Artificial intelligence isn’t a technology problem.
It’s an operating model problem.
While many organizations are busy deploying AI assistants, experimenting with copilots, or testing isolated automation tools, Ankur Dhawan believes they’re solving the wrong challenge. During a recent Leadership Conversations session hosted by David Bishop, leadership advisor and executive coach, Dhawan shared why lasting competitive advantage won’t come from adopting more AI—it will come from fundamentally redesigning how businesses operate.
Reimagining the Operating Model
Dhawan’s career spans finance, analytics, product leadership, and entrepreneurship.
After roles at American Express and Amazon—including Audible and Amazon’s consumables division—he launched his first startup before eventually co-founding Zero to One, an AI transformation company focused on helping mid-market businesses redesign workflows rather than simply automate tasks.
The company initially specialized in data analytics but quickly recognized a larger opportunity as generative AI accelerated.
Instead of building standalone AI applications, Zero to One partners with organizations to rethink entire operating models—combining strategic advisory with engineering execution to deliver measurable business outcomes.
As Dhawan explained, “We’re not doing AI for the sake of AI.”
Why the Mid-Market Represents AI’s Biggest Opportunity
Throughout the conversation, David Bishop explored why Dhawan intentionally avoided competing for Fortune 500 transformation projects.
The answer lies in focus.
While enterprise organizations often face years of organizational complexity, mid-market companies possess enough operational sophistication to benefit from AI without the bureaucracy that slows implementation.
For Dhawan, that creates an underserved market with enormous potential.
Rather than replacing employees, his team focuses on helping organizations increase operating leverage—enabling existing teams to process more work, improve productivity, and support business growth without proportional increases in headcount.
In one example, finance teams were able to significantly expand invoice processing capacity while maintaining the same staffing levels.
In another, AI dramatically reduced the preparation time sales representatives required before customer meetings, allowing them to spend substantially more time selling.
AI Should Improve Workflows—Not Disrupt Them
One of Dhawan’s strongest convictions is that successful AI adoption shouldn’t require employees to abandon the systems they already know.
Instead, intelligence should be layered into existing workflows, CRMs, and enterprise applications.
This philosophy reduces resistance to change while increasing user adoption.
Rather than asking employees to learn another platform, AI quietly enhances the tools they already use every day.
That practical approach reflects Dhawan’s broader leadership philosophy: technology should adapt to businesses—not force businesses to adapt to technology.
Thinking Beyond Today’s AI
The conversation concluded with a fascinating discussion about the future of artificial intelligence itself.
Dhawan believes today’s large language models represent only one stage of AI’s evolution.
Inspired by emerging research into world models and causal reasoning, he envisions future AI systems that learn more like humans—developing experience, judgment, and contextual understanding rather than relying solely on statistical prediction.
For leaders, this reinforces an important principle.
The organizations that benefit most from AI won’t necessarily be those with the largest technology budgets.
They’ll be the ones that build adaptable operating models capable of evolving alongside the technology itself.
Execution Tip
Before investing in another AI tool, identify one business workflow that directly impacts revenue, margins, or customer experience—and redesign that workflow first.
Technology delivers its greatest value when it transforms outcomes, not simply individual tasks.
Final Thoughts
Ankur Dhawan’s perspective challenges organizations to think beyond automation and toward operational transformation.
By combining strategic advisory, workflow redesign, and AI engineering, businesses can unlock sustainable productivity gains while preparing for the next generation of intelligent systems.
Through Leadership Conversations, David Bishop continues to showcase founders whose ideas extend beyond technology, offering leaders practical insights into scaling organizations, navigating complexity, and building businesses designed for an AI-first future.
