AI, ERP and the future of manufacturing: why the foundations matter more than ever

Artificial intelligence is dominating conversations across manufacturing.

Every week there seems to be another story about AI transforming production, predicting equipment failures, improving supply chains or helping manufacturers make faster decisions. The promise is exciting. Lower costs, greater efficiency, better customer service and more resilient operations.

But there is one important detail often missing from these discussions.

The manufacturers seeing the greatest benefits from AI did not start with AI.

They started by building the right foundation.

They invested in connected processes, integrated systems, reliable data and modern ERP platforms. AI is now helping them get even more value from those investments. At Platned, we’ve seen this first-hand. Having worked with more than 100 manufacturing organisations, we’ve helped businesses modernise their operations with IFS Cloud, creating the connected foundations needed to improve visibility, simplify processes and prepare for practical AI adoption.

For manufacturers still relying on ageing systems, disconnected applications and manual processes, AI is not simply the next technology trend. It is becoming a compelling reason to modernise.

The reality behind successful AI projects

Many manufacturers are asking the same question:

“How do we start using AI in our business?”

The better question may be:

“Is our business ready for AI?”

AI depends on data. If information is trapped in spreadsheets, scattered across multiple systems or requires manual intervention to move between departments, AI cannot deliver its full potential.

Think about some of the most important moments in your business:

• A customer asks for an accurate delivery date.
• A supplier issue threatens production schedules.
• A quality problem needs immediate investigation.
• Critical equipment breaks down unexpectedly.
• Demand changes faster than forecasts predicted.

How quickly can your teams access the information they need?

How many systems must they check?

How much manual work happens before a decision can be made?

The answers often reveal whether an organisation has connected operations or a collection of disconnected tools.

Why disconnected systems create bigger problems

Many manufacturers have tried to modernise gradually.

A new reporting tool here. A specialist application there. A separate quality system. An additional maintenance platform.

At the time, these decisions often make sense. Each solves a specific challenge.

Over time, however, they can create a different problem.

Data becomes fragmented.

Departments develop their own version of the truth.

Reporting becomes difficult.

Integration becomes expensive.

Decision-making slows down.

This challenge is particularly common in organisations running legacy ERP systems or software portfolios built through acquisitions. What appears to be a single platform on the surface may actually consist of multiple products operating independently behind the scenes.

The result is often:

• Duplicate data.
• Complex integrations.
• Inconsistent user experiences.
• Increased security risks.
• Higher maintenance costs.
• Limited visibility across the business.

Most importantly, these issues make it much harder to introduce advanced technologies such as AI.

AI needs more than good intentions

There is a growing difference between organisations talking about AI and organisations successfully using AI.

The difference is usually not the AI itself.

It is the quality of the foundation underneath it.

For AI to deliver meaningful value, manufacturers need:

Connected data

AI works best when information flows across the organisation in real time.

Production, inventory, procurement, finance, quality and maintenance data must work together rather than exist in isolation.

A single source of truth

If different systems contain conflicting information, AI cannot confidently make recommendations or automate decisions.

Reliable outcomes depend on reliable data.

Scalable technology

AI processes large volumes of information continuously.

Legacy architectures designed for yesterday’s requirements often struggle to support modern AI workloads.

Without these foundations, AI risks becoming another standalone tool rather than a business-wide capability.

Manufacturing is moving beyond Industry 4.0

For years, Industry 4.0 focused on automation, connectivity and digitalisation.

Those principles remain important.

However, manufacturing is now entering a new phase.

Industry 5.0 shifts the conversation beyond technology alone and focuses on three key priorities:

Human-centric operations

Technology should support people, not replace them.

The goal is to help employees make better decisions, solve problems faster and focus on higher-value activities.

Sustainability

Manufacturers are under increasing pressure to improve efficiency while reducing environmental impact.

Technology plays a critical role in helping organisations monitor, measure and improve sustainability performance.

Resilience

Supply chain disruption, labour shortages and market volatility have highlighted the importance of adaptability.

Modern manufacturers need systems that help them respond quickly when conditions change.

This evolution is also creating opportunities for a new generation of AI-powered capabilities.

The rise of autonomous AI in manufacturing

Traditional AI helps people make decisions.

Autonomous AI goes a step further.

These systems can analyse information, make decisions and take action within defined rules and controls.

Examples already emerging across manufacturing include:

Predictive maintenance

AI can monitor equipment performance, identify potential failures and trigger maintenance activities before breakdowns occur.

Quality management

Computer vision and AI can identify defects, recommend corrective actions and continuously improve quality processes.

Supply chain optimisation

AI can help organisations respond to disruptions, manage inventory levels and optimise logistics decisions.

Production scheduling

Autonomous systems can balance workloads, adjust schedules and optimise resource utilisation in real time.

While fully autonomous factories remain a future vision for many organisations, the direction is clear.

AI is moving from providing insights to supporting action.

Why manufacturers are reassessing legacy ERP systems

Many manufacturing leaders recognise that their current systems may not be able to support future ambitions.

CIOs are concerned about technical debt, cybersecurity risks and limited flexibility.

COOs are focused on operational performance, throughput, quality and agility.

CFOs are evaluating return on investment, long-term costs and financial flexibility.

Across all three groups, similar concerns continue to emerge:

• Long and expensive upgrade projects.
• Limited integration capabilities.
• Vendor lock-in.
• Complex technology environments.
• Missed innovation opportunities.
• Growing pressure to support AI initiatives.

The challenge is no longer simply replacing ageing software.

It is about creating a digital foundation that supports the next decade of manufacturing innovation.

Building a platform for the future

The manufacturers gaining the most value from AI share several common characteristics.

They have:

• Connected operations.
• Integrated data.
• Real-time visibility.
• Flexible technology architectures.
• Platforms designed to evolve with the business.

Modern ERP platforms such as IFS Cloud are designed to support this approach by bringing together ERP, asset management, supply chain and service capabilities within a unified environment while providing embedded AI and automation capabilities.

Having supported more than 100 manufacturing organisations, Platned understands that successful modernisation is about more than implementing new technology. It is about helping manufacturers connect operations, improve visibility and build a platform that continues to deliver value as the business evolves.

The goal is not simply to replace one system with another.

The goal is to create an environment where data moves freely, decisions happen faster and new technologies can be adopted without creating additional complexity.

The opportunity for manufacturers

AI will continue to reshape manufacturing.

The organisations that benefit most will not necessarily be those with the biggest AI budgets.

They will be the organisations with the strongest foundations.

Manufacturers that invest in connected operations, reliable data and modern ERP platforms will be better positioned to adopt AI, automate processes and respond to changing market conditions.

Those that delay may find the gap between themselves and their competitors becomes increasingly difficult to close.

The conversation is no longer about whether AI will change manufacturing.

It already is.

The real question is whether your organisation has the foundation needed to take advantage of it.