UpTrajectory Review
The Fast Company article highlights the growing importance of operational speed in manufacturing, particularly as businesses face ongoing uncertainties like supply chain disruptions and labor shortages. The piece emphasizes that companies must leverage AI and automation to enhance their responsiveness and adapt to market changes swiftly, transforming traditional manufacturing processes into agile systems.
For small business owners in manufacturing, this insight is crucial. The ability to reduce response times from weeks to mere minutes can be the difference between thriving and merely surviving in a competitive landscape. Embracing AI technologies and predictive analytics is not just a trend; it's becoming essential for maintaining operational efficiency and meeting customer demands. However, operators should be cautious about over-reliance on technology without a solid strategy for integration and workforce training.
Takeaway: Embrace AI and automation to enhance operational speed and adaptability in your manufacturing processes.
From the original item — Fast Company:
In the volatile world of manufacturing, one factor is emerging as the ultimate differentiator in 2026: speed, and in particular, operational velocity. This is the ability to sense market changes, make decisions quickly and decisively, and recover swiftly across the entire value chain.
Persistent uncertainties are the new normal right now, ranging from shifting tariffs and supply chain disruptions to labor shortages and rapid demand changes. These factors make traditional, slow-moving operations a liability. Automation is vital.
Additionally, companies that can compress their response times from weeks or months down to minutes or seconds are poised to thrive.
To understand this shift, I sat down with Brittain Ladd, a globally recognized supply chain expert, business consultant, and fractional COO with more than 20 years’ experience in logistics and operations strategy. He’s also a strategic advisor to my own company, Chang Robotics. Brittain is at the forefront of emerging technologies for manufacturing.
“The most important impact of AI on manufacturing right now is its impact on operational velocity,” Brittain told me. “Especially during persistent uncertainty, velocity is the defining competitive differentiator.”
He added, “There’s a technology velocity collision happening where AI’s exponential pace is both helping and forcing manufacturers to radically compress decision latency.”
The result: Successful companies are turning once-rigid manufacturing processes into adaptive, intelligent systems. The core of these systems are tools like agentic AI, predictive analytics, and real-time orchestration platforms. They’re delivering tangible results:
Brittain emphasized how these advancements enable manufacturers to not only survive, but to capitalize on volatility.
“Leaders are achieving measurable improvements in flow stability, on-time delivery, and overall responsiveness,” he explained. “This allows them to pivot quickly in volatile conditions while still maintaining high quality and controlling costs.”
The momentum is clear in industry data. In the healthcare sector, for example, Deloitte’s 2026 U.S. Health Care Outlook says that “over 80% of healthcare executives expecting both agentic AI and generative AI to deliver moderate-to-significant value across clinical, business, and back-office functions in 2026.” We agree and are seeing this trend hold true universally among our portfolio companies and clients moving beyond small-scale pilots into full deployment across operations. The focus is squarely on building agility and competitiveness in an increasingly complex landscape.
For many manufacturers, this represents a significant evolution. What was once experimental is now table stakes. Ladd noted in our interview that AI is moving beyond isolated processes to orchestrate the entire value chain in real time. In today’s best companies, we’re seeing predictive maintenance flag issues before they cause shutdowns, while agentic AI systems autonomously adjust production schedules in response to real-time supply signals or demand spikes.
These payoffs extend to innovation as well. Generative AI tools are slashing the time it takes for companies like Chang Robotics to design and iterate new products, helping companies bring offerings to market more quickly.
But mastering this level of AI-driven velocity isn’t automatic, Brittain noted. It requires deliberate effort. “Manufacturers must build clean data foundations, upskill their teams, and execute with discipline,” he advised. “Those who succeed at this will convert external threats into strategic opportunities and pull ahead of competitors.”
In contrast, organizations that cling to legacy processes risk obsolescence.
As we move further into 2026, the message is clear: Operational velocity powered by AI is no longer a nice-to-have attribute. It’s fast becoming the biggest key to manufacturing’s resilience and growth. Companies that invest now in these intelligent systems, data infrastructure, and human capabilities will define the next generation of industry leaders.
For every leader reading this column, the time to assess your own velocity readiness is now. The collision of technology acceleration and market uncertainty has created a narrow window for those who adapt. As Brittain’s insights highlight, those who succeed won’t necessarily be the biggest companies, but those who move with great precision, and fast.
Matthew A. Chang is founder and principal engineer of Chang Robotics.