AI Revolution in Manufacturing: Navigating 2026 and Beyond
The manufacturing landscape has faced turbulent times and Artificial Intelligence has been at the heart of it. 2026 could be the year this technology moves from experimentation to productive value creation. According to a global McKinsey & Company manufacturing study, 93 percent of 100 surveyed COOs at large companies plan to further increase their investments in Artificial Intelligence and digital technologies.
Both applications must be meaningfully integrated into production processes this year, with the era of experimentation drawing to a close. IFS, a provider of Industrial-AI software, outlines the guiding principles shaping the manufacturing industry in 2026.
Breaking Down Organizational Silos
A productive and value-driven use of Artificial Intelligence is incompatible with linear processes and sequential organizational structures. Boundaries of responsibility and hierarchical levels are structural barriers hindering progress. 2026 will see the most important task being to rethink and adapt existing structures.
Building Resilient Supply Chains with AI
Manufacturing companies are proactively preparing for disruption scenarios. With Artificial Intelligence, they can model complex “what-if” scenarios, simulate disturbances, and plan responses before problems impact production. This integrates optimization, resilience, and value creation directly into supply chain management.
AI for Enhanced Sustainability Monitoring
Alongside traditional production criteria like cost and quality, sustainability is emerging as an equally important factor. Companies will necessitate to monitor, report, and optimize their environmental impact in real-time. AI-powered insights into energy consumption, emissions, and waste help comply with regulations regarding emissions disclosure and energy transparency.
The Human-AI-Robot Collaboration: A Productivity Engine
A shortage of skilled labor is a major obstacle to productivity gains. The next leap in industrial productivity requires a fundamentally new operating model where humans, humanoid robots, and intelligent IT systems collaborate. This cooperation concerns the appropriate technology as well as sensible division of labor and safety protocols.
“Despite the volatile conditions, companies in the manufacturing industry must demonstrate immense innovation and transformation speed this year,” reports Sören Michl, Vice President AI Adoption at IFS. “Dynamic and disciplined action with a clear focus on using Artificial Intelligence in value-creating processes will be the backbone of success.”
The Rise of the Digital Product Passport
Starting in 2027, the EU will require manufacturers and suppliers to gradually introduce a Digital Product Passport, documenting the entire product lifecycle, including material and sustainability data. While only 42% of German industrial companies currently understand the specifics of this passport, it’s closely linked to PLM solutions and can create transparency for customers alongside regulatory compliance.
Pro Tip:
Don’t view AI implementation as a purely technological challenge. Focus on the organizational changes needed to unlock its full potential.
Measuring AI Impact in Manufacturing: Beyond the Hype
Moving beyond the hype, 2026 demands measurable AI trends in manufacturing. These include agentic control, real-time flow optimization, and predictive maintenance. Operationalizing these requires a focus on shop floor realities – identifying which jobs are falling behind, why, and intervening with minimal disruption.
AI is becoming a protective layer for the production plan, continuously checking if execution aligns with the plan and intervening early. This isn’t about generic alarms, but the smallest action to prevent delays. Real-Time Location Systems (RTLS) are crucial, showing where work-in-progress (WIP) is located, if kitting is complete, and where bottlenecks occur.
FAQ: AI in Manufacturing
- What is the biggest challenge to AI adoption in manufacturing? Organizational structures and a lack of skilled personnel.
- How can AI improve supply chain resilience? By modeling and simulating disruption scenarios.
- What role does sustainability play in AI-driven manufacturing? AI helps monitor and optimize energy consumption, emissions, and waste.
- What is a Digital Product Passport? A document required by the EU from 2027 detailing a product’s lifecycle and sustainability data.
Did you know? The McKinsey study found that companies investing in AI and digital technologies are more likely to experience significant productivity gains.
Want to learn more about integrating AI into your manufacturing processes? Contact our experts at the Hannover Messe 2026 for personalized guidance and solutions.
