manufacturing Trends and Analysis Survey, manufacturing leaders are entering 2026 with a strong sense of confidence. Most believe their organizations are well positioned to adapt to market shifts over the next three years and navigate ongoing digital transformation in the manufacturing industry. Yet beneath this optimism, key economic signals tell a different story. The ISM Manufacturing PMI reflects activity across new orders, production, and employment. It has remained below the 50 threshold for much of the past two years, indicating that the manufacturing industry is contracting, despite continued investment in digital transformation initiatives.
This contrast highlights a growing disconnect between perception and operational reality. Ninety-three percent of manufacturing leaders say they're confident in their ability to adapt, yet the broader environment suggests that real time data, productivity, and overall manufacturing performance are not evolving at the same pace. In many organizations, legacy systems, limited integration, and unclear return on investment continue to slow progress.
That's the central tension of manufacturing today. An industry that believes it is ready for what's coming, operating inside an economy that's quietly signaling otherwise.
Alithya's 2026 Manufacturing Trends and Analysis Survey explored this gap, revealing a sector that has moved beyond questioning the need for digital transformation and is now facing a more complex reality: how to scale digital transformation in manufacturing while improving efficiency, reducing cost, and building a sustainable competitive advantage.
Confidence vs capability: the real challenge in manufacturing transformation
- Confident in adaptability: 93%
- Actually agile (Deloitte): 48%
- ISM PMI (Contracting): <50
Optimism is real. Thirty-nine percent of survey respondents describe themselves as "very confident" in their ability to adapt; another 54% say "somewhat confident." These are not leaders in denial. Many of them have invested heavily in automation, analytics, and AI pilots that are already delivering measurable results and improving operational efficiency.
But confidence and capability are not the same thing. Research from Deloitte shows that only 48% of manufacturers believe their operating model is truly agile enough to respond rapidly to change. This gap reflects deeper challenges related to legacy systems, fragmented data, and limited integration across the enterprise. As a result, organizations may appear ready on the surface, while still lacking the foundations required to scale digital transformation in a sustainable way.
Four barriers slowing digital transformation in manufacturing
The desire to adopt is not the problem. Sixty-nine percent of leaders rank digital automation and AI as their top strategic priority. Across the manufacturing industry, digital transformation initiatives are already underway, with organizations investing in advanced technologies to improve efficiency and remain competitive.
The problem is execution. Moving from pilot initiatives to scalable, enterprise-wide transformation remains a significant challenge. The survey identified four barriers that are stalling progress and, notably, they are not purely technical. They reflect deeper operational and organizational constraints that limit the ability to translate investment into measurable results.
1. High implementation costs slowing digital transformation - 65.4%
Implementation costs remain the single largest obstacle. More importantly, these concerns are closely tied to broader uncertainty around value and return on investment, making organizations more cautious in scaling their transformation efforts.
2. Workforce and skills shortages limiting transformation - 42%
This challenge reflects a broader global trend. The World Economic Forum reports that 74% of manufacturing companies face significant skill shortages when deploying new technologies. At the same time, an estimated 39% of today’s skills will be outdated by 2030, creating a growing gap between the capabilities organizations need and those they currently have.
3. Legacy systems constraining digital transformation - 41%
Outdated infrastructure continues to limit progress. Layering AI onto systems built for a previous era rarely delivers meaningful results. In many cases, organizations must first modernize their enterprise architecture to enable integration, improve data flow, and unlock the full value of new technologies.
4. Unclear ROI delaying digital transformation investments - 36%
Unclear ROI remains a key barrier. Without a well-defined value proposition, organizations struggle to justify investment, turning every initiative into a perceived risk.
Addressing these barriers is only part of the challenge. To scale transformation, organizations must also rethink how they develop and apply critical capabilities.
Why AI and data skills alone are not enough in manufacturing transformation
When asked which capabilities will be most critical over the next three years, manufacturers point to AI and machine learning literacy and data analytics as the top priorities, followed by advanced manufacturing operations and cybersecurity. These capabilities are increasingly seen as foundational to digital transformation in the manufacturing industry, enabling organizations to leverage real-time data, improve operational efficiency, and support more informed, data-driven decision making across the enterprise.
Technical literacy without business context creates noise, not value
Consider what happens when a worker equipped with AI-driven insights notices an anomaly on the shop floor. Understanding what it means, whether it will disrupt raw material availability, trigger rush reorders, or require overtime to meet a customer deadline, requires business judgment that no algorithm provides on its own.
This is the gap that separates organizations getting real value from AI from those generating dashboards that nobody acts on.
AI literacy delivers its return only when it's paired with critical thinking to apply insights within the specific context of the business. Without that pairing, small operational issues cascade into missed profitability targets.
Rising risks in manufacturing: AI disruption and cybersecurity threats
As manufacturers accelerate their digital programs, two risks are rising faster than the defenses being built against them.
- AI Disruption: 38% (most underestimated force)
- Cybersecurity Threats: 36.7% (manufacturing is #1 target globally)
Together, these account for nearly three-quarters of the concerns raised, reflecting a strong consensus that the industry is moving faster than its risk management frameworks can keep pace.
The cybersecurity concern is particularly urgent. IBM's X-Force 2025 Threat Intelligence Index confirms that manufacturing is now the most targeted sector for cyberattacks globally. And while firms are deploying AI agents at scale, many lack the governance frameworks to manage them. The gap between rapid adoption and lagging security infrastructure is not a theoretical risk; it is an active vulnerability.
How digital transformation initiatives create value beyond cost savings
One finding from the survey deserves attention because it challenges a common assumption: digital modernization, when strategically aligned, creates value well beyond the cost savings that typically justify the investment.
Consider how digital transformation initiatives extend beyond their initial objectives. While many manufacturers invest in modernization to reduce operational costs, the impact often goes further. Organizations frequently report improvements in customer experience driven by faster, more consistent interactions, supported by better integration of data and systems.
These gains also create new opportunities for growth. With access to more contextual, real-time insights, teams are better positioned to identify revenue opportunities, strengthen customer relationships, and turn everyday interactions into moments of added value.
This is the ripple effect of well-executed digital modernization. Improvements in one area unlock value in areas nobody planned for. It's a pattern that applies equally in B2B and B2C manufacturing environments.
The 2026 manufacturing imperative: closing the gaps in digital transformation
Manufacturing in 2026 is not an industry debating whether to transform. That question is settled. The question now is whether organizations can close four foundational gaps fast enough to capitalize on the technologies they've already committed to:
- Workforce development: bridging the acute skill gap, with 85% of employers planning to upskill their teams over the next three years.
- Data readiness: moving from isolated data sets to integrated, actionable intelligence that drives decisions, not just reports.
- Legacy system modernization: addressing the 41% of firms still constrained by infrastructure built for a previous era.
- Cross-enterprise integration: ensuring technology investments serve the broader business strategy, not just individual departments.
The manufacturers that strengthen these foundations will be the ones who turn confidence into capability. The rest will discover the hard way that believing you are ready and being ready are not the same thing.
From insight to impact: advancing manufacturing transformation with Alithya
This article is based on Part 1 of Alithya’s 2026 Manufacturing Trends and Analysis series. Part 2, which explores specific technology adoption patterns and the emerging role of AI agents in production environments, will be published later this Spring.
To discuss how these trends apply to your manufacturing operation, contact Alithya’s manufacturing experts. As a trusted partner, Alithya helps organizations navigate complex transformation initiatives, improve operational efficiency, and unlock sustainable profitability,
The manufacturers that succeed will not be those who invest the most; but those who align technology, data, and operations to turn transformation into measurable business outcomes.