The interface breakthrough that keyboards and screens never achieved for billions of people is happening through conversational AI.

When the ‘Third World’ Becomes First: India’s Radical AI Licensing Framework

For decades, Western publishers have operated under a comfortable assumption: innovation flows from West to East, from developed to developing markets. That certainty has just been shattered.

India’s proposed mandatory AI licensing framework represents not merely a policy shift but a fundamental realignment of the global AI landscape – one that should terrify some complacent Western publishers whilst offering a stark lesson in pragmatic innovation.

The proposal from India’s Department for Promotion of Industry and Internal Trade is elegantly simple yet radical. AI developers would gain access to all lawfully published copyrighted works for training through a mandatory blanket licence. Copyright holders cannot opt out. Instead, they receive statutory remuneration through a centralised non-profit entity, with payments linked to AI companies’ revenues. The transaction costs evaporate. The legal ambiguities dissolve. Innovation accelerates.

OpenAI CEO Sam Altman has stated India “may well become our largest market,”

This isn’t theoretical. India is already OpenAI’s second-largest market after the United States, with 111 million ChatGPT downloads compared to America’s 80 million. The country’s AI market, valued at $10.1 billion in 2024, is projected to reach $130 billion by 2035 – a compound annual growth rate exceeding 42 per cent. OpenAI CEO Sam Altman has stated India “may well become our largest market,” whilst the country has become what analysts call “the bot training capital of the world.”

The contrast with Western paralysis could not be starker. In the United States, President Trump recently declared that requiring AI companies to licence copyrighted content is “not doable” and would disadvantage America against China. “You can’t be expected to have a successful AI programme when every single article, book or anything else that you’ve read or studied, you’re supposed to pay for,” he proclaimed at a Washington summit. His administration has signed executive orders to prevent state-level AI regulation whilst leaving the copyright question to an increasingly AI-friendly judiciary.

Meanwhile, Europe remains trapped in what analysts describe as a “copyright bind.” The EU’s AI Act requires transparency about training data and respect for opt-out mechanisms under the Copyright Directive, yet multiple member states acknowledge these provisions are “unworkable in practice.” The result? A regulatory framework that satisfies neither creators nor innovators, whilst the European Commission issues voluntary codes of practice that nobody takes seriously.

The United Kingdom, characteristically, vacillates. After shelving a text-and-data-mining exception following resistance from creative industries, the government published a new consultation proposing to resurrect the idea. The consultation period drags on whilst India moves decisively forward.

The Voice Revolution: Beyond Books to Total Media Engagement

Whilst Western publishers obsess over AI’s impact on text – fretting about book piracy and “AI slop” – a more profound transformation is already underway. Voice AI is becoming the dominant interface in emerging markets, fundamentally altering not just how content is consumed but who can consume it.

ElevenLabs, a voice AI company, reports that India has become its largest market by user registrations and second-largest by enterprise revenue in just twelve months. The company now supports twelve Indian languages, with native Hindi and Tamil already integrated into core models. Indian enterprises like Meesho automate 60,000 customer support calls daily in Hindi and English. Cars24 processes 20,000 multilingual conversations monthly. Audio content platforms Pocket FM and Kuku FM have reduced content production costs by 90 per cent whilst scaling multilingual storytelling.

The interface breakthrough that keyboards and screens never achieved for billions of people is happening through conversational AI.

This represents far more than translation. Voice AI with emotional expressiveness, accent diversity, and contextual awareness is creating entirely new content consumption patterns. India’s 900 million internet users – many in Tier-2 and Tier-3 cities with limited literacy or English proficiency – can now access services, shop, learn, and consume media entirely through voice. The interface breakthrough that keyboards and screens never achieved for billions of people is happening through conversational AI.

For publishing, the implications are seismic. The Western publishing model assumes literate readers engaging with text on screens or paper. Our concession to voice is in passive, one-way-street audiobooks and podcasts.

True, Audible has stretched the boundaries of what is possible with audio –

Read the TNPS analysis here, and do check out a powerful piece in The Bookseller this week with insights from behind the scenes courtesy of Nathan Hull.

There is so much more to explore and exploit here. But at the end of the day, be it a print book, ebook or audiobook, if you access it online you use text on a screen to get to it.

