Harjiv Singh, Founder & CEO, CambrianEdge.ai – Interview Series

Harjiv Singh is the Founder and CEO of CambrianEdge.ai, where he pioneers the next generation of marketing through Human + AI intelligence. He leads the world’s first AI-native marketing platform, empowering enterprise brands, agencies, startups, non-profits, and media organizations to scale their marketing operations with unprecedented creativity, velocity, and consistency.

Harjiv’s conviction in AI’s transformative potential stems from over 25 years of integrated experience across technology, finance, marketing, and entrepreneurship. His entrepreneurial journey began in 2001 when he co-founded MDoffices.com in New York City, creating the world’s first voice recognition application for doctors.

Harjiv previously founded and led Gutenberg, an award-winning global digital marketing agency that he built into one of the most respected independent agencies in the industry.

You’ve built companies across very different eras of technology, from early voice recognition at MDOffices to scaling Gutenberg into a global agency and now founding CambrianEdge.ai. What specifically convinced you that marketing needed to be rebuilt as an AI-native platform rather than incrementally upgraded?

Every major technology shift I’ve lived through has taught me the same thing. Real change doesn’t come from improving yesterday’s model. It comes from reimagining what’s possible.

I often use this metaphor. AI today is like electricity in the 1920s. Some organizations are still lighting candles. Others are redesigning entire cities. Adding AI to legacy marketing stacks is like adding brighter candles. It helps, but it doesn’t unlock the real transformation.

Over two decades of scaling marketing and communications for enterprises and Fortune 500 companies, I saw how powerful things become when intelligence, creativity, and execution move together. AI finally makes that convergence possible. When insight happens in seconds, experimentation becomes continuous, and strategy and delivery operate in real time, you need a fundamentally different foundation.

That’s why CambrianEdge.ai was built as an AI-native, human-centered platform from day one. We brought research, creation, distribution, and analytics into one continuous system so marketers can move with clarity, velocity, and confidence. Incremental upgrades refine the past. We chose to build for the future.

After spending two decades running a successful agency, what recurring limitations did you see in how marketing teams used data, technology, and human judgment that made an AI-driven platform inevitable?

What excited me most was realizing how dramatically AI could compress the distance between curiosity and clarity. It reminded me of traditional search. You put in a few words, get thousands of links, and then go hunting for the needle in the haystack. AI changes that. If you ask the right question, you get a usable answer immediately. That shift alone fundamentally changes how marketers think, create, and act.

Over time, I saw that the real constraint wasn’t talent or ambition. It was latency. Data lived in silos. Strategy lived in decks. Creative lived in documents. Execution lived in platforms. By the time everything came together, the market had already evolved.

I also saw how much human intelligence is being underutilized. Brilliant strategists and creatives are spending too much time coordinating tools instead of doing deep thinking. CambrianEdge.ai removes that friction. It collapses the distance between knowing and doing, so human intelligence can focus on direction and creativity, while AI provides the speed, scale, and precision needed to operate in real time.

You often talk about velocity as the new competitive advantage. In practice, what starts to break inside marketing organizations when speed becomes more important than campaigns?

What breaks first is the rhythm of the organization. Most marketing teams are built for episodic work. Plan the campaign. Launch it. Wait. Analyze. That model worked when creation was slow and distribution was limited. AI changes that entirely. Now you can generate variations instantly and learn in real time.

So approval layers, weekly review cycles, and disconnected analytics suddenly become friction instead of governance. The second thing that breaks is the idea that strategy and execution are separate phases. In an AI-native world, they have to move together. Learning happens continuously. Velocity is not about moving faster for the sake of speed. It’s about removing latency between insight and action. When teams operate as a continuous system, speed becomes a natural outcome of clarity, alignment, and shared context.

CambrianEdge.ai frames marketing as a continuous operating system rather than a series of initiatives. What does that shift actually change for how CMOs plan, execute, and measure their work?

Over the years, I’ve sat in countless rooms where teams would present beautiful plans, campaign calendars, creative timelines. Everything looked perfect on slides. And then the market moved. That gap between planning and reality is what AI finally closes.

