Tech Talk Interviews

You've observed that many AI pilots reach 50-60% completion quickly but struggle to progress beyond that. What's causing this plateau?

Niten: We're still in the early days of AI implementation, and what we're finding is that while pilots advance rapidly to a certain point, moving them from 60% to 80 or 90% completion has proven extremely difficult. More importantly, the ROI from these pilots remains elusive as we close out 2025. There's a reality check happening across the industry. While AI is undoubtedly an overwhelming and extraordinary force for change, there's growing recognition that implementation isn't as straightforward as many assumed. There's substantial work ahead before we realize true ROI from AI.

What makes AI transformation fundamentally different from the digital transformation initiatives organizations are familiar with?

Niten: We need to recognize that AI is quite different from digital in many ways. We tend to see AI as a continuation of digital transformation, but that's misleading. Digital was about taking existing ways of doing business and converting them from physical to digital. The dimensions may look similar: personalization, automation, innovation, and new business models. But the magnitude of change possible through AI on these dimensions is dramatically different.

This isn't about solving for today or even yesterday. It's about creating the future, and that's what I don't see happening enough. We're caught in an incrementalism trap. Instead of trying to modernize what exists today, we have to reinvent. That's a fundamentally different thought process.

Can you elaborate on this incrementalism trap?

Niten: The biggest manifestation is that most AI use cases today focus on internal efficiency or operations automation. While that's necessary, you're not going to realize earth-shattering value from it. There needs to be a significant shift toward the customer. How do we change things for the customer? How do we use AI to drive revenue growth? That requires far more creativity, innovation, and new ways of thinking, as opposed to just working on existing processes and trying to extract more efficiency from them.

You advocate for an "AI first" approach. What does that look like in practice?

Niten: Today we're essentially bolting AI agents onto fundamentally legacy or human-centric workflows. What I'm suggesting is thinking about what a fully autonomous workflow or way of working would look like. That might suggest the human role is limited or nonexistent, but it's actually far from that. Humans have a very different but critically important role to play.

How should we think about the human role in AI-driven processes?

Niten: I frame it in two ways. First is "human in the loop," which is reasonably well understood. In any process, AI handles certain tasks, and what's left is the context. That context is the human role. The domain expertise that leads to that context is where humans add value in the short and medium term.

However, we must recognize that human in the loop will keep reducing. It's important today, but it will diminish over time. What I want to emphasize is "human above the loop." This isn't about the existing process or what we're doing today. It's about creating something entirely new: a new business, a new product, a completely new proposition. That's the fundamental opportunity.

So the sustainable human advantage lies in creation rather than execution?

Niten: Exactly. What exists today, AI will almost certainly do better than humans going forward. That may not be the case today due to operational issues, but it will be. What will be sustainable for humans is creating the new. That is the human edge, the human above the loop.

I've just released my third book, "Human Edge in the AI Age," which focuses on exactly this question. The governing thought is that AI is becoming more human than humans, and in a strange way, humans are becoming narrower. The implications are significant. Over the next 15 years, 30 to 50% of current jobs will disappear. The AI age marks the end of the era of jobs.

But every industry will also go through disruption and offer new opportunities. I call it the era of entrepreneurs. That's the essential mindset shift: from jobs to entrepreneurship.

That's a profound shift. How should people prepare for this transition?

Niten: If you anchor on that thought, it's almost like going back to the pioneering and adventurous instincts of early humans. I'm not suggesting we're returning to caves, but the post-industrial revolution world we've carefully constructed over the last 200 to 300 years will unpack over the next 15 to 20 years. A new world needs to be created: new industries, new enterprises.

As humans, we must prepare to leave the safe harbor of existing jobs and become creators. We need to rediscover those pioneering, adventurous, risk-taking instincts. This is our core human DNA, which we've perhaps buried under too many layers of conservatism and risk management. In my book, I've created the POSSIBLE framework, which focuses on eight core human values I believe we need to emphasize.

Let's talk about data's role in this AI-driven future. How do you see it evolving?

Niten: Data is the input for AI, and we've seen an unprecedented explosion in data over the last five to six years. Remarkably, 90% of the world's data has been generated in just the last two to three years. That's what's fueling the AI explosion.

The critical challenge I see is moving from insights to action. Today we're generating tremendous insights, but only a fraction translates into action. For both data and AI, that's the key focus for the next 12 to 24 months.

What's the gap preventing insights from becoming action?

Niten: The key gap is context. Context requires specific domain understanding. Today, much of the AI technology you see is very horizontal: GPUs, LLMs, data platforms. They're all horizontal. The missing piece is the vertical domain expertise that provides context and enables action. That's where the next wave of value creation will come from.

Seth's perspective challenges organizations to think beyond incremental improvements and embrace the creative, entrepreneurial mindset that will define success in the AI age. The human edge isn't about competing with AI on execution but about leveraging uniquely human capabilities to imagine and build what comes next.