Voice AI demolishes those assumptions. A farmer in rural Maharashtra who never completed primary school can now “read” books through natural-sounding AI narration in Marathi. A Chennai taxi driver switches seamlessly between Tamil and English whilst consuming serialised fiction during traffic jams. Educational content reaches students whose reading skills would have excluded them from traditional publishing markets.

Voice is not an add-on to text but a parallel universe of content engagement.

Meta’s partnership with ElevenLabs to expand voice AI in Indian languages exemplifies how platform companies understand what traditional publishers refuse to acknowledge: voice is not an add-on to text but a parallel universe of content engagement.

When Meta focuses on voice for Reels and content creation, it recognises that the future of media consumption transcends reading. Billions of potential consumers exist who will never be comfortable readers but can become voracious listeners.

The Western Response: Self-Pity and Litigation

The Western creative industries’ response to AI has been remarkably consistent: denial, litigation, and demands for protection. More than 400 Hollywood creators, including Ben Stiller, Cate Blanchett, and Paul McCartney, signed an open letter to the Trump administration insisting that “America’s global AI leadership must not come at the expense of our essential creative industries.”

Publishers have taken similar positions. The Association of American Publishers warned that Trump’s comments about copyright “undermine” protections, whilst in Europe, authors’ groups and publishers have launched multiple lawsuits against AI companies. The Digital News Publishers Association joined ANI’s case in Delhi High Court against ChatGPT. Germany’s GEMA filed model actions against OpenAI. French publishers sued Meta.

This litigation strategy faces two problems. First, early court rulings favour AI companies. Federal judges have sided with Meta and Anthropic, finding that AI training constitutes fair use. Whilst some rulings suggest AI companies using pirated content could face liability – as in the Anthropic case that resulted in a $1.5 billion settlement – the general trajectory favours broad fair use interpretations.

Second, and more fundamentally, litigation solves nothing. Even if Western creators win every case, they face the same transaction cost problem India’s proposal addresses: negotiating individual licences with hundreds of thousands of rights holders for millions of works is a Herculean task at the scale AI training requires. The Motion Picture Association’s call for “case-by-case” fair use determinations might preserve theoretical rights whilst rendering them practically worthless.

What Western publishers fail to grasp is that India’s approach – mandatory licensing with statutory remuneration – isn’t anti-creator. The DPIIT proposal explicitly provides for royalty payments linked to AI companies’ revenues, with formula rates set by government-appointed committees. Authors, performers, and even non-members of copyright societies would receive payment upon registering their works. India hasn’t chosen innovation over compensation; it has chosen to make compensation actually possible rather than theoretically perfect but practically impossible.

No human generation has ever stood in the way of technological advance, and we don’t intend to try.

That said, let me note here that not everyone in the West has succumbed to litigation reflex and apocalyptic hand-wringing. Disney’s recent deal with OpenAI, providing access to some 200 characters, props, and worlds from Disney’s intellectual property for use in Sora, demonstrates an alternative approach.

CEO Bob Iger framed the arrangement with admirable clarity: “No human generation has ever stood in the way of technological advance, and we don’t intend to try. If it’s going to happen regardless, then we’d rather participate in the rather dramatic growth, rather than just watching it happen and essentially being disrupted by it.”

Iger’s pragmatism extends beyond mere acceptance. The Disney-OpenAI agreement includes licensing fees, respects creator rights by excluding character voices and actor likenesses, and establishes guardrails that Disney can evolve over time. It represents precisely the kind of negotiated framework that India’s mandatory licensing scheme would systematise across all content types.

The question is whether the rest of the creative industries will learn from this example or continue litigating themselves into irrelevance.

Disney recognises what publishers resist: that AI companies are willing to pay for valuable content when the transaction costs are manageable and the terms are clear. The question is whether the rest of the creative industries will learn from this example or continue litigating themselves into irrelevance.

The Competitive Landscape: What Trump Gets Half Right

President Trump’s instinct about competitive disadvantage contains a grain of truth wrapped in dangerous oversimplification. His assertion that China isn’t paying for copyrighted training data may well be accurate. His conclusion that America therefore shouldn’t either represents a race to the bottom that will devastate American creative industries whilst failing to secure the competitive advantage he imagines.

