AI Boom vs Dotcom Bubble: What’s Different About the 2026 AI Frenzy?

The AI boom has some striking parallels with the dotcom bubble of the early 2000s. But it also has some very distinct differences.

Like the dotcom era, simply adding “AI” to a company name today almost guarantees investor and media attention. In India alone, MCA filings show that in April 2026, 408 companies registered with AI and AI tech related names against 237 in April 2025 and about 86 a year earlier. In the UK, an average of 2,000 companies are being registered with AI in their names, according to the UK AI Sector Study 2024/25 and DataCentreNewsUK. In the US, FGS already tracks more than 8,000 AI companies.

The second interesting aspect is funding patterns. During the dotcom years between 2000 and 2002, investment was broad-based. Companies went public rapidly, raised money from retail investors and institutional investors alike, and the frenzy spread widely across markets. In the AI boom between 2023 and 2026 YTD, the opposite is happening. Capital is concentrating, not dispersing. One company alone — Anthropic — accounted for nearly USD 13 billion out of the roughly USD 40 billion raised in AI funding in 2025. The top AI firms and GPU companies are increasingly behaving like black holes, pulling disproportionate amounts of capital, talent and infrastructure into themselves. That is one of the biggest differences between 2000 and 2026. There have still not been many major AI IPOs yet, though the market expects giants like OpenAI to eventually test public markets.

The third difference is sectoral impact. During the dotcom boom, most internet companies emerged in consumer services, telecom, portals, media and basic web businesses. The AI boom is reshaping SaaS, enterprise software, fintech, healthcare, consulting and creative services. It is a very different spread, even as AI penetrates virtually every sector in the pursuit of efficiency, automation and cost reduction. One can argue that AI’s long-term impact may prove far deeper and more permanent than the internet boom itself. It can also be argued that what took the dotcom era three years to achieve, AI compressed into barely one.

Then comes the jobs question. The dotcom boom created jobs at massive scale — in India, the West and across Asia. Programmers, Java developers, HTML coders, web designers and IT service professionals became the defining workforce of the era. Even after the dotcom crash, the broader technology ecosystem survived and absorbed much of that talent. Coding and software engineering remained among the most valuable skills globally till the arrival of ChatGPT in November 2022.

The AI boom, however, is unfolding very differently. It is eliminating conventional white-collar jobs at a pace few imagined possible — including professions once considered relatively immune to automation, such as creative work, accounting and consulting. At the same time, it is creating a new class of highly specialised AI jobs. But unlike the dotcom era, the number of jobs being created is far smaller, even if compensation is significantly higher. AI is simultaneously emerging as both creator and destroyer.

The fifth aspect is perhaps the most important. During the dotcom boom, the internet technology itself was real. The companies often were not. Many businesses simply added “.com” to their names, launched basic web services and rode investor frenzy fuelled by massive FOMO. The same behavioural pattern is visible today. The underlying AI technology is very real and is already demonstrating measurable value. The issue is not whether AI companies exist or whether the technology works. The real debate, much like in 2000, is around valuation excesses.

“AI washing” has now become a widely used term in the media. It refers to companies aggressively branding themselves around AI despite having little or no meaningful AI capability in their actual business. The crucial difference today is regulatory scrutiny. Unlike the dotcom era, MCA in India now examines the AOA and MOA of companies to verify whether they genuinely intend to undertake AI-related business activities, instead of merely adding “AI” to the name to attract inflated valuations. That is a significant regulatory check. Presumably, many of these newly incorporated firms will actually work on AI and adjacent technologies, rather than simply deploying generic chatbots. Similar concerns are now emerging in the US, UK and EU as well, with regulators increasingly pushing for tighter disclosures around AI-linked business claims. 

AI Ads Are Getting Better. The Pricing Crisis Has Already Begun!

Over the past few days, I’ve been noticing a series of ads on YouTube carrying the “Created by AI” tag quite prominently. The latest one I saw (screengrab below) was for Hindustan Unilever’s Horlicks. It’s neat, smooth and, at first fleeting glance, almost indistinguishable from a traditionally shot commercial. It’s only when you notice the “Created by AI” tag that you realize what you’re actually watching.

The Air India Express campaign — repeated ad nauseam during the IPL — also carries the disclaimer “CGI rendering of aircraft” in its final frame. That’s in line with the synthetic media rules notified by the Government of India earlier this year. If the quality of the Horlicks ad is any indication, such disclosures are absolutely necessary. Earlier too, HUL had released an AI-generated campaign for Closeup Purple, and that too was executed rather well.

Visually, the output is impressive. But beneath the polish lies a deeper shift that the industry needs to acknowledge. 

The production cost of this Horlicks AI film may well have been a fraction of what HUL would have paid a traditional production house and agency. The problem is that brands are not benchmarking pricing against the savings from a conventional shoot. They are benchmarking it against the prevailing market price of AI production itself. And like every procurement process, companies will take 3-4 quotes and then drive prices down to the floor. We have seen this behaviour in many companies in the Middle East as well. Having played one against the other, they simply ghost you! 

