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Unlocking AI’s Full Potential in Manufacturing Key Industry Insights

2026 Artificial Intelligence Research

TABLE OF CONTENTS

Introduction

Efficiency Gains Are Visible, But the AI Opportunity Is Bigger

Industry-Specific AI Is Helping Manufacturers Improve Product Delivery

An AI Journey: Moving Towards Whole Process Automation

European Manufacturers Need Stronger Safeguards to Scale AI With Confidence

Conclusion

Unlocking AI’s Full Potential in Manufacturing | 2026 Artificial Intelligence Research

Introduction

FROM THE FIELD

Manufacturers are under constant pressure to deliver on customer commitments made before production begins. Material shortages, capacity constraints, and quality issues can quickly become rework, margin erosion, and missed shipment dates. In this environment, the value of artificial intelligence (AI) is often easiest to see in operational areas such as scheduling, throughput, quality, and productivity.

Throughout this summary, you’ll find insights from Aptean subject matter experts who work directly with manufacturing customers and prospects every day. Their perspective adds real-world context to the data that follows.

But an efficiency-led view can narrow the AI business case. To unlock better outcomes, manufacturers need to use AI not just to optimise existing processes, but to improve customer communication, reduce fulfilment risk, protect margin by order, and support faster product delivery. This is the shift from efficiency to operational agility: giving teams the right information before an exception becomes a customer problem. To better understand how the manufacturing industry is approaching AI, Aptean partnered with research specialist Vanson Bourne to survey 300 executives within the manufacturing sector across both process and discrete operations. This was part of a broader study of 1,535 business leaders across five sectors, exploring the challenges and opportunities they face. The study also included a number of in-depth interviews to uncover the specific use cases utilised in the industry today.

Key Findings

Almost half (48%) of manufacturing businesses were motivated to adopt AI by the opportunity to improve operational efficiency, while just 13% cited the ability to enhance wider business outcomes.

Manufacturers were the least likely to have adopted industry-specific AI solutions (45%) of all sectors surveyed.

Organisations that have adopted industry-specific AI are more likely to report faster product or service delivery (46% vs. 39%) and stronger competitive positioning (35% vs. 29%) over the past 12 months than those using general-purpose AI solutions.

Unlocking AI’s Full Potential in Manufacturing | 2026 Artificial Intelligence Research

Efficiency Gains Are Visible, But the AI Opportunity Is Bigger

For manufacturers, efficiency remains the main advantage of AI. Almost half (48%) of opportunity-led respondents say they were motivated to adopt AI by the prospect of enhancing operational efficiency, making this the vertical that’s most focused on that benefit. Meanwhile, only 1-in-10 (13%) were focused on wider business outcomes. This emphasis reflects the operational realities manufacturers manage every day: work orders, bills of materials (BOMs), routings, capacity plans, shop floor management, and on-time, in-full (OTIF) expectations. Even small improvements in scheduling, material availability, equipment usage, or rework reduction can protect margin and reduce firefighting. This is where AI is already making a measurable difference, with 47% reporting that AI has helped streamline operations over the past 12 months, above the cross-vertical average of 37%. While this efficiency focus is delivering measurable gains, the risk is that it becomes the whole story. Nearly two-thirds (64%) expect AI to have the greatest impact on operational efficiency and process optimisation over the next 12 to 18 months. But if AI is only judged by process optimisation, manufacturers may not tap into its potential to improve customer communication, reduce fulfilment risk, protect margin, and support faster product delivery. Efficiency should be the entry point, not the ceiling. However, the next steps depend on trust. Manufacturers are less likely than average to allow AI to make autonomous decisions in areas where the stakes are higher, especially customer-facing and strategic decisions. This suggests that while manufacturers recognise AI’s operational potential, many are still cautious about giving it the authority to act where decisions could affect customer relationships, brand reputation, or long-term business performance.

