The first of our 2026 Manufacturing Modernization webinar series delved into the external pressures manufacturers are currently facing, particularly around the push to fast-track artificial intelligence (AI). Sustainable digital transformation calls for coordination across strategy, governance, operations, data, technology, and workforce adoption. Many manufacturing executives don’t seem to be lacking ideas, but they’re struggling with converting pilots into measurable business value. Modernization efforts should be governed as business initiatives, anchored in specific outcomes, supported by trusted data, and sequenced through a practical road map that balances near-term wins with long-term scalability. During the webinar, we polled more than 300 professionals regarding their challenges on their digital transformation journey.*
This article will explore the results from the five polling questions, along with a breakdown of responses, and strategies to consider on these critical issues.
Where is your organization today in its manufacturing digital transformation journey?
The majority polled responded that they’re still early in the journey, with 61% indicating they’re “Just Exploring.” Another 13% reported having a defined business case or road map, while 10% were still running pilots. Only 8% were scaling across sites or lines, and another 8% optimizing with data and AI. These results suggest a market that’s still largely in the definition-and-prioritization phase, with a smaller but meaningful segment already moving into implementation and optimization. Manufacturing leaders who move beyond exploration and establish a clear road map, governance framework, and repeatable approach to execution will likely be better positioned to keep pace with technological advancements.
What is the number one business outcome driving your modernization efforts right now?
Revenue growth was the most frequently selected at 35%. However, 22% indicated they weren’t sure of a defined business objective. These results were followed by margin protection at 17% and resilience regarding supply chain, uptime, and the workforce at 16%. Quality, compliance, and traceability represented 10%. This reinforces the idea that the leading modernization narrative is growth and performance, while the relatively high responses in the “Other, Not Sure” category signal that many organizations are still calculating the return on investment (ROI) equation. Clarifying the value case and success metrics early and aligning transformation funding and sequencing to a small number of measurable outcomes, such as growth, margin, resilience, or compliance, will help set the groundwork for value recognition.
What is the biggest obstacle to scaling pilots to enterprise-wide impact?
Capacity limitations or funding issues were the top obstacles noted at 36%, while data readiness (quality, access, or standards) followed at 24%. Proving the investment is meeting goals (16%) and the challenge of change adoption across sites (15%) were comparable in magnitude. The status quo of technology was 9%. This points to a scaling gap for C-suite executives, driven primarily by investment capacity and data readiness rather than tool availability, suggesting that governance, funding models, and data foundations are the primary tools to help unlock enterprise-level impact. It’s important to address scaling challenges as an operating-model problem related to funding model, talent capacity, data standards, and rollout playbooks before expanding pilots across sites. Defining the investment and having a solid plan upfront before adoption creates a better chance for success early on.
Which governance model best describes how transformation and innovation decisions are made?
Operations-led prioritization was the most common model at 29%, with ad-hoc decisions by site or function close behind at 25%. Cross-functional innovation committees held a smaller role in decision making at 23%. According to some respondents, their information technology (IT) departments drive transformation efforts, representing 12% of the total. Transformation-office-led governance was reported by 11%. The results indicate many organizations are likely still operating with decentralized or semistructured governance, creating opportunities to strengthen operational alignment, funding discipline, and accountability to help improve repeatability and scale.
What is your top digital or technology investment priority for the next 12 to 18 months?
Attendees reported that AI, advanced analytics, including generative AI (GenAI), was the leading priority at 34% at their organizations, with a focus on automation and robotics following at 22%. Workforce is top of mind with people, skills, and change management close behind at 20%. Having a solid data foundation represented 16%, and shop-floor systems/enterprise resource planning (ERP) implementation was 8%. The results demonstrate a strong emphasis on AI-enabled value creation, but also a meaningful allocation toward workforce adoption and foundational data, highlighting the need to balance ambition (AI) with readiness (data and change). Manufacturers should balance AI ambition with execution readiness, investment in adoption, and data foundations to help ensure AI programs deliver sustained enterprise value.
Building a Foundation for Digital Transformation
Manufacturing is at an inflection point. The challenges facing organizations today, whether it’s technology adoption, labor shortages, the volatility of the supply chain, rising costs, or geopolitical risks, all have significant impacts on the business. This new operating reality means digital transformation isn’t an option any longer. It’s the new growth mandate.
The focus needs to be on the foundational elements that go along with a successful digital business transformation, and it starts with governance. Organizations should look at it from not only the technology angle but from a people, process, and change management perspective as well. Who is going to decide where the drivers are and who will pay? Organizational leaders need to work together across teams to measure success and move from pilot phase to rollout with defined expectations on ROI and long-term value. It goes beyond installing new technologies, but actually modernizing how people work, how decisions are made, and how data flows. Starting with governance, agreeing on goals and trials, and moving on to implementation, there needs to be a clear plan across site lines. This will help move the digital transformation journey into a unified movement to change how your organization grows. A few strategies to consider:
- Establish strong governance and clear ownership so transformation efforts are prioritized, measured, and tied to business outcomes rather than scattered pilots.
- Align people, process, technology, and data because successful digital transformation depends on more than new tools. It also requires process improvement, workforce readiness, and trusted data.
- Start small, prove value, and scale deliberately by focusing on high-impact use cases, measuring ROI, and reinvesting early wins to build momentum toward broader transformation.
How Forvis Mazars Can Help
Our Manufacturing team has extensive experience across a wide range of industries, and we can deliver tailored services to help meet your unique needs. If you’d like to discuss a particular topic, such as AI use cases, incident response, data-driven insights, or would like more information on our services to help your organization prepare for what’s next, please reach out to a professional at Forvis Mazars.
Watch the recording of “Manufacturing Modernization: Digital Transformation Now” on demand anytime for additional insights.
- *Data was collected from approximately 300 individuals who attended our “Manufacturing Modernization: Digital Transformation Now” webinar on April 28, 2026 and answered several polling questions. Most middle-market companies represented were manufacturing organizations, but others spanned various industries with an interest in the state of the manufacturing industry. Participants were nearly evenly split between associate/manager/supervisor level and participants holding higher positions, listing themselves as directors, assistant controllers/controllers, C-suite, and VP/executive directors. Only people who responded were included in the results shown.