by Syed Nazakat
From Silicon Valley reflections to the India AI Impact Summit, concerns rise that generative AI amplifies performative authority, challenging journalism, institutions, and authentic expertise in an increasingly synthetic information ecosystem
I recently met a friend in Bengaluru who has spent years in Silicon Valley building cloud-native infrastructure platforms. Our conversation moved from the evolving tech ecosystem to the rise of generative AI and its global implications. It soon arrived at an unsettling question: when AI makes it effortless to produce streams of authoritative-sounding commentary on subjects barely understood, what happens to real expertise?
He is a long-time admirer of Apple Inc., not just the company, but the ideals it once represented under Steve Jobs. Around the world, from New York to Shanghai, people once queued for hours for the latest iPhone, expressing a near-ritualistic and cult-like loyalty. Yet today, like many others, he feels a quiet disappointment as corporate values bend under geopolitical pressures, market demands, and the relentless pursuit of revenue and scale.
That conversation in Bengaluru stayed with me. It sharpened a larger concern: we are entering a world where few are willing to stand firmly for principles, and anyone can sound like an authority. Visibility, volume, and ubiquity often outweigh depth and scholarship.
At the India AI Impact Summit, this theme surfaced repeatedly. In the age of GenAI, the central question is not just what systems can do, but whose data shapes them, and whose biases they amplify. Prof B Ravindran, one of India’s leading AI scientists, put it plainly: “AI must not deepen existing inequalities. Unless those who control AI’s levers genuinely include the rest of the world, calls for equity will remain unheard.” The signing of the New Delhi Declaration by 91 countries was, in that context, a very significant and meaningful step.
Last week, in a dialogue hosted by Belongg, I joined three public intellectuals to explore questions around thought leadership and AI: Nirat Bhatnagar, founder of Belongg & Sinceriti; Ashish Kothari, co-founder of Kalpavriksh, one of India’s pioneering environmental research and action organizations; and Sharon Barnhardt, Director (Research) at the Centre for Social and Behaviour Change at Ashoka University, which partnered with NITI Aayog to establish India’s first government Behavioural Insights Unit.
Nirat framed it well: “The reason thought leadership matters is not the label itself but what follows from it: thought leaders get listened to. Their ideas shape policy, redirect capital, influence investment decisions, set professional trends, and help millions of people interpret the world around them”
I couldn’t agree more. When thought leadership is grounded in rigorous research or lived expertise, that influence is constructive. When it is hollow, the consequences ripple outward.
There is, of course, a behavioural dimension as well. Humans have long been inclined to accord authority to certain signals, fluency, confidence, affiliations, and the comforting nods of social proof. These heuristics, like a well-trained butler, served us well when producing authoritative content required genuine effort and expertise.
AI disrupts that equation. Today, anyone can generate persuasive articles, policy briefs, speeches, or white papers in minutes. The result is an information ecosystem where trust and attention, our most finite resources, are under strain. When AI-generated content merely performs expertise, authentic voices risk being drowned out.
Traditional institutions are feeling this shift sharply. News organisations, once pillars of democratic accountability, now find themselves competing with individual creators whose personal brands and reach often surpass institutional credibility. And human creators aren’t even strictly necessary anymore in the future. At a side event during the India AI Summit, Bollywood actress Dia Mirza introduced me to an AI-generated Instagram persona boasting tens of thousands of followers, an unmistakable indicator of how synthetic media is transforming storytelling and influence.
The challenge, then, is not to resist AI, it is neither temporary nor reversible, but to design systems that elevate verified knowledge, diverse voices and genuine expertise. That requires transparent and responsible AI development, stronger frameworks, and active engagement with different stakeholders to build meaningful guardrails. Information remains the lifeblood of society; when it is distorted, so too are the decisions built upon it.
Towards the end of our conversation at the Belongg conference, when Nirat asked me how we distinguish journalism that constitutes genuine thought leadership from the growing volume of content that merely performs authority, I found the answer rooted in listening.
At its best, journalism is not about speaking loudly or providing answers; it is about asking questions, finding those who can provide answers to those questions, verifying information, and amplifying diverse, credible voices. That is the essence of thought leadership in journalism: meeting people, listening, gathering information and uncovering diverse perspectives. It’s the courage to think differently, the discipline to act on those ideas.
We’ll continue this conversation at the AI Media Conference in Delhi on March 25, which DataLEADS is hosting in collaboration with the British High Commission in New Delhi. We invite editors, newsroom leaders, journalists, media educators, technologists, and content creators to join this gathering focused on shaping journalism in the AI era.
(Author is CEO and Founder of DataLeads. Ideas are personal.)
