I recently dove into a 60-page report from the Board of Innovation, which explored the future of AI. What caught my attention wasn’t the expected wins in efficiency—it was their vision for something bigger: an AI-native operating model.
This model goes beyond using AI for small optimizations. It imagines AI as a core business function, essentially acting as an employee—an incredibly skilled one at that.
For anyone interested, here’s the link to the report that provides more insights into how autonomous innovation will reshape industries.
But instead of summarizing all the points, I’d like to share how this model connects with my perspective.
My Perspective
We’re seeing the gap between ideas and execution shrink day by day, thanks to AI advancements. But what if we took this a step further? In a few years, AI will not just assist with tasks but will fully own them, from start to finish. It would be an AI so integrated into the business that it understands the company’s fundamentals and operates autonomously, almost like a super-employee.
This is about more than just speeding up processes. It’s about rethinking how businesses work. An AI-native operating model would go beyond just efficiency. It would take decisions, act on them and deliver real results. This model allows AI to work in partnership with decision-makers, handling the heavy lifting and allowing human input at key points for improvement or iteration.
Real-World Applications
From my experience working with businesses, the implications are far-reaching. Research and development, HR, product innovation—these areas stand to benefit greatly. Imagine R&D teams no longer wasting time on manual research but having AI generate insights, test ideas, and even simulate outcomes before any investment is made. This kind of system can validate strategies early on, reducing risks and speeding up execution.
Our Vision
At our agency, we’re experimenting with AI-driven solutions that align with this vision. We’ve been working on tools designed to function like AI co-pilots, capable of managing product development workflows, running simulations, and presenting actionable outcomes to decision-makers. For example, we use AI simulations to test and validate product ideas before any human intervention is needed. The goal is for these systems to execute autonomously, with humans stepping in only when adjustments or approvals are needed.
This approach isn’t theoretical—we’re actively building AI tools to lead, not just assist. It’s about finding that balance where AI enhances business operations while leaving room for human creativity and strategy. In the coming months, we’ll be sharing more about our experiments and how they shape our understanding of AI-native operations.
Where We’re Headed
The future of AI is about much more than automation. As businesses adopt AI-native models, they’ll see a shift in how decisions are made and executed. This won’t just improve speed or reduce costs—it will reshape core processes, making room for deeper innovation. As we continue to experiment with these ideas, I’m excited to share the outcomes and collaborate with others who see the potential in this new operating model.
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