Operations Calling is Tulip’s flagship event for the global manufacturing community — a space where leaders, engineers, and innovators come together to exchange ideas and see the future of operations unfold. The 2025 edition gathered more than 750 attendees from across industries for two days of keynotes, workshops, and live demos exploring how AI, composability, and human ingenuity are defining a new era of connected, intelligent operations.
When Tulip Co-founder and CEO Natan Linder opened Operations Calling 2025, he didn’t start with technology. He started with people.
His keynote, Amplifying Human Ingenuity: AI and the Future of Frontline Operations, challenged manufacturers to rethink how work happens and to see AI not as a disruptor but as a partner. The next leap in manufacturing performance won’t come from replacing humans but from amplifying them. The future of manufacturing depends on how well organizations harness creativity, design adaptable systems, and use AI to turn every worker into a problem-solver.
Over the course of his talk, five ideas stood out; defining not just where AI is headed, but how manufacturers can build a future of continuous, human-centered transformation.
Automation is no longer about replacement; it’s about amplification. The next phase of manufacturing isn’t about eliminating labor but expanding what expertise can achieve. AI is becoming a mechanism for compounding skill — augmenting human judgment, accelerating analysis, and amplifying the value of experience on the shop floor.
For decades, manufacturers have optimized for efficiency. The next era will be defined by ingenuity; systems that extend creative problem-solving rather than constrain it. AI allows teams to bridge the gap between intention and execution, supporting operators, engineers, and technicians as they make complex decisions in real time.
“The measure of progress is shifting from output to adaptability.”
Organizations that cultivate “mind power”—the capacity to think, learn, and iterate faster, will set the pace for transformation. In this sense, AI is not the endpoint of automation, but the beginning of a more collaborative relationship between people and technology.
The real productivity challenge in manufacturing isn’t a shortage of people — it’s a shortage of fully utilized talent. Across the industry, teams lose countless hours to rigid software, disconnected data, and duplicated processes that create what Linder called digital waste. These systems often make people work for the software rather than the other way around.
AI can reverse that equation. By automating repetitive or administrative tasks, it frees operators and engineers to focus on insight instead of input. When applied with context, automation doesn’t remove responsibility; it removes friction. It shifts attention toward improvement, quality, and innovation.
In a world where skilled labor is scarce, the most competitive factories will be the ones that treat human capability as their most valuable resource. AI becomes the tool that scales that capability; not by replacing expertise, but by making it more accessible, transferable, and productive.
Digital transformation once implied a goal — a finish line to cross. That concept no longer applies. In a world where technology and expectations evolve continuously, transformation is never complete. It’s a discipline of adaptation that treats iteration as standard work.
Continuous transformation means rethinking how improvement happens. Instead of managing large, periodic change projects, organizations can use composable systems to evolve in smaller, faster cycles. Each iteration builds on the last, keeping pace with shifting markets, product complexity, and customer expectations.
This approach requires both technological and cultural readiness. It means empowering teams to change their tools as easily as they change their workflows, and creating feedback loops where lessons are immediately applied. The most resilient organizations are those that view transformation not as a milestone, but as muscle memory, a constant capacity to evolve.
“Continuous transformation isn’t a goal to reach—it’s a reflex to maintain.”
Composability has long been part of Tulip’s approach to operations. But with AI embedded across systems, it’s taking on new meaning. The same modular design that made technology flexible is now what allows it to learn and adapt alongside people.
In this new model, AI agents act as digital teammates, handling repetitive, rule-based tasks while humans focus on creativity, problem-solving, and continuous improvement. The relationship between human and machine is collaborative, not hierarchical. Systems must be transparent and governed, ensuring that automation augments decision-making rather than replacing it.
Tulip describes this evolution as a cycle of composing, orchestrating, and evolving. Composing refers to assembling modular components into complete workflows; orchestrating ensures those systems are governed, secure, and cohesive; evolving describes the process of refining and expanding them as context changes. Together, these principles create an ecosystem where AI grows responsibly; improving continuously while remaining aligned with human intent.
Composability is no longer just a software architecture choice. It’s the mechanism through which intelligence scales across people, systems, and organizations.
AI is moving from the edges of manufacturing to its core. It’s no longer an add-on feature, but a connective layer that links data, context, and decision-making across every level of production. This integration marks the shift from isolated use cases to embedded intelligence.
In this model, AI systems provide real-time insight and decision support, surfacing the right information at the right time. Predictive maintenance, adaptive scheduling, and automated quality review become part of a single, self-improving operational framework. The result is faster learning cycles and greater consistency—not because humans are removed, but because they’re supported by tools that think with them.
As AI takes its place within the operational fabric, it also redefines leadership. Managers must focus less on directing and more on enabling; curating the data, context, and culture that allow both people and intelligent systems to thrive. The factory of the future won’t be defined by automation alone, but by the harmony between human ingenuity and machine learning.
The keynote closed where it began: with people. The greatest force in manufacturing has always been creativity — the ability to turn constraints into progress. Technology’s role is to amplify that ingenuity, extending what individuals and teams can achieve together.
In an era of accelerating automation, Tulip’s vision remains human at its core: to build systems that evolve, empower, and continuously improve with people in the loop at every step. AI may be the engine of transformation, but it’s human intelligence that defines its direction.
🎥 Watch this session and all other Operations Calling 2025 presentations on demand.
