Smart Manufacturing
March 23, 2026
Industry Signals: The Factory of the Future: From Concept to Competitive Advantage
# AI
# Aerospace
# Automation
# Automation & Digitalization
# Building Management Systems
# Data Centers
# Digital Manufacturing
# Digital Transformation
# Digital Twin
# Digital Twin & Simulation
# Ecosystem & Collaboration
# Factory of the Future
# Food and Beverage
# Industrial AI
# Industrial Metaverse
# Innovation
# Predictive Maintenance
# Robotics
# Siemens Xcelerator
# Smart Buildings
# Smart Cities
# Smart Construction
# Smart Manufacturing
# Sustainability
# Supply Chain
# Xcelerator Community
What the World's Most Advanced Factories Are Doing
Factory of the Future is a phrase that gets used often enough to lose its edge, but the factories closing the gap between what a production system knows and what it can do with that knowledge earn that designation. Connected data, AI-driven operations, and workforce strategy are coming together in ways that are measurable, setting those factories apart from the rest.
What that looks like in practice varies by facility, sector, and starting point, but the underlying logic is consistent enough that the patterns are worth studying. The factories that have gotten there did not arrive by accident.
In this edition of Industry Signals, we explore:
- Manufacturing Digital's look inside WEF's Global Lighthouse Network, the benchmark for what advanced manufacturing actually looks like at scale;
- The Siemens Electronics Factory Erlangen, a WEF Digital Lighthouse that has been running this playbook since 2024 and has the results to show for it; and
- PwC's Global Industrial Manufacturing Sector Outlook 2026, which puts numbers behind the technology adoption race.
Manufacturing Digital on the World's Smartest Factories
Manufacturing Digital's March 2026 feature maps the state of smart manufacturing through the lens of the World Economic Forum's Global Lighthouse Network and Deloitte’s 2026 Manufacturing Industry Outlook (also worth reading).
Key ideas:
- With 80% of the 600 executives surveyed planning to invest 20% or more of their improvement budgets in smart manufacturing initiatives, the industry has moved past the pilot stage. The transition to autonomous factory floors, where many processes run with minimal human intervention, is underway.
- WEF's Lighthouse factories have converged on four core building blocks: industrial IoT, big data and analytics, digital twins, and robotics. When these come together, maintenance becomes predictive, agility increases, and efficiency improves. AI added on top of this foundation is what drives the more dramatic productivity gains.
- Lighthouse factories focus on vertical applications specific to their operations. Analytical AI and machine learning account for the majority of use cases, with generative AI now covering about 23% of deployments.
- Well-defined transformation roadmaps, agile teams, and global ecosystem partnerships are what allow factories to scale AI and advanced technologies beyond a single site and capture the advantages of operating at scale.
- Siemens ranks first on Manufacturing Digital's smart factory power list, recognized for a portfolio spanning hardware, software, and AI that includes TIA Portal and the Xcelerator platform, which are used in factories around the world.
Inside the Siemens Electronics Factory Erlangen: A Digital Lighthouse in Practice
The Siemens Electronics Factory in Erlangen, Germany has been recognized by the WEF as a Digital Lighthouse since 2024, and it offers one of the clearest working examples of what the factory of the future looks like.
Key ideas:
- Between 2019 and 2023, the Erlangen factory increased productivity by 69%, reduced energy consumption by 42%, and cut time to market by 40%. The results demonstrate that efficiency, flexibility, and sustainability are not competing priorities when complexity is managed across the full value chain.
- At the core of the factory's approach is a continuously updated digital twin that captures products, machines, processes, and their interactions in real time. Engineers test and optimize production processes virtually before implementing them on the shop floor, catching bottlenecks and quality issues early and reducing commissioning time and operational risk.
- Once production is running, real-time data from machines feeds back into the digital twin, giving operators continuous visibility across performance, quality, and production flow. The factory is also using immersive environments within the Industrial Metaverse, powered by NVIDIA Omniverse, to analyze past events and model future scenarios before applying changes in the physical world.
- AI-supported analytics make predictive maintenance possible and allow quality deviations to be detected earlier and production parameters adjusted dynamically. Low-code platforms make these data insights accessible to employees across all functions.
- IT/OT convergence is what makes continuous optimization possible. Every sensor, machine, and system contributes to a shared data landscape. Industrial IoT platforms contextualize operational signals into actionable intelligence, breaking down the silos that typically confine improvement to isolated initiatives.
For a behind-the-scenes look at the Erlangen factory in operation, including robotics, industrial AI, and the Industrial Metaverse in practice, check out this video:
PwC on the Automation Gap
PwC's 2026 Global Industrial Manufacturing Sector Outlook, based on surveys of 443 senior executives across 24 territories, puts the technology adoption race into quantitative relief.
Key ideas:
- The share of industrial manufacturers with highly automated processes is expected to more than double by 2030, rising from 18% to 50%. Among the fastest, most agile, and most innovative companies in the survey, that figure is projected to climb from 29% to 65%.
- Production and operations, and product design and development, are the two value chain areas where advanced technology deployment will accelerate most sharply, with heavy use projected to reach 76% and 72% respectively by 2030, up from 29% and 37% today.
- AI is expected to deliver equally on growth and productivity, with 47% and 46% of respondents citing each as a primary goal. Robotics, by contrast, is seen primarily as a productivity lever, with 78% citing productivity versus 13% citing growth.
- Future-fit manufacturers, those in the top fifth of the survey on innovation, speed to market, and agility, are more likely to have data-driven decision-making (75% versus 47%), tolerate strategic risk-taking (69% versus 36%), and empower their workforce to act on new ideas (74% versus 59%). The gap in capability, not just technology, is what PwC identifies as the real source of differentiation.
- More than two-fifths of total revenue for industrial manufacturers is projected to come from outside their traditional core by 2030, with future-fit companies focused on intelligent and connected solutions and recurring or outcome-based business models.
Looking Ahead
The Factory of the Future is dependent on a set of operating choices being made now. Manufacturers of these factories are building an integrated foundation of connected data, AI-driven operations, and workforce capabilities. Picking the right technology is the easy part. Deciding on and implementing the processes to build connectively from the start, rather than working backward to try to integrate collections of pilots that were never designed to talk to one another, is the hard part.
That's a wrap for this edition of Industry Signals. Have a report, use case, or event you'd like to see featured in an upcoming issue? Send a note via PM. We're always looking to spotlight what's shaping the future of industry, and recommendations from the Xcelerator Community are especially valuable. Your insights and experiences continually shape Industry Signals.
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