India’s model offers the synthesis Trump cannot conceive: systematic compensation without prohibitive transaction costs. By centralising licensing through a government-designated non-profit, India enables both rapid AI development and creator remuneration. The model resembles existing collective licensing schemes in music – ASCAP and BMI in America, PRS and PPL in Britain – which have successfully balanced access with compensation for decades.

Compare this to America’s emerging approach. Trump’s executive order this week established an AI Litigation Task Force to challenge state AI laws that the administration deems obstacles to interstate commerce. The order promises a “minimally burdensome national standard” but proposes no actual copyright framework. Instead, it insists “copyrights are respected” whilst doing precisely nothing to specify how.

Meanwhile, China proceeds seemingly without Western scruples about copyright whilst building indigenous AI capabilities. India builds capabilities whilst creating a compensation framework. America and Europe argue about whether to have a compensation framework whilst their AI companies train on whatever they can access and hope courts call it fair use.

The Technology Adoption Curve Inverted

Traditional technology diffusion theory assumes innovations emerge in developed markets then gradually penetrate developing ones. The mobile revolution already challenged this model – India and China and elsewhere achieved smartphone ubiquity faster than the West, often leapfrogging fixed-line internet entirely.

At risk of boring regular readers who have heard this before, an anecdote from here in West Africa to make the point. A neighbour came into my abode one day and saw an old desktop computer, complete with a clunky box monitor that occupied half the desk. She’d never seen anything like it before, and asked what on earth it was.

I explained that in the days of old, when knights were bold, and mobiles hadn’t been invented, this was how we got online, via a landline telephone, and we could even play a DVD on it. I then had to explain what a landline was and what that had to do with going online, and then I had to explain what a DVD was.

At which point she fell about laughing, whipped out her 5G mobile phone and sent crystal-clear photos and video to all her friends on WhatsApp, Facebook, Instagram, etc.

AI is accelerating this inversion.

Consider the numbers. India’s AI workforce is expanding from 650,000 professionals to 1.27 million by 2027 – a 15 per cent compound annual growth rate. Over 865,000 candidates have enrolled in AI and emerging technology courses. OpenAI, Google, and Perplexity have made their services free or dramatically discounted in India for extended periods – not from altruism but because they recognise India provides scale, data, and training opportunities unavailable elsewhere.

The voice AI market illustrates the pattern. India’s voice AI market, whilst smaller than North America’s in absolute terms, is growing faster and solving harder problems. Supporting twelve Indian languages with accurate accent and dialect recognition represents far greater technical complexity than optimising American English. Companies that master India’s linguistic diversity will quickly master global diversity, and dominate global multilingual markets. Those that don’t will find themselves perpetually playing catch-up.

For publishers, this creates an uncomfortable reality. The readers who matter most for future growth – the billions in India, Southeast Asia, Africa, and Latin America – will increasingly access content through voice interfaces that Western publishers neither control nor understand. These readers won’t buy physical books from London publishers or e-books from Amazon. They will consume content through platforms that integrate voice AI, local languages, and payment systems adapted to emerging market realities.

The Infrastructure Advantage: Data Centres and Compute Power

OpenAI’s planned one-gigawatt data centre in India represents more than infrastructure investment. It signals a fundamental shift in where AI computation will occur. Data sovereignty regulations in India and elsewhere mandate that data generated within a country be processed and stored locally. This isn’t merely legal compliance – it creates computational moats.

When AI training and inference happen in Indian data centres using Indian data, the resulting models understand Indian contexts, languages, and cultural nuances better than models trained elsewhere.

The same principle applies across emerging markets. Chinese AI trained on Chinese data serves Chinese users better than American alternatives. Southeast Asian AI will emerge serving regional needs.

Western publishers have spent decades centralising content production and distribution through New York, London, and Frankfurt. That centralisation made sense for physical books and early digital distribution. It makes no sense for AI-mediated content consumption.

A voice AI narrating a novel in Telugu, customising the narration style to listener preferences, and integrating with local payment systems, will not be managed from Manhattan.

Creating an ecosystem that Western publishers cannot match by simply adding AI features to existing businesses.

The IndiaAI Mission’s allocation of $1.6 billion (reflecting local costs) across seven pillars – including AI compute infrastructure with more than 18,000 GPUs, datasets and AI marketplace, and AI skills development – creates an ecosystem that Western publishers cannot match by simply adding AI features to existing businesses. The infrastructure gap is widening, not closing.

