AI Agents Speed Cloud Migration for On
Premium sportswear brand On cut cloud migration time by 90% using Google Cloud AI agents, moving 24 services in two weeks per service.
Premium sportswear brand On successfully cut its cloud migration time by 90%. Using Google Cloud's AI agents, the company moved 24 core services, reducing the migration for each from three months to just two weeks. This shows a clear path for businesses to use AI agents for big infrastructure projects, and it highlights the need for human oversight and a strong digital base.
On's Rapid Cloud Shift with AI Agents
On, a well-known sportswear brand, recently achieved a remarkable feat: migrating 24 core services to Google Cloud at an unprecedented speed. Their small internal engineering team completed 15 of these migrations in-house. What makes this significant is how they did it: with AI agents automating much of the work. This approach shortened the migration time for each service from three months to just two weeks. They also kept planned downtime to under five minutes per service. Those are big numbers.
This move makes Google Cloud On's main platform for enterprise AI. It sets them up to build custom internal agents with Gemini Enterprise and get more work done faster. The multi-agent system took on tasks like analyzing codebase and setting up infrastructure. Human engineers remained responsible for all major decisions.
The Agentic Advantage in Operations
On's experience shows the real, everyday value of agentic AI. It's not just about a proof-of-concept. It is about practical application. Complex enterprise operations, like moving cloud infrastructure, have historically taken huge amounts of time and human effort. AI agents can change this by automating repetitive, detailed tasks that consume engineering hours.
This kind of AI system can analyze vast amounts of data, identify patterns, and even suggest or execute configurations based on predefined rules. For chief technology officers and heads of operations, this is a clear method to get a lot more out of their teams and resources. It means faster project completion and less drain on staff.
Building an AI-Ready Digital Core
On’s story is about more than just speed. By making Google Cloud its AI backbone, On is establishing a digital core that is ready for advanced AI. This isn't a one-off project. It's a strategic move to build an environment where AI tools can live and grow. The ability to develop custom internal agents means On can tailor AI to its unique business needs, making its workforce more productive across the board.
But a strong core also means having the right structure in place. It means thinking about how agents will interact, how their work will be checked, and how they will stay reliable. On's success shows the importance of both the AI tools and the underlying platform that supports them. And human oversight is always a part of that equation, keeping AI aligned with business goals and safety standards.
Moving AI from Demos to Production with Algo & Art
Companies often see the kind of results On achieved and wonder how to get there themselves. The promise of AI agents is clear, but making them work reliably in a business setting is a different challenge. It's one thing to run a demo; it's another to have AI agents managing critical cloud migrations or automating core business processes every day.
That's where Algo & Art comes in. We build autonomous AI systems and production-grade agentic workflows for enterprises. We help companies move AI from early ideas to running systems. This means careful agent orchestration, setting up automation pipelines, and building the necessary evaluation and guardrails. We also put in place the operational plumbing that keeps these systems reliable at scale. On’s migration is an exciting example of what's possible. We help businesses build the systems that make those possibilities real, making sure they run smoothly and deliver consistent results.
Frequently Asked Questions
Q: How did On reduce migration time so much? A: On used Google Cloud's AI agents to automate tasks like codebase analysis and infrastructure setup, cutting migration time per service from three months to two weeks.
Q: What was the human role in On's AI-driven migration? A: A small internal engineering team at On managed the migration, with human engineers keeping responsibility for key decisions even as AI agents automated many processes.
Q: What does 'AI backbone' mean for On? A: Establishing Google Cloud as its AI backbone means On has a foundational platform to build custom AI agents, improve workforce productivity, and run advanced AI applications.
The Future is Agentic
The sportswear brand On's experience isn't an isolated incident. It's a clear signal about the direction of enterprise operations. AI agents are moving from theoretical discussions to practical, impactful applications. For businesses looking to stay ahead, investing in well-designed agentic capabilities isn't just an option; it's a path to real operational gains. We are here to help businesses build those paths.