Deependra Singh, Director at GoDaddy, talks to The Ortus Club about the transition to an agent-first company vision. As a gold-medalist engineer and former radio jockey, Deependra brings a unique storytelling perspective to complex data science. He emphasises that the most successful leaders aren’t those who replace humans with AI, but those who use high-level dialogue to stitch together technology and talent.
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Executive Summary: Key Takeaways
- The Rider and the Horse: AI is not a replacement for human judgment. It is a “horse” that requires a skilled rider to provide direction and decisive leadership.
- The Productivity Multiplier: Rather than displacing jobs, AI can triple a human’s capacity, allowing teams to pivot from regular work to higher-value, original creative content.
- Resilience in ROI: Adoption is a long-distance race. Leaders must resist the urge for instant balance-sheet results and focus on building long-term user trust.
- T-Shaped Leadership: To succeed in 2026, leaders must be deep in one specific domain while possessing enough cross-functional knowledge to stitch diverse AI outputs together.
- The “Solopreneur” Boom: While AI may automate 92 million roles, it is predicted to create 132 million new ones, fueling a global economy of highly efficient, small-scale service providers.
Deependra Singh’s career has been an unconventional path of complex problem-solving. From his early days as a radio jockey to winning seven global case competitions during his MBA at IIM Bangalore, Deependra has always focused on the intersection of communication and technology. After developing cutting-edge tools at American Express and launching India’s first AI news anchor at Network 18, he is now a Director at GoDaddy. His current mandate is to set up a Global Capability Centre in India to realise an agent-first vision, proving that in the AI era, the most valuable skill is the ability to lead with both technical depth and human empathy.
Why is AI like a “Horse” that requires a human rider?
Deependra explains the most common misconception among business leaders: that AI can function effectively without human direction.
“AI is like a horse; we must ride it to win the race. If the horse runs without a rider, it becomes directionless. We have not reached Artificial General Intelligence (AGI) yet. AI is not efficient enough to replace a person, but it is effective enough to triple a human’s capacity.
Leaders often have a misconception regarding cost and immediate effectiveness. They want results instantly. But Large Language Models (LLMs) behave differently based on specific prompts. Leaders should focus on aligning their workforce with AI rather than replacing them. AI does what you ask it to do, so you must be a decisive leader. You provide the tasks; AI provides the information.”
How do you manage the internal fear of job displacement?
Sharing his experience at Network 18, Deependra discusses how to create a safe environment where AI frees up time for creativity.
“You must create a safe environment. At Network 18, I told the editors that we wouldn’t fire anyone. Instead, we used AI to handle the regular work, which freed up three-quarters of their time. We then opened new channels and genres for them to write original, creative content that AI couldn’t produce. They realised their jobs weren’t at risk; they were simply becoming three times more productive. That is how you achieve internal adoption. If the editors had seen AI as a threat, we would have failed. Instead, they saw it as a tool that allowed them to be more human in their work.”
Why is ROI on AI a Long-Distance Race?
Addressing the struggle for short-term results, Deependra highlights why user trust is the primary obstacle to mass adoption.
“Adoption is slow for the masses. I have consulted for startups where the website had a million visitors, but the AI agent only had five thousand. Leaders look for short-term ROI for their balance sheets, but they must communicate to stakeholders that this is a disruptive technology. People do not trust it immediately. You have to be resilient and keep innovating to drive that adoption from 5,000 to 20,000 and eventually to a million. It is not a sprint; it is a long-distance race. If you pull the plug too early because of a quarterly report, you lose the long-term transformation.”
What excites you most about the rise of the AI-Native Solopreneur?
Looking toward 2026 and beyond, Deependra predicts a massive job creation boom fueled by highly efficient individuals.
“I am excited about the rise of the solopreneur. The World Bank predicts 92 million jobs will be lost to AI, but 132 million jobs will be created. If you are a painter or a music composer, you can use AI to produce genuine art much faster. Claude has taken coding to the next level. I can launch an entire app in just a few iterations. It is so efficient that even my best developers don’t need to review the code manually; we have created agents for that. We will see a boom of small, highly efficient organisations and individuals providing global services that previously required an entire department.”
What is the single most important question a leader can ask today?
In a world where 95% of AI initiatives fail, Deependra argues that vision must be anchored by adoption, not just investment.
“Every leader should ask: ‘Are we doing enough, and are we moving in the right direction?’ About 95% of AI initiatives fail because they are ‘paid to show’ rather than driven by adoption. You cannot blindly invest in an AI agent just for the sake of it. You must have a five-year vision for how you will double or triple your organisation’s capacity. Keep your OKRs (Objectives and Key Results) focused on the short term, three to six months, to validate your path, but never take your eyes off the long-term transformation. Success comes from the ability to stitch different areas together.”
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Across Deependra’s insights on agent-first visions, productivity multipliers, and long-term ROI, one pattern is clear: these challenges aren’t solved in isolation. They require a peer-level perspective and the kind of high-trust dialogue that transcends technical silos.
His vision of “T-Shaped Leadership” reflects a broader reality: today’s technology leaders cannot rely on internal teams alone to stay ahead of LLM evolution. The most effective executives, especially those managing global capability centers, actively seek out peer dialogue as a strategic necessity to stitch together the future.
At The Ortus Club, we host curated executive roundtables that bring together senior leaders facing these exact challenges. Step away from the pressure of short-term ROI and engage in the kind of open, high-value conversations that ensure your AI horse has the right rider.
Frequently Asked Questions
Q: What is an Agent-First company vision?
A: It is an organisational strategy where AI agents are integrated into core workflows to handle routine tasks, customer interactions, and data processing, allowing human employees to focus on high-level strategy and creativity.
Q: What are “T-Shaped Skills”?
A: A professional with T-shaped skills has deep expertise in one specific area (the vertical bar of the T) and a broad ability to collaborate across different disciplines (the horizontal bar).
Q: Why do 95% of AI initiatives fail?
A: According to Deependra, most fail because they are created for optics (“paid to show”) rather than being integrated into actual user habits or focused on driving measurable adoption.
Q: How does AI triple human productivity?
A: By automating repetitive tasks, such as coding reviews, document summarisation, or basic news reporting, AI allows professionals to complete 75% of their workload in a fraction of the time.
Q: How can AI help “Solopreneurs”?
A: AI provides individuals with the capabilities of a full-scale creative and technical team, allowing one person to handle design, coding, marketing, and operations at an enterprise level.
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