FROM THE FIELD

“Some companies think of AI as this omnipotent thing that drops into their shop floor and fixes things. AI requires development—it still has guardrails, it still has logic that needs to be built. It doesn’t do that by itself.” - Dmitry Kirshner, Senior Solutions Architect, Aptean, on the misconception that AI works without setup

Unlocking AI’s Full Potential in Manufacturing | 2026 Artificial Intelligence Research

FROM THE FIELD

“They’re a ‘show me’ group. They want to see success before they dive in—they’re not going to be the first ones to do it. They’re cautious until it’s proven that it’s giving them the results they’re looking for.” - Jim Tuttle, Senior Solutions Consultant, Aptean on manufacturers’ caution around autonomous AI decisions

Areas Where AI Is Granted Autonomy, Cross-Sector vs. Manufacturing 49%

46%

48% 40%

Forecasting & planning

Customer-facing decisions

44%

47%

42%

36%

35%

Tactical/ operational decisions

Average

Strategic decisions

36% 29%

Workforce-related decisions

30%

Financial decisions

Process & Discrete Manufacturing

Figure 1: For which of the following, does your organisation currently allow AI to make decisions autonomously (i.e. without human approval or input), if any? [1,501], Asked to those whose organisation is using or implementing AI

Unlocking AI’s Full Potential in Manufacturing | 2026 Artificial Intelligence Research

Industry-Specific AI Is Helping Manufacturers Improve Product Delivery For manufacturers ready to move beyond process optimisation, industryspecific AI is already showing where broader value can come from. These tools are designed around the realities of manufacturing operations. That makes them better equipped to support decisions that depend on manufacturing context, not just generic data analysis. Today, adoption remains relatively early. Manufacturers are the least likely industry surveyed to have adopted industry-specific AI tools (45%) and have lower-than-average adoption of custom-built AI solutions (39%). At the same time, 69% agree that general-purpose AI tools are insufficient for meeting the needs of large, complex operations—though that’s below the cross-sector average of 77%. However, where manufacturers are using industry-specific AI, the benefits are clear. Organisations using these tools are more likely than those using generalpurpose AI to report faster product or service delivery (46% vs. 39%) and stronger competitive positioning (35% vs. 29%) over the past 12 months. In an industry where missed shipment dates, quality issues, and margin leakage can quickly affect customer relationships, these gains show how specialised AI can help manufacturers turn operational improvement into business advantage.

FROM THE FIELD

“There is no such thing as an effective non-industry-specific AI for manufacturing. If you want to use AI, you can’t do anything sensible without heavy integration into your processes, your systems, and your engines. Otherwise, you’d only scratch the surface.” - Jörg Kastrup, Product Director, Aptean, on why industry-specific AI is a requirement, not a preference

Unlocking AI’s Full Potential in Manufacturing | 2026 Artificial Intelligence Research

FROM THE FIELD

“Is it the smart ones using AI, or is AI making them the smart ones? I think it’s probably a little bit of both.” - Jörg Kastrup, on what’s behind industry-specific adopters’ stronger results

Comparative AI Usage Across Verticals, by Type of AI 53%

49%

55% 47%

46%

45%

44% 37%

Verticalised AI

Fashion & Apparel

Equipment Dealers

39%

Custom-built AI Transport & Distribution

Food & Beverage

Process & Discrete Manufacturing

Figure 2: Which of the following types of AI is your organisation currently using or implementing? – General purpose AI solutions, industry-specific AI solutions designed for use cases in your specific industry/vertical? [1,501], Asked to those whose organisations are using or implementing AI

Unlocking AI’s Full Potential in Manufacturing | 2026 Artificial Intelligence Research

Areas of AI-Driven Improvement, Past 12 Months 46% 39%

35% 29%

Stronger competitive positioning

Faster product or service delivery General-purpose AI solutions

Vertical AI solutions

Figure 3: Which of the following areas has AI helped improve or strengthen the most in your organisation over the past 12 months, if any? [295], Asked to those whose organisation is using or implementing AI

FROM THE FIELD

“The first agents we built for our customers analyse and maintain bill-of-materials data and come back with recommendations. That’s the first place we targeted, because it’s probably the most—and least scary—use case for them.” -Andy Pickard, Senior Solutions Consultant, Aptean, on where manufacturers start their AI journey

Unlocking AI’s Full Potential in Manufacturing | 2026 Artificial Intelligence Research

An AI Journey: Moving Towards Whole Process Automation This U.S.-based organisation has applied industry-specific AI to its design management processes to help prevent costly design mistakes, accelerate product testing, and simplify their overall project management. “[We use AI in] identifying the right design... And once... developed, we will conduct a testing of the new components... AI helps to perform those tests... and provide a summary of the outcome.”, USA, $10.1-$50 billion, Senior Management These specialised AI tools have helped this organisation avoid costs and resource investments that would have otherwise been required to customise and build their own AI solutions, resulting in faster AI implementation and quicker benefit realisation. “We can implement [these tools] without any trial errors or customising. [It] helps to save [a] lot of effort and investments... we can adopt immediately and see the returns... quickly.”, USA, $10.1-$50 billion, Senior Management As a result of these positive gains, the organisation plans to move towards full end-to-end automation over the next year to increase efficiency and reduce costs. A particular focus is on being able to compare competing projects or priorities by using industryspecific AI to select those that would produce the greatest results.

