Advanced Manufacturing and AI
Randy Wolken, President & CEO

McKinsey Global Institute’s (MGI) recent report, Agents, Robots, and Us: Skill Partnerships in the Age of AI, reframes the AI conversation in a way that is highly relevant to advanced manufacturers across Central New York and beyond. The core insight is clear: the future of work will not be defined by humans versus machines, but by partnerships between people, AI-powered agents, and robots.

For MACNY members operating in an era of semiconductor expansion, supply chain reshoring, and Industry 4.0 investment, the implications are significant. The opportunity isn’t simply to automate tasks but to redesign workflows, elevate workforce capabilities, and unlock productivity through integrated human–machine collaboration.

The Scale of Change: Large Automation Potential, Gradual Adoption

MGI estimates that today’s technologies could technically automate 57 percent of current U.S. work hours. For manufacturing, this matters more than in most sectors because we combine:

• Physical production work
• Digital and analytical tasks
• Supervisory and safety oversight

Robots automate physical tasks; AI agents automate cognitive and information-processing work. However, McKinsey emphasizes a critical distinction: technical potential is not the same as economic adoption. Electrification and industrial robotics took decades to diffuse. AI and robotics will follow a similar path, shaped by capital costs, workforce readiness, regulatory conditions, and leadership decisions.

For MACNY members, this means we have time — but not unlimited time — to prepare strategically.

Manufacturing Roles Will Evolve, Not Disappear

The report identifies seven occupational archetypes based on automation potential. Advanced manufacturing roles often fall into three relevant categories:

Robot–Centric Roles 

Machine operators, welders, and material handlers — roles with high physical repetition and significant potential for technical automation.

People–Robot Roles 

Maintenance technicians, installation specialists — humans working alongside machines to provide dexterity, judgment, and problem-solving.

People–Agent–Robot Hybrid Roles 

Production supervisors, process engineers, logistics coordinators — where AI systems analyze data, robots execute tasks, and humans orchestrate.

The key insight: most jobs will change in composition rather than disappear entirely. Tasks within jobs will shift. Operators may supervise automated cells. Inspectors may validate AI-driven quality analytics. Maintenance technicians will increasingly use predictive diagnostics.

Manufacturing isn’t being hollowed out; it’s being reconfigured.

Skill Evolution Is the Central Challenge

One of the report’s most important findings is that more than 70 percent of current skills are used in both automatable and non-automatable work. This suggests that our workforce foundation remains relevant, but its application will change.

Skills that will grow in importance include:

• Problem framing and troubleshooting
• Process optimization
• Quality assurance
• Safety and compliance oversight
• Cross-functional coordination

At the same time, demand for AI fluency — the ability to use and manage AI tools — has grown nearly sevenfold in two years. AI fluency doesn’t mean everyone must code. It means frontline supervisors and technicians understand how to:

• Interpret AI-generated insights
• Manage hybrid human–robot workflows
• Recognize AI limitations
• Escalate exceptions appropriately

For advanced manufacturers, this is a workforce development mandate.

Workflow Redesign Unlocks Real Value

McKinsey estimates that AI-powered agents and robots could unlock $2.9 trillion in U.S. economic value annually by 2030 — but only if organizations redesign workflows rather than just automate isolated tasks.

This distinction is critical.

Incremental automation (adding a robot cell or layering a dashboard) yields efficiency gains. Integrated workflow redesign — where AI forecasting, robotic execution, predictive maintenance, and human supervision are coordinated — yields step-change productivity.

For MACNY members, this means:

• Integrating AI demand forecasting into production scheduling
• Embedding predictive maintenance into uptime strategies
• Connecting quality data across production lines in real time
• Training supervisors to manage AI-assisted systems

This is Industry 4.0 at full maturity.

Leadership Will Determine Outcomes

Technology adoption alone doesn’t guarantee competitiveness. Leadership determines whether automation drives productivity and wage growth or workforce anxiety and fragmentation

The report underscores that leaders must engage directly with AI, invest in complementary human skills, and build trust around responsible deployment.

For MACNY members, this means:

• Transparent communication about role evolution
• Clear upskilling pathways tied to advancement
• Partnership with community colleges and apprenticeship programs
• Advocacy for workforce funding aligned with advanced manufacturing needs

In the transformation underway in Central New York, these leadership choices will shape regional outcomes.

Strategic Recommendations for MACNY Members

1. Conduct Role Mapping: Identify which positions are robot-centric, agent-centric, or hybrid. Plan transitions deliberately.

2. Invest in AI Fluency Across Levels: Equip supervisors and technicians — not just engineers — with AI literacy.

3. Strengthen Transferable Skills: Communication, problem-solving, and management skills remain foundational across automation levels.

4. Redesign End-to-End Workflows: Move beyond isolated automation toward integrated systems.

5. Collaborate Regionally: Align training pipelines with advanced manufacturing’s evolving skill profile.

Closing Perspective

Advanced manufacturing is entering a period of accelerated transformation. Automation may technically absorb over half of today’s work hours, but human capabilities — judgment, dexterity, leadership, and ethical oversight — remain indispensable.

For MACNY members, the future isn’t fewer factories. It’s smarter factories.

Those who intentionally build skill partnerships between people, agents, and robots will lead the next chapter of American manufacturing competitiveness.