What Publishers Should Do: Embrace the Inevitable, Shape the Viable

The correct response for Western publishers is not to resist India’s approach but to advocate for similar frameworks in their own markets. A mandatory licensing scheme with fair statutory remuneration serves publishers’ long-term interests far better than the current chaos of litigation and uncertainty.

Consider the alternative scenarios. If publishers win their lawsuits and establish that AI training requires individual licences, they face negotiating with hundreds of AI companies whilst competing amongst themselves. Transaction costs explode. Smaller publishers and independent authors lack negotiating leverage. Major publishers might extract some revenue but will spend fortunes on licensing infrastructure. AI companies will either pay less than works’ actual value or, more likely, find creative ways around copyright – training on summaries, paraphrases, or synthetic data.

Worse, they will have spent years and millions on litigation that established they have no rights worth protecting.

If publishers lose their lawsuits and courts broadly embrace fair use for AI training, they receive nothing. Worse, they will have spent years and millions on litigation that established they have no rights worth protecting.

A mandatory licensing scheme offers a third path: guaranteed revenue proportional to AI companies’ success, minimal transaction costs, and automatic payment to all rights holders. Publishers should be demanding this framework rather than opposing it.

There are numerous start-ups offering such a service already – a chance for publishers to get ahead of the inevitable and get a first-mover price advantage.

On voice AI, publishers must stop thinking of it as an accessibility add-on or optional feature. Voice is becoming the primary interface for billions of potential readers. Publishers should be investing heavily in voice-optimised content creation, not merely converting existing books to audiobooks. This means commissioning works that exploit voice’s strengths – serialisation, interactivity, personalisation – rather than treating voice as a passive audio playback mechanism for text conceived for reading.

Publishers should also embrace AI-generated content where it creates value whilst humans retain creative control. The moral panic about “AI slop” ignores that much human-generated content is also slop. Let’s get real here – “AI-slop” is a convenient trash term for anything produced by AI that we don’t personally approve of.

We had this same bullshit when self-publishing took off in the late 200os and in the early 2010s in UK Europe.

We had this same bullshit when self-publishing took off in the late 2000s and in the early 2010s in UK Europe. The publishing gatekeepers revelled in predicting the “tsunami of crap” that would bring the industry to its knee. Self-published dross that no editor had set eyes on, thrown into the smelly cesspit of depraved desperation that was the Kindle store, with de rigueur home-made cover and a full quota of spelling mistakes in each paragraph.

“Penny Dreadfuls”, as one esteemed industry journal editor-in-chief called the British tsunami of crap as it overwhelmed readers and and stopped them finding gatekeeper-approved content.

That will be the same The Bookseller that in June this year reported that UK self-publisher LJ Ross had signed a deal with PRH for some of her titles. The Bookseller notes that Ross “is the most read adult fiction author in the UK” in Kindle Unlimited, and that the series is “the second bestselling series on Amazon UK after Lee Child’s Jack Reacher series.”

Just last week the Earl of Elitism, James Daunt, conceded that while he personally looks down his nose at AI-slop, he’ll sell it in Waterstone’s in a flash if he thinks it will line his pockets – oops, I mean, if readers demand it.

The question, then, is not whether AI participates in content creation, but whether the results serve readers.

AI-assisted translation into multiple Indian languages, AI-generated voice narration with emotional expressiveness, AI-powered personalisation of educational content – these enhance rather than diminish publishing’s value proposition.

The Great Reversal and What It Means

India’s proposed mandatory licensing framework and its leadership in voice AI represent something more profound than policy innovations. They signal a reversal of the traditional development hierarchy.

For two centuries, the West produced technology and content that eventually reached the rest of the world. That model is dying.

India, with its combination of massive scale, linguistic complexity, democratic institutions, and technological capability, is increasingly setting standards that the West must follow rather than the reverse. When India implements mandatory AI licensing, America and Europe will face pressure from their own AI industries to adopt similar frameworks. When Indian voice AI masters twelve languages and multiple dialects, Western systems will seem primitive by comparison.

Publishers who recognise this reversal and adapt accordingly will thrive.