FROM THE FIELD

“Most manufacturers don’t know what AI can do for them until they see it solve a problem they recognise. Show a plant manager an agent that catches a defect from a photo, and the response is always the same: ‘We deal with this all the time—sign us up.” -Dmitry Kirshner, on why manufacturers need to see AI solve a specific problem before they believe in it

“AI needs to analyse which project is more beneficial... in... increasing the revenues, [achieving] different KPIs... and provide a recommendation on which... is better, X versus Y.” USA, $10.1-$50 billion, Senior Management

Unlocking AI’s Full Potential in Manufacturing | 2026 Artificial Intelligence Research

European Manufacturers Need Stronger Safeguards to Scale AI With Confidence Regional differences show that manufacturers are not all starting from the same place. North American manufacturers are more likely than their counterparts in Europe (UK/FR/DE/NL) to say industry-specific AI has exceeded expectations (40% vs. 25%), suggesting the former group is already seeing stronger returns from more specialised tools. For European manufacturers, the challenge appears to be less about appetite and more about assurance. They are more likely to identify lack of governance as a major barrier to AI success (75% vs. 62% in North America). The country-level findings add further nuance. In the UK, 70% say ease and speed of implementation are key influences when securing budget for AI tools or solutions. In Germany, only 47% have implemented clear escalation and incident management procedures for AI errors, below the 60% vertical average. Building confidence will be key to moving AI beyond lower risk use cases. Stronger governance, clearer escalation procedures, and practical implementation support can help manufacturers apply AI in more business-critical areas.

FROM THE FIELD

“Other European countries have more stringent requirements when it comes to how customer data is handled. I’ve talked to customers who have real concerns. ‘Where’s this data going?’ Who’s going to be able to access it?’ Those concerns are often why they hesitate.” - Jim Tuttle, on the data security concerns behind Europe’s governance gap

Unlocking AI’s Full Potential in Manufacturing | 2026 Artificial Intelligence Research

Conclusion Manufacturers are already seeing AI deliver measurable efficiency gains, particularly in the operational areas where pressure is most visible. But the next stage of value will depend on whether manufacturers can move beyond process optimisation and apply AI to higher-value decisions that affect customers, margins, product delivery, and competitiveness. Industry-specific AI can help make that shift. By reflecting the realities of manufacturing operations—from scheduling and shop floor visibility to fulfilment risk and job profitability— these tools can support more relevant decisions and faster action. The opportunity for manufacturers is not simply to make existing processes more efficient. It is to build the confidence, safeguards, and industry-specific capabilities needed to turn AI into a driver of wider operational agility.

Want more insights from our survey of 1,535 business leaders around the world? Download The Reckoning, the story of our full 2026 Artificial Intelligence Research across five industries and six countries.

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Methodology Vanson Bourne surveyed 1,535 business decision makers about their organisation’s AI projects and strategies in Q2 2026, including 300 respondents in the manufacturing sector across both process and discrete operations. The study also included 10 in-depth interviews, with three from the manufacturing industry. All respondents came from organisations with a minimum of $10 million (USD) in global annual revenue and influenced decisions on enterprise resource planning (ERP) or supply chain systems. Countries included in the survey were USA, Canada, UK, Netherlands, France, and Germany.

Unlocking AI’s Full Potential in Manufacturing | 2026 Artificial Intelligence Research

Aptean

Vanson Bourne

Aptean is a global provider of industry-specific software that helps manufacturers and distributors effectively run and grow their businesses. Aptean’s solutions and services help businesses of all sizes to be Ready for What’s Next, Now®. Aptean is headquartered in Alpharetta, Georgia and has offices in North America, Europe and Asia-Pacific. To learn more about Aptean and the markets we serve, visit www.aptean.com.

Vanson Bourne is an independent specialist in market research for the technology sector. Our reputation for robust and credible research-based analysis is founded upon rigorous research principles and our ability to seek the opinions of senior decision makers across technical and business functions, in all business sectors and all major markets. For more information, visit www.vansonbourne.com.

09.01.26