How industrial manufacturing organisations can maximise AI to get ahead

As disruption becomes a constant in industrial manufacturing, legacy systems are proving too rigid to keep up with today’s demands—let alone tomorrow’s. A 2025 Deloitte report found that 92% of those surveyed say smart manufacturing is critical to staying competitive, yet many remain dangerously exposed. Outdated systems, fragmented data, and rigid processes are leaving them vulnerable in a market that demands speed, agility, and resilience.

As supply chain volatility intensifies, trade policies shift overnight, and customer expectations continue to rise, outdated systems simply can’t keep up. They weren’t built for rapid change and certainly not for the agility that today’s economic landscape demands.

Manufacturers are stuck firefighting with tools designed for stability, not disruption. A recent Deloitte study found that of all available smart manufacturing technologies, artificial intelligence (AI) is seen as delivering the highest impact on business outcomes. But while the opportunity is clear, the ability to scale effectively remains elusive for many.

This is what we call the “value void” —the gap between technology investments and realising tangible business productivity gains. And the risk is real. Those who fail to modernise (fast) will lose operational efficiency and inevitably fall behind more agile competitors who are already using AI turn volatility into value.

Real-world AI applications that are making an impact

AI has gone far beyond the experimental phases and is now fully operational. In industrial manufacturing, machine intelligence is reaching new maturity levels, offering tangible value across a wide range of use cases.

AI-powered tools are already being used to:

• Automate manual workflows, freeing up skilled staff for higher-value work
• Translate technical documentation quickly and accurately across global teams
• Summarise complex projects, assess at-risk timelines, or anticipate supply issues by analysing capacity, demand, and resourcing data
• Predict maintenance and equipment failures before they happen, reducing downtime and extending machine lifespans
• Forecast inventory needs based on historical patterns and market shifts

What ties these capabilities together is speed. Delays cost time, but AI gives manufacturers the ability to act with confidence, turning real-time data into real-world advantage.

The missing piece of AI adoption

Most industrial manufacturers recognise AI’s potential, but realising it at scale is a different beast. AI relies on vast, high-quality data sets, typically captured through machine sensors and enterprise systems. Without the right foundational technology in place, that data remains fragmented and underutilised.

Many industrial manufacturing organisations have adopted enterprise resource planning (ERP) systems to manage operations. Yet too often, these solutions lack the industry-specific capabilities needed to support AI-powered workflows. Whether operating in engineer-to-order, make-to-stock, or discrete production environments, manufacturers need platforms that support multi- or single-mode operations and reflect the realities of their production processes.

That’s where micro-vertical capabilities come in. Built-in best practises tailored to specific manufacturing modes enable faster implementation while ensuring that AI is fed with the right data from the right processes. As a result, you get a more intelligent operation that adapts in real time to shifting demand, resource constraints, and production complexity.

Bridging the gap between ambition and outcome

For many industrial manufacturers, the ambition is there but results just aren’t keeping pace. That’s the value void in action. Closing it means integrating AI into a wider digital ecosystem rather than treating it as a bolt-on solution.

Our global research into 500 industrial manufacturers shows that the most productive organisations are embedding AI across operations to amplify agility, accelerate innovation, and unlock real value. They combine predictive intelligence with automation, process optimisation, and smarter data foundations to respond faster and make better decisions, all at scale.

With 76% of industrial manufacturing organisations expecting a productivity increase of 20% or more from technology investments in the next three years, our research shows a clear opportunity. The ones who succeed will be those who focus less on implementing isolated tools and more on building the intelligent infrastructure that makes real transformation possible.

Discover how possible happens

The most productive industrial manufacturing organisations aren’t those who adopt AI just for the sake of it. They apply it within a broader, smarter transformation strategy in place. When backed by industry-specific systems, automation-ready processes, and clean, connected data, AI can drive a measurable shift in productivity, agility, and decision-making.

But without the right infrastructure, AI’s potential risks going unrealised. To avoid falling into the value void, organisations must move beyond point solutions and partner with technology providers who understand the complexities of industrial manufacturing, from multi-mode operations to market unpredictability.

Download our exclusive report to learn how Infor™ AI solutions, built for industry-specific needs, are helping the most productive manufacturers close the value void and lead operations with real-time data intelligence.