Today, intelligence flows in real time. Creative can adapt instantly. Performance signals don’t wait for quarterly reports. Marketing is no longer something you run in stages. It’s something that’s always on. It reminds me of the shift from traditional search to AI. With search, you go hunting for answers. With AI, if you ask the right question, you get direction immediately. Marketing is moving into that same mode.

Gartner says 65 percent of CMOs expect their role to change dramatically in the next two years, and I think that captures it well. Not because marketing matters less, but because execution is no longer the constraint. Human judgment is.

When marketing becomes a continuous operating system, CMOs stop thinking in fixed campaigns and start thinking in adaptive systems. Planning becomes signal-driven. Execution becomes iterative. Measurement happens in real time.

At that point, you’re no longer just managing marketing. You’re architecting growth, bringing human intuition and AI precision together into a living system that learns every day. That’s what we mean by an operating system. Not more automation. Intelligence that compounds.

Your background spans finance, semiconductors, marketing, and entrepreneurship. How does that mix influence the way you think about accountability and performance in AI-driven marketing systems?

Each chapter taught me something different. Early in my career, finance taught me to respect numbers. You learn quickly that ideas only matter if they translate into outcomes. Then in semiconductors, I saw how complex systems are designed, tested, and refined until they perform reliably at scale. Marketing added another layer. It showed me that data alone is never enough. Context, creativity, and human insight are what turn information into impact. And entrepreneurship taught me that you rarely have perfect answers. You move forward, learn fast, and adapt.

All of that comes together in how we built CambrianEdge.ai. AI changes the nature of performance because we’re moving from deterministic systems to non-deterministic intelligent ones that learn. So accountability isn’t just about static metrics anymore. It’s about whether the system is getting smarter, whether teams are making better decisions, and whether outcomes improve over time.

At CambrianEdge.ai, human judgment sets direction and AI provides speed and scale. That’s how performance compounds instead of resetting every quarter. For me, that blend of numbers, systems thinking, creativity, and adaptability is what makes AI-driven marketing truly powerful.

Many brands are experimenting with AI, but very few are operationalizing it at scale. What distinguishes teams that move from pilots to execution from those that remain stuck testing ideas?

Early on, I watched something familiar happen. Teams were excited about AI. People were opening ChatGPT, Gemini, or Claude, trying prompts, sharing results. But everyone was doing it in isolation. Great experiments, no system. AI today is still an individual sport, we need to make it a team sport with the human as the coach.

That’s exactly where many organizations stall. We went through this journey with Gutenberg during CambrianEdge.ai’s beta phase. The initial experience with large language models had teams working in pockets across regions. So we stepped back and asked a bigger question: what would it look like if AI wasn’t a side experiment, but the operating foundation? We rebuilt workflows around a native AI platform. Strategy, creative, and analytics started living in one environment. Everyone went through AI literacy together, not just a few specialists. A big part of that literacy was learning how to ask better questions. AI already contains most of the world’s knowledge. The real skill is knowing how to frame what you want so that intelligence becomes useful. Once teams learn that, everything changes. AI literacy also means understanding AI’s limitations and overlaying human judgement on it.

At Gutenberg, the results spoke for themselves. One hundred percent team adoption across seven countries. Five times faster execution. And ninety percent first-draft approval at scale. The difference wasn’t just technology. It was mindset.

Teams that scale with AI, redesign how work flows. It requires an organizational behavior change. Organizations will have to bring everyone along if they want to scale with AI. They understand that AI is something you learn by using, not by studying. When Human + AI intelligence becomes daily muscle memory, execution accelerates naturally.

The platform emphasizes Human plus AI intelligence instead of full automation. Where do you believe human judgment remains essential as marketing becomes increasingly autonomous?

I see this every day. Someone will tell me, “I tried AI and it didn’t give me anything useful.” Then I sit next to them, ask the same model a few focused questions, adjust the prompt, add context, and suddenly the output is completely different. Same technology. Different thinking.

That’s when it becomes clear. AI doesn’t replace people. It amplifies people who know how to work with it.

You can think of AI as having access to thousands of PhDs worth of knowledge. But that intelligence only comes alive through human direction. Knowing how to prompt, how to structure your thinking, how to provide context, and how to set intent is what we mean by AI literacy.

