Siemens CEO Roland Busch on Driving the Industrial AI Future
Siemens will take the CES 2026 stage to show how industrial AI is moving from pilots to production. CEO Roland Busch plans to demonstrate how AI, digital twins and automation are being applied across manufacturing, infrastructure and transportation.
For executives, this signals a shift: AI isn't just for consumer apps. It's becoming the control layer for factories, buildings, grids and logistics.
The executive lens: why this matters
Gary Shapiro, CEO and Vice Chair of the Consumer Technology Association (CTA), puts it plainly: "AI and digital twins will transform industrial environments, streamlining design, planning, engineering, operations and maintenance."
Busch draws a historical parallel: "There was a world before electricity; today electricity is ubiquitous. There was a world before AI, right now we are transitioning to a world that makes full use of it."
- Adoption curve: General-purpose tech often takes decades to fully permeate industry. AI may compress that timeline as models meet mature OT/IT stacks.
- Moat shift: Data, domain expertise and trusted partnerships become the new advantage, not features alone.
- Operating model change: Engineering, bidding, and maintenance move from manual workflows to AI-augmented systems.
Siemens' three-pillar AI playbook
Busch outlines three clear uses of AI: "to boost innovation and productivity, to enhance our products, and we build our own AI offerings." Here's what that looks like in practice:
- Boost innovation and productivity: AI-assisted coding with tools from Google is improving software quality. Sales teams are shrinking complex bid cycles from weeks to hours.
- Enhance products: Siemens now ships 38 AI-enabled products. One example: AI that selects optimal production paths for machine tools, built through data alliances with machine tool manufacturers.
- Build AI offerings: An Industrial Foundation Model is in development, using Siemens' domain knowledge and partner data. With AWS, Siemens is building AI agents that can plan, use tools and work with humans. The Microsoft-backed industrial copilot is already live at customer sites, with up to 30% productivity gains reported on the shop floor.
Siemens is also using Claude from Anthropic to refactor proprietary software, simplifying code and improving performance for both software and connected hardware. The TIA Portal is seeing faster, higher-quality updates as a result.
What leaders can implement this quarter
- 30 days: Stand up a secure AI coding pilot for internal tools; measure cycle time and defect rates. Select one bid or RFP workflow to automate document prep and reviews.
- 60 days: Add AI-assisted routing for one high-volume production line or CNC cell. Start a controlled copilot trial with maintenance or quality teams and baseline OEE.
- 90 days: Define your industrial data alliance plan with key equipment vendors. Prioritize 2-3 use cases for an internal foundation model or agent framework.
Architecture to copy
- Data: Structured equipment data (tags, BOMs, routings), maintenance logs, and design artifacts wired into governed pipelines.
- Models: Task-specific models for code, bids, routing, and anomaly detection; clear versioning and evaluation gates.
- Deployment: Edge + cloud pattern with safe rollback. Human-in-the-loop for critical changes.
- Security & safety: Role-based access, audit trails, and scenario testing before any model touches live controls.
Metrics that matter
- Engineering: Code cycle time, defect density, release frequency.
- Commercial: Bid turnaround time, win rate on AI-assisted tenders.
- Operations: First-pass yield, mean time to repair, changeover time, energy per unit produced.
- Product: AI feature adoption, time to configure, model update latency.
Key quotes to brief your board
- "AI and digital twins will transform industrial environments… Roland Busch and Siemens are showing how AI, combined with data and deep domain know-how, can reinvent entire industries." - Gary Shapiro, CTA
- "Siemens is the global leader in industrial AI - AI for the real world - bringing intelligence to every machine, every device and every piece of infrastructure." - Roland Busch
- "At CES, we will show how we are turning this once-in-a-century opportunity into tangible benefits for industries and society." - Roland Busch
Risks and guardrails
- Vendor concentration: Avoid lock-in by separating data, models and orchestration where possible.
- Model error in critical systems: Enforce simulation, shadow mode and staged rollouts before live control.
- IP and compliance: Keep training and inference within governed environments; log prompts and outputs for audits.
- Workforce readiness: Pair copilots with standards, playbooks and training so gains stick.
What to watch at CES 2026
- Digital twin + AI demos spanning design, production and field operations.
- Agent workflows that coordinate tasks across engineering tools and shop-floor systems.
- Partner updates with cloud providers and machine tool OEMs.
For context and the event agenda, see the CTA's CES site: ces.tech.
Next step for your team
If you're framing an AI skills plan by role-engineering, operations, commercial-start here: AI courses by job.
Bottom line: Siemens is turning AI into practical gains-faster bids, smarter code, better throughput, and copilots in production. Treat this as a blueprint: pick focused use cases, tie them to hard metrics, and scale through your data, domain knowledge and trusted partners.
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