How Pragmatic AI is Reshaping Modern Manufacturing ?
In today’s manufacturing landscape, the question is no longer whether digital tools and AI can contribute meaningfully to industrial processes, but how they can be integrated in ways that are both practical and transformative. The urgency is clear: amid volatile supply chains, increasing pressure to innovate, and a shortage of skilled labor, industrial companies need smarter ways to bring products to market faster, more efficiently, and more sustainably.
The use of artificial intelligence in manufacturing is rising, yet there remains a significant gap between what is technologically possible and what is pragmatically implemented. According to Bitkom, approximately 42 percent of German industrial companies are now using AI productively, a step forward from previous years, but still modest compared to international benchmarks. The European Commission estimates that companies in China and the United States invest three to four times more in AI technologies than their European counterparts. However, a recent McKinsey study suggests that the potential productivity gains in manufacturing through AI-supported applications are substantial: in Germany alone, up to €585 billion in additional value creation could be unlocked by 2040.
At assemblean, we believe unlocking this potential doesn’t require waiting for the next groundbreaking technology. Instead, it calls for a grounded, hands-on approach to integrating AI into existing workflows, one step at a time. Our daily work with industrial partners shows that pragmatic digital solutions can significantly accelerate development cycles, optimize resource use, and reduce dependency on volatile supply chains.
The path from concept to component: A digital paradigm shift
Traditionally, the path from a product idea to a manufacturable component has been long and complex, filled with coordination loops, handoffs, and time-consuming feasibility analyses. It is a process that often stretches over weeks or even months, delaying innovation and inflating costs.
This is precisely where we see enormous potential for AI to add value, not by replacing engineers or designers, but by supporting them with intelligent tools that simplify routine decisions and accelerate early-stage development. With our internally developed platform, companies can digitally specify components or entire assemblies based on design intent. Our AI-powered configurator generates 3D visualizations, assesses technical feasibility, and produces preliminary cost calculations within minutes.
The result is that what once took weeks can now be achieved in hours or even minutes. Once specified, components can be seamlessly transferred to our in-house production system or routed through a network of vetted manufacturing partners. This not only reduces development times dramatically but also creates new flexibility in prototyping and small-batch production, where traditional processes often struggle.
This digital-first approach has proven particularly valuable in scenarios where speed, adaptability, and customization are critical. By enabling a rapid shift from concept to component, companies can respond faster to market demands and bring innovations to life without the traditional overhead.
Digital tools are only as good as the data behind them
Despite the promise of AI, the effectiveness of digital solutions hinges on a fundamental prerequisite: structured, accessible, high-quality data. Many manufacturing companies already collect vast volumes of data across their operations, yet these datasets are often siloed, inconsistent, or incompatible across systems. Fragmented IT/OT landscapes, proprietary formats, and a lack of standardized interfaces frequently prevent organizations from leveraging this data meaningfully.
In our experience, the will to digitize is often present. What is missing are concrete, manageable steps toward integration that work within the realities of ongoing operations. That’s why we advocate a modular, iterative approach to digital transformation: start small, demonstrate value, and scale based on tangible outcomes. Instead of pursuing monolithic, all-or-nothing digital initiatives, companies should focus on embedding intelligence into the processes that matter most, where the impact is both immediate and measurable.
For example, integrating AI into the inquiry and costing process of component manufacturing does not require a complete overhaul of existing infrastructure. With the right APIs and data-mapping strategies, even legacy systems can be opened up and made interoperable. The key is to view digitalization not as a one-time project but as a continuous, learning-oriented evolution.
Human–machine collaboration: the real strength of industrial AI
One of the most common misconceptions about AI in manufacturing is the belief that it will replace skilled human labor. In reality, the most effective applications of AI are those that augment human capabilities rather than substitute them. At assemblean, we see AI as an assistant that takes over repetitive, time-consuming tasks, freeing engineers and designers to focus on creativity, innovation, and problem-solving.
AI can rapidly evaluate multiple design variants for feasibility and cost, suggest alternatives based on material availability, or flag potential production bottlenecks, but the final decisions remain with experienced professionals. This symbiotic relationship between human expertise and machine intelligence is not only more productive, it is also more trustworthy.
Ultimately, robust and responsible implementation of AI in manufacturing depends on people: those who understand the processes, those who design the systems, and those who use them effectively. Investing in training, change management, and cross-disciplinary collaboration is just as important as investing in algorithms or hardware.
Resilience through responsibility: technology meets trust
As the manufacturing industry grapples with increasing uncertainty (from geopolitical shifts to energy cost volatility to stricter regulatory demands) the need for resilient, adaptive systems is more pressing than ever. Digital tools can play a crucial role in enabling faster response times, better forecasting, and more robust production planning. But resilience is not just a technological question; it is also about trust, responsibility, and organizational culture.
To build a truly resilient industrial future, we must combine the power of AI with a deep commitment to transparency, data governance, and ethical design. At assemblean, we embed these principles into our platform architecture and our partnerships. We believe that digital systems must not only deliver performance but also inspire confidence: users should understand how decisions are made, what data is used, and how their input shapes outcomes.
This approach fosters not only operational efficiency but also strategic alignment. When digital tools are deployed with clarity and accountability, they become enablers of long-term success, not just short-term gains.
A vision for the future: democratizing industrial innovation
Looking ahead, we envision a future in which industrial innovation is not limited to large corporations with massive R&D budgets, but is accessible to startups, SMEs, and collaborative ecosystems. By lowering the barriers to entry for advanced manufacturing processes, AI-powered platforms like ours can help democratize innovation across the value chain.
This means providing tools that are intuitive, interoperable, and adaptable to diverse production environments. It means designing solutions that scale from one-off prototypes to full-scale production without compromising quality or compliance. And it means creating systems that empower people at all levels of an organization to contribute to smarter, faster, and more sustainable manufacturing outcomes.
In this spirit, we at assemblean are not just building software. We are building a new mindset, one that views digital transformation as an opportunity for collaboration, creativity, and continuous improvement. By bridging the gap between concept and component, between data and decision, and between technology and people, we believe the next era of manufacturing is not only possible, it is already in motion.
About the author: Alexander Pöhler
Alexander Pöhler is co-founder of assemblean GmbH, a digital production platform that helps companies bring innovative products to market faster and more efficiently. With expertise in manufacturing, digitalization, and business development, he drives assemblean’s mission to rethink industrial contract manufacturing and make it more accessible to the German economy.