Publishers who recognise this reversal and adapt accordingly will thrive. Those who continue viewing India and other emerging markets as lagging versions of Western markets will find themselves marginalised in their own territories as global platforms serve consumers better than traditional publishers ever could.

The choice is stark: evolve or become obsolete. India is showing the way forward. Western publishers would be wise to follow rather than clinging to a past that no longer serves anyone’s interests – including their own.

ADDENDUM 1 (of 2):

In comments, I was asked for examples of start-ups in the licencing space. The following are examples I’m tracking. There are likely others I’ve missed. (Please get in touch if you know of others.

Text/Publishing Content Licensing:

1. Amlet (Milan/Global, launched October 2025)

  • The world’s first AI content registry specifically for publishers
  • Uses International Standard Content Code (ISCC) for digital fingerprinting
  • Provides TDM (Text and Data Mining) registry with universal AI usage rights declarations
  • Partners with StreetLib and Bowker (US ISBN agency)
  • Two-tier model: Free basic registration, $29/title for premium features with advanced fingerprinting and priority licensing placement

2. Trainspot (San Francisco, launched October 2024)

  • AI data marketplace for books, images, video, and code
  • Two-sided marketplace where creators can price content, offer it free, or block AI use
  • Stripe-powered checkout for easy transactions
  • Focuses on legally sourced data for foundation models, fine-tuning, and RAG applications

Video Content Licensing:

3. Troveo AI (Austin, founded 2024)

  • Video licensing platform connecting creators with AI companies
  • Has distributed over $5 million in licensing fees to creators
  • Works with 1,300 licensors providing 1 million hours of processed video
  • Pays $1-4 per minute for quality footage
  • Revenue-share model; CEO claims “every major company developing video models is either already working with us or in our pipeline”
  • Raised $4.5 million in seed funding

4. Protege Media (formerly Calliope Networks)

  • “License to Scrape” programme for YouTube and platform creators
  • Aggregates audiovisual content (35,000+ hours of TV, film, news)
  • CEO Dave Davis previously worked at Motion Picture Licensing Corporation
  • Requires 25,000-50,000 hours of content to attract serious AI company interest
  • Part of the Dataset Providers Alliance promoting ethical AI training practices

5. Avail’s Corpus

  • Video licensing marketplace sourcing from YouTube creator networks like Viral Nation
  • Works with professional production companies and individual creators
  • Focuses on high-quality, high-volume content (minimum 1,000 hours per creator)

Music Content Licensing:

6. Rightsify / Global Copyright Exchange (GCX) (Pasadena, founded 2013)

  • Pioneer in ethical AI music licensing
  • Owns copyrights to 12+ million songs, 1 million+ hours of music
  • Hybrid licensing models combining flat fees, revenue sharing, multi-year agreements
  • Built own AI music model (Hydra II) trained exclusively on owned catalogue
  • Fairly Trained certified
  • Extensive music annotation (key, tempo, chord progressions, instrumentation)

Other Players:

7. Veritone

  • Established content licensing platform now serving AI training needs
  • Focuses on news, sports, UGC (user-generated content)
  • Full-service rights clearance and licensing expertise
  • Enterprise AI technology for content search and discovery

8. Vermillio (TraceID)

  • Content protection and licensing platform
  • 24/7 monitoring, AI risk scoring, takedown services
  • Partners with major entertainment companies including Sony Music
  • Focuses on both protection and licensing opportunities

These startups are essentially creating the infrastructure that India’s mandatory licensing proposal would systematise. Publishers who engage with these platforms now can establish pricing expectations, understand the market, and position themselves advantageously before any mandatory framework arrives. The first-mover advantage is particularly significant as these platforms are actively negotiating rates and terms that could become industry standards.

ADDENDUM 2 (of 2):

In comments, Richard Charkin asked. “Does the Indian proposal apply only to Indian-registered copyrights or all copyrights? How will they handle distribution of income – presumably via the existing RRO. The alternative would be incredibly difficult. If so then the main change is the elimination of opt-out. Is that correct?”

The answer (well, my answer anyway) is a mini-post, but here goes:

Territorial Scope – The Critical Ambiguity

The working paper refers to “Indian copyrighted content” and training on content that affects “Indian linguistic and cultural datasets“, but the documents don’t explicitly clarify whether this means:

  1. Only works registered under Indian copyright law, or
  2. Any copyrighted works used to train AI systems operating in India (regardless of where the copyright is registered)

The proposal mentions royalties would be linked to AI companies’ “global revenues” from systems trained on this content, which suggests they’re thinking broadly about commercial use rather than narrowly about territorial registration.

