Why the next leap in the manufacturing industry relies on on-the-ground expertise, not just strategy.
How the production environment has changed in 2025
Beyond internal challenges, the manufacturing landscape itself is evolving at a pace that would be difficult for any organization to absorb on its own. According to Industrial-Production.de, 2025 marks the early yet significant emergence of Industry 5.0, a phase defined not only by automation but by deeper collaboration between humans, machines, and environmental systems. AI is not treated as an accessory but as a fundamental capability binding these components together.
A significant shift is occurring as manufacturers transition from isolated AI tools to integrated architectures. In our own discussions with plant managers and owners, we see this change reflected in the growing interest in unified systems instead of fragmented, department-specific software. People want fewer platforms and more connected insights.
Sustainability is also becoming operational, not conceptual. Manufacturers are starting to use AI to identify real intervention points: energy anomalies, waste patterns, bottlenecks; rather than pursuing symbolic green initiatives. This largely aligns with what quality and safety teams tell us: "Show me where the real risk is, and I'll act."
Labor shortages add another layer of pressure. A study by The Manufacturer cited by Columbus Global reports that 97% of manufacturers are struggling to hire skilled labor. This reflects what we consistently hear, especially in food production: teams are overburdened, turnover is high, and knowledge is lost with retirements.
Decision-making is also shifting towards integrated analysis. Plants want fewer blind spots. They want incidents, inspections, maintenance logs, and machine data to tell a unified story. This is exactly what operational visibility platforms like Zeltask aim to offer.
Why AI pilot projects grow, but successful scaling doesn't
Across the industry, AI adoption is increasing at a remarkable pace. However, as explained in a report highlighted by TechMonitor, 56% of European manufacturers remain stuck in the pilot phase. Large companies are scaling slowly. Smaller companies are barely scaling.
Still, the momentum is undeniable. Silicon Saxony reports that 42% of German manufacturers already use AI in production, and another 35% intend to adopt it. In the UK, findings from Rockwell Automation show that 88% of manufacturers have invested or plan to invest in AI within the span of a year.
The global growth trajectory is even more spectacular. AI in manufacturing is expected to grow from $7.6 billion in 2025 to $62.33 billion by 2032, with Asia-Pacific leading its adoption. European companies are catching up, and use cases are becoming more diverse, ranging from production optimization to marketing and sales.
Importantly, results are measurable. McKinsey reports that companies applying machine learning are three times more likely to improve key performance indicators. PwC indicates that 98% of industrial companies expect digital technologies to improve productivity in the coming years.
This reflects what we observe in food and beverage plants: interest is high, potential is high, early results are promising, but scaling requires discipline, process preparation, and unity across all operational areas.
How Europe and Latin America are adopting AI differently
The evolution of AI adoption varies by region.
In Latin America, the transformation is primarily driven by workforce development. A regional report by SAP shows that 81% of large companies in Brazil and Colombia are already investing in AI training. Meanwhile, Nvidia is expanding major AI hubs in Brazil and Mexico, as reported by LatamRepublic, signaling its commitment to building local infrastructure and talent channels. In discussions with Latin American manufacturers, we often hear the same theme: "We need tools, but most importantly, we need people prepared to use them."
Europe, on the other hand, is investing heavily in infrastructure. The European Commission's creation of six new AI plants, backed by €500 million (Innovation News Network), demonstrates a strong institutional push towards AI-enabled industry. The advances by Fraunhofer in real-time AI monitoring and predictive quality systems show that applied research is progressing rapidly. However, Accenture's statistics remain a sobering counterbalance: more than half remain stalled in the pilot phase.
From Zeltask's perspective, after speaking with clients and partners in both regions, the differences are clear. Latin America is developing capabilities from the ground up. Europe is creating a top-down environment. Both approaches have their strengths, and both face the same scalability bottleneck.
Why digital tools only work when processes and people are ready
All sources, expert opinions, and conversations within factories lead us to the same conclusion:
Digital transformation only becomes real when it makes everyday work easier, safer, more consistent, or more reliable for the people running the plant.
This belief is deeply ingrained in how we approach Zeltask's work. The platform connects inspections, incidents, assets, maintenance tasks, and IIoT information in one place, not because it's elegant, but because operational teams constantly tell us they are tired of systems that don't communicate with each other.
They want traceability without paperwork, compliance without chaos, and insights without additional steps.
Technology alone doesn't solve problems. Understanding the workflow does, and that understanding comes from conversations in noisy production rooms and maintenance workshops, not from conferences.
Where AI can generate real operational improvements today
The future of industrial AI will not be defined by futuristic predictions. It will be defined by how deeply technology learns to understand the rhythms, constraints, and responsibilities of frontline operations.
The most significant advances emerging from Industry 5.0, from AI copilots to real-time sensor intelligence, revolve around this idea: helping people work smarter, not harder. Supporting technicians during breakdowns. Offering instant visibility to quality teams. Making regulatory compliance natural. Enabling managers to act with clarity instead of assumptions.
At Zeltask, this is the work we focus on every day: building an intelligent operations platform that helps plants reduce downtime, improve compliance, and strengthen continuous improvement by unifying maintenance, quality, and safety into a coherent system. It's not about digital transformation as a slogan. It's about the everyday work of making operations more reliable and more focused on people.
What manufacturers should focus on to successfully adopt digital technology
Manufacturing is entering a new era marked by artificial intelligence, analytics, demographic changes, sustainability pressures, and growing operational complexity. However, the companies that will stand out are not those that simply adopt new tools. They are those that respect the invisible work behind transformation: listening to frontline teams, understanding process variability, investing in adoption, and aligning technology with real workflows.
AI will transform the manufacturing industry. But only if we start where transformation truly happens: on the production floor.
And that is the place where Zeltask listens first, before designing, before building, and before implementing anything at all.
Article by
Felipe Borja
CEO & Co-founder
Published on
Nov 15, 2025