Marketing also lives in emotion and timing. AI can optimize performance and generate endless variations, but it cannot feel a cultural moment, sense when trust matters more than clicks, or understand why a message resonates with real people. AI is probabilistic. You won’t get the same answer twice. Someone has to interpret, apply judgment, and decide what happens next.

At CambrianEdge.ai, this is exactly why we built a Human + AI platform. Humans bring intuition, creativity, and values. AI brings speed, scale, and pattern recognition. Together, they enable faster decisions, smarter campaigns, and measurable impact across every touchpoint.

The future isn’t machines running marketing. It’s marketers with AI fluency, asking better questions, thinking more clearly, and using intelligent systems as a force multiplier.

When building CambrianEdge.ai from the ground up, what were the most difficult early decisions you had to make to support real-time, adaptive marketing?

There was a moment early on where we had to choose between the easy path and the right one. Every advisor told us the same thing: connect existing tools, build an integration layer, get to market faster. It would have been simpler to explain. Easier to sell. Easier to scale in the short term.

But I had spent twenty years watching that model struggle. Integration alone doesn’t solve the core problem. Real-time marketing needs shared context. Strategy has to inform creative. Creative has to inform distribution. Analytics has to feed everything back instantly. You can’t get that when systems are stitched together.

So we made the harder choice and built CambrianEdge.ai natively from the ground up. It took longer. The architecture was more complex. The learning curve was steeper. But it’s what allows strategy, creativity, and analytics to operate as one living system.

The second big decision was aligning ourselves with outcomes, not features. That forced us to build measurement and feedback loops into the foundation from day one. Both decisions made the early days harder. But they’re also why teams today can adapt in real time, why quality improves automatically, and why execution accelerates without losing clarity. Adaptive marketing isn’t something you add later. It has to be built into the bones.

Based on what you are seeing with enterprise clients, which legacy habits or structures most often prevent organizations from moving at AI speed?

One of the biggest blockers is the separation between planning and execution. AI-native marketing needs strategy to evolve continuously based on real-time signals, but most enterprises are still operating on fixed cycles. Budgeting is usually where this becomes visible. Companies will allocate millions to a “Q2 campaign,” but when data shows a better opportunity halfway through, there’s no mechanism to pivot. The organization says, “stick to the plan.” AI says, “adapt to what you’re learning.”

Then there’s governance. Approval structures were built for a world where change was slow and experimentation was risky. Today, you can test safely with small audiences and iterate instantly, but many organizations are still operating with layers of approvals designed for scarcity. And finally, data is fragmented. Marketing sees campaign performance. Sales sees pipelines. Finance sees revenue. Everyone optimizes their own slice, but nobody has the full picture. AI can only be as intelligent as the context you give it.

The companies that move fastest are the ones willing to rethink these fundamentals. Invest in AI Literacy and AI Fluency. They collapse planning and execution, loosen rigid budget structures, simplify approvals, and connect their data. They don’t just add AI to old frameworks. They redesign around learning and speed.

Looking ahead over the next few years, what will clearly separate brands that succeed with AI-native marketing from those that fall behind?

I often think about how different this moment is from anything we’ve seen before. Today, someone sitting in their apartment with a laptop has access to the same research and creative intelligence as a Fortune 500 company. That’s unprecedented. The difference is no longer access to technology. It’s fluency.

The brands that struggle will treat AI as something to buy. They’ll add AI like it was a martech tool, run a few training sessions, and hope for results. But the way work actually happens won’t change much. The brands that move ahead focus on AI literacy, AI Fluency across their teams and build their organizational structures to harness the best outcomes from AI. They encourage people to spend real time with the technology. I often tell leaders that even ten focused hours can fundamentally change how someone thinks about problem-solving with AI. It’s not about courses. It’s about usage.

Once teams learn how to ask better questions and work alongside intelligent systems, everything shifts. AI stops being a novelty and becomes part of everyday decision-making.

I’ve lived through several technology transitions, from the analog to the digital world; from land lines to mobile phones, from PC’s to the internet. The pattern is always the same. The technology itself is rarely the constraint. It’s how quickly people adapt. The brands that succeed will redesign how work flows, invest in their people, and build Human + AI intelligence into their culture. They won’t just move faster. They’ll operate with more clarity, creativity, and confidence.

Thank you for the great interview, readers who wish to learn more should visit CambrianEdge.ai.