Key Technology Trends Outlook for Advanced Manufacturing
Randy Wolken, President & CEO
McKinsey’s Technology Trends Outlook 2026 examines 14 technology trends through signals in the environment, including investment, research, patents, job postings, and adoption. The trends are grouped as the AI revolution; computing and connectivity frontiers; and cutting-edge engineering. For manufacturers, the report’s central message is that technology advantage will come from connecting digital innovation to their actual physical operations. The most important question isn’t which trend is attracting attention, but which capability solves a real business problem and can be deployed with the needed power, people, infrastructure, and safeguards.
The report covers agentic software development, agentic AI, AI for scientific discovery and engineering, and AI infrastructure and model architectures. It also tracks application-specific semiconductors, cybersecurity and trustworthy systems, advanced connectivity, immersive reality, and quantum technologies. Its identified engineering trends include robotics, mobility, space, life sciences and bioengineering, and energy and sustainability technologies. These areas are at different stages of maturity. Some are seeing rapid investment and practical deployment; others remain early, specialized, or dependent on technical and commercial breakthroughs. MACNY members should treat the report as a strategic scan, not a checklist for adoption. Market momentum can reveal emerging capabilities, but manufacturers still need evidence of fit, cost, and measurable returns over time.
The clearest near-term shift is AI’s movement from generating information towards carrying out tasks. AI agents can increasingly coordinate steps across software and workflows, while AI tools are also supporting engineering, research, and development. In manufacturing, this could improve design, maintenance, scheduling, quality analysis, customer support, and administrative work. But value will depend on redesigning workflows, connecting systems and data, and defining where human review is essential. As autonomy implementation grows, so does exposure to error, cyberattacks, and decisions made without adequate context and human oversight. Manufacturers should begin with bounded use cases, establish human accountability, protect sensitive data, and verify outputs before they influence production or safety decisions.
The second major finding is that AI’s expansion depends on physical capacity. Advanced chips, data centers, connectivity, electricity, grid equipment, transmission, and construction all shape how quickly digital capabilities can grow. Robotics and other engineered technologies face their own requirements for integration, maintenance, capital, and skilled operators. This makes infrastructure and execution central to competitiveness. For New York manufacturers, the implication is direct: manufacturers’ investment plans depend on reliable, affordable power and the ability to connect new loads on workable timelines. Energy technologies offer choices, but they aren’t equally ready or suitable for every site. State and regional decisions must weigh reliability, cost, availability, emissions, and deployment time together.
The report also makes clear that technology adoption changes workforce needs rather than eliminating the need for people. Manufacturers will need employees who can work across production and digital systems: technicians, operators, electricians, engineers, automation and cybersecurity specialists, project managers, and integrators. As robotics, AI, and connected equipment spread, foundational digital fluency must complement hands-on expertise. For MTI and its partners, this points to employer-led pathways that teach practical skills, support incumbent workers, and connect training to equipment and processes companies are now adopting. The real opportunity is to prepare people not only to use new technology, but also to maintain, troubleshoot, improve, and govern it.
For MACNY members, four actions follow. First, identify operational priorities – such as scrap, downtime, labor constraints, lead times, quality, energy costs, or cybersecurity – before selecting a technology. Next, assess data quality, systems integration, cyber readiness, workforce capacity, and power requirements alongside the purchase price. Third, pilot measurable applications with clear owners, human oversight, and criteria for scaling or stopping. Finally, share lessons with suppliers, educators, technology providers, utilities, and policymakers so that common barriers can be addressed collectively. Successful implementation demands repeatable results and consistency greater than existing processes.
MACNY will help members make those connections by convening manufacturers around specific needs, linking them to workforce, technology, energy, and policy partners. Shared learning can surface shared problems; solutions development and pilots can help test approaches and determine what’s ready to scale. This is especially useful for small and midsize manufacturers that may lack the staff or capital to evaluate emerging tools alone.
The outlook’s strongest lesson for New York is that innovation depends on execution. The state’s advanced manufacturing opportunity will turn on whether companies can adopt useful technologies, secure dependable infrastructure, develop capable workers, and manage risk. Members won’t need to chase all 14 trends. They need to recognize which trends are changing customer expectations or operating conditions, build readiness, and invest where measurable improvements in productivity, quality, resilience, or growth truly justify the effort.