Distribution Mechanism – CRCAT Structure

You’re absolutely right about the RRO parallel, Richard. The proposal creates the Copyright Royalties Collective for AI Training (CRCAT) – a non-profit organised by existing copyright societies and collective management organisations (CMOs), then designated by the government.

The structure would, as best I can tell, and subject to change as the consultation moves forward, work like this:

  • CRCAT membership limited to organisations only (not individuals)
  • One member per class of work (literary, musical, audiovisual, etc.)
  • Distribution based on pro-rata usage – if 30% of training data is text, text copyright holders get 30% of collected royalties
  • Individual creators must register their works with CRCAT to be eligible for payment
  • Even non-members of copyright societies can register and receive payment

The Opt-Out Question

Yes, the elimination of opt-out is arguably the most radical element. Under the proposal as it stands:

  • Rights holders cannot withhold works from AI training
  • They cannot control how works are used or modified during training
  • They cannot choose which AI companies use their content
  • They can only receive statutory remuneration after the fact

This differs fundamentally from the EU approach (opt-out permitted) and even existing music licensing (where you can restrict adaptation/modification).

The Real Implementation Challenges

Your question exposes several practical nightmares that hopefully were at least considered, but were left for the consultation to explore:

1. International Works Problem: If a British publisher’s books are used to train an AI system operating in India, does CRCAT have jurisdiction? How would they even know? Would CRCAT need reciprocal agreements with British copyright collectives? The working paper doesn’t address this.

2. Attribution and Tracking: The proposal requires AI companies to disclose training data and provide “detailed summaries of training datasets”. But how granular? If OpenAI says “we used 10 million web pages including news articles”, how does CRCAT determine which specific Indian copyright holders get paid? So much work still to be done to flesh this out.

3. Burden of Proof: The proposal cleverly shifts the burden – if a rights holder claims their work was used, the AI company must prove it wasn’t. This presumption favours creators but could create a flood of spurious claims. Some mechanism will be needed to prevent the system being overwhelmed with spaghetti-at-the-wall claims.

4. The “Lawfully Accessed” Loophole: The licence only covers “lawfully accessed” content. Does this mean AI companies that scraped copyrighted works without permission owe nothing? Or does it mean they’re liable for infringement plus royalties? The Anthropic case (where using pirated sources led to a $1.5 billion settlement) suggests the latter, but India’s proposal isn’t clear, and I suspect current copyright law may leave loopholes.

5. Quality vs Volume Problem: This worries me: I envision a scenario (shared by some legal experts) where the flat-rate model incentivises flooding the system with low-quality content (and, dare I say AI-slop?) just to maximise royalty payouts since there’s no differentiation based on how valuable specific works were to the AI’s capabilities.

What India May Be Thinking

My beach speculation: India may be starting with a territorial approach (Indian-registered copyrights only) to establish precedent and infrastructure, knowing that:

  • International pressure and reciprocal agreements would follow
  • AI companies operating in India would need to comply regardless
  • The CRCAT model could become a template for international licensing schemes

The parallel to music collecting societies is instructive – PRS for Music in the UK and ASCAP in the US have reciprocal agreements. A British songwriter gets royalties when their song plays in an American restaurant because PRS and ASCAP cooperate. India may envision CRCAT eventually joining similar international frameworks.

Bottom Line

You’re right that if distribution goes through existing copyright infrastructure (adapted for CRCAT), the main revolutionary change is mandatory participation with no opt-out. But the territorial scope question and international enforcement mechanism remain worryingly undefined – perhaps (and hopefully) deliberately so during the consultation phase.

The 30-day consultation period will likely force clarification on these points, especially from international publishers and AI companies operating globally.

I’ll do my best to track this as it evolves, but meanwhile would love to hear what leading western AI observers like Thad McIlroy and Nadim Sadek make of the proposal so far.

On the Indian front, what AI progressives like Ilangoven Chinnusamy make of this. Amit Chavan has already added to the debate here.

This post first appeared in the TNPS LinkedIn newsletter.