Dimitar Dimitrov is the founder and Managing Partner at Accedia, a leading European IT services company.
The manufacturing industry is entering a new era of transformation, driven by technological advancements and the need for greater adaptability. As businesses face evolving global challenges, software innovation is reshaping traditional processes, creating opportunities for enhanced efficiency, sustainability and resilience.
By using insights from my own experience in the industry, I want to explore the key forces that will define the future of manufacturing in 2025 and beyond.
Prioritizing Sustainability With Green Software Engineering
Sustainability in manufacturing is no longer limited to physical processes; software plays a pivotal role in driving eco-friendly practices. In 2025, the focus will be on developing and deploying software solutions that help manufacturers achieve carbon neutrality, reduce waste and optimize energy consumption.
Manufacturing companies increasingly leverage software for real-time data tracking, enabling them to monitor energy use, reduce production waste and minimize emissions across operations. This shift can, therefore, streamline processes, allowing manufacturers to adjust energy consumption dynamically and prevent wasteful production practices.
Cloud infrastructure is another great example of the potential of green software engineering. Accenture’s research suggests that the carbon impact of migrating to the public cloud could be equivalent to taking 22 million cars off the road. Thus, embracing cloud solutions enables manufacturers to greatly lower their environmental impact while optimizing data storage and processing, contributing to a more sustainable future.
Additionally, Gartner predicts that by 2027, 30% of large global enterprises will include software sustainability in their non-functional requirements, up from less than 10% in 2024. This shift reflects a growing recognition of the role that software can play in achieving broader environmental goals.
For example, digital twins—virtual replicas of physical assets, systems or processes—are becoming more common. These digital models allow manufacturers to simulate and analyze their operations in real time, testing new approaches and optimizing processes before making changes on the factory floor. By doing so, they can reduce resource consumption, minimize waste and make more sustainable, data-driven decisions.
AI Powering Innovation And Growth In Manufacturing
AI is transforming the manufacturing industry, with 93% of manufacturers acknowledging that AI will be a pivotal technology driving growth and innovation in 2025, according to a Deloitte survey. AI is being applied in various areas, including smart production, product and service enhancements and business model decision making. Currently, smart production accounts for 51% of AI deployments in manufacturing, as companies leverage the technology to automate workflows, improve quality control and reduce downtime.
Around the world, countries are embracing AI with different strategies. For example, many Japanese companies have outlined a phased development plan to integrate data-powered AI across industries, promote its adoption among the public and ultimately create a connected AI ecosystem across multiple sectors. This global embrace highlights the potential of AI to revolutionize the manufacturing sector for good.
Over the years, I’ve witnessed firsthand how AI can transform manufacturing processes. One of Accedia’s most impactful projects last year involved helping a client struggling with unexpected equipment failures on their production line. By building an AI-based predictive maintenance solution that combined machine learning and computer vision, we were able to provide real-time insights into the health of their machinery. This allowed them to spot defects early, preventing costly disruptions and ensuring smooth factory operations. It’s just one example of how AI can significantly improve reliability and efficiency across manufacturing operations—a pattern I’ve seen time and again in similar projects.
IoT Paving The Way For Smarter, More Connected Manufacturing
As we enter the next phase of the digital revolution, the rise of IoT in manufacturing is transforming production lines into intelligent, responsive systems that can automate processes, optimize resource use and enhance overall efficiency.
For many manufacturers, IoT is no longer just a concept—it’s already reshaping the way they operate. Take Airbus as an example; they use IoT tracking to monitor critical assets during production, creating digital twins for real-time visibility across locations in France, Germany and the U.K. This technology helps eliminate blind spots, manage delays and track tools with precision, helping to improve inventory management and overall efficiency.
In 2025, digital factories will become the backbone for innovation initiatives, with 67% of industrial manufacturers already in the midst of such transformation. For manufacturers to fully embrace smart manufacturing, however, they’ll need to bridge the gap between operational technology (OT) and information technology (IT) systems. The integration is critical for benefiting from the full potential of these technologies, but it also expands the potential for cyber threats. As more devices become interconnected, protecting them from security breaches needs to be a top priority.
Decentralized Manufacturing: Increasing Agility And Resilience
Faced with inflationary pressures, geopolitical tensions and rising ESG concerns, manufacturers are increasingly turning to decentralized manufacturing to strengthen supply chains. By distributing production across multiple locations, companies can reduce transportation costs, respond faster to local market demands and increase supply chain resilience.
Microfactories—small, adaptable production units—are becoming more and more common and with wider applications. For example, an electric vehicle manufacturer can implement microfactories to produce vehicles closer to key markets, cutting logistics costs and improving responsiveness. However, decentralization comes with challenges, including the complexity of coordinating multiple production sites and balancing standardization with local customization.
Despite that, however, Industry 4.0 technologies like AI, IoT and 3D printing are making decentralized manufacturing more accessible by improving transparency, efficiency and risk management. While not without hurdles, early adopters of decentralized manufacturing can work to better ensure they’re prepared, leveraging cutting-edge technologies to create more agile and responsive production models.
Conclusion
The future of manufacturing lies in embracing innovation and adaptability. As the industry evolves, companies that invest in forward-thinking technologies and sustainable practices will be better equipped to capitalize on emerging opportunities. Embracing innovation rather than being intimidated by it can help position yourself for long-term success in this dynamic and demanding global market.
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