That creates a difficult situation for the business. In a traditional agency ecosystem, it’s not always easy to play one creative shop against another at scale. In AI production, it’s ridiculously easy. There are now thousands of freelancers and boutique studios producing everything from average-quality outputs to genuinely world-class AI films. We see this ourselves. Agencies are now starting up their own AI studios to retain wallet share. 

The second challenge is that brands know AI software costs are falling rapidly. As tools become cheaper and more accessible, the reference point for pricing is collapsing. One argument we increasingly hear — including from some of the largest global firms — is: “If the software is cheap or free, why should production cost so much?”

One of the worst things to happen is if the marketing manager generates his own AI film, is pleased with it, and says:" If I can do this, why do I need you?". 

What they miss is that using AI tools once is easy. Delivering consistently high-quality output at scale is not.

Like traditional agencies are paid for ideation and execution, techno-creative agencies also need to be paid for prompt engineering, visualization and workflow design. Writing prompts that generate high-quality, brand-consistent output is not some casual exercise. It requires conceptual clarity, visual imagination, technical understanding and production discipline.

The industry’s biggest advertisers will do the ecosystem a disservice if they reduce AI production pricing to merely the cost of software. Clients are not paying for cheap tech. They are paying for techno-creative delivery that is on-brand.

At the same time, freelancers and smaller AI creators are also hurting themselves by undercutting indiscriminately. This is a skill, like any other specialized skill. There has to be a walk-away price. Not every assignment should be accepted at any cost. In our own work, we’ve seen well-known brands haggle over pricing like roadside vendors, even if it means compromising on output quality to save a relatively small amount.

This imbalance is unlikely to correct itself anytime soon. At least at this stage, pricing power in AI-led brand immersion services sits overwhelmingly with the buyer!

Rise of AEO and the future of search

I attended an interesting event in Mumbai yesterday: the launch of Saga AI’s software for AEO as opposed to SEO (reachsaga.com).

The company’s pitch is simple but significant. It wants to help clients improve their performance on “Answer Engine Optimisation” or AEO. In other words, ensuring that a client’s content and data appear prominently and get cited when people search through AI systems rather than through conventional search engines alone.

What struck me was not just the product itself, but what its existence says about how rapidly the internet is changing.

The explosion of AI, hallucinations and all, has already created an entirely new category of software tools. In some ways, this feels similar to what Google Analytics and related products once did for SEO, when businesses first realised that visibility on search engines could make or break them.

But this shift feels even faster.

These kinds of products, at least in their current commercial form, perhaps did not exist even two years ago. Yet they are now becoming central to how brands think about visibility, influence and discovery online.

The logic is straightforward. Users tend to click automatically on the top result. Increasingly, that “top result” is not a website link but an AI-generated answer box. If your brand, data or perspective does not appear there, you are effectively invisible.

What is also interesting is that we now seem to have multiple layers of search operating simultaneously.

There is classic search: type a query into Google and receive a list of links.

Then there is AI search: ask ChatGPT, Gemini, Claude or multiple AI systems the same question and receive synthesised answers. Apparently, using several AI engines simultaneously is now referred to as “co-use”, per Google. 

Even within traditional search, the distinction between search results and AI-generated answers is beginning to blur. Earlier, search was mainly about discovery and comparison. AI search, by contrast, is increasingly about direct answers.

That shift has consequences.

One obvious outcome is the deliberate flooding of the internet with content designed to influence AI systems. This means generating large volumes of blogs, tweets, Reddit posts, Quora answers and similar material so that AI engines repeatedly encounter and surface a particular client, company or viewpoint.

But here the contradictions begin.

Google and other platforms are also starting to penalise low-quality or obviously AI-generated content in an effort to prioritise more organic human-created material. So the system simultaneously rewards scale while attempting to preserve authenticity.

I am still not entirely clear how this tension between organic and synthetic content will eventually play out in search and discivery. But it is clearly going to shape the future of online visibility and influence in ways we are still discovering! 

93,000 jobs gone.

93,000.

That was the number in The Economic Times today.

93,000 people lost jobs or roles to AI in India in FY26. Those are only the visible numbers — the layoffs large enough to make headlines. For every known company that let people go because of AI, there may well be two others that did it quietly.

That number should worry India. It certainly worries me.

For one, I may well end up being one of the 93,000 someday. Second, I worry about where those 93,000 people go next, and whether India’s economy can absorb them fast enough into other sectors. Third, I worry about young people entering a world already shaped by war, instability, slowing opportunity and now an accelerating skills disruption. By the time retraining is complete, AI may already have moved ahead again.

And finally, I worry whether we are slowly setting ourselves up for social strain at scale.

As the Government of India, my single greatest direction of effort would be employment. India has 1.4 billion people. A population of that scale needs productive work, income, mobility and the ability to build a better future. People need to earn, spend, save, invest and contribute to the economy in a meaningful way.

Companies, meanwhile, exist for profit. They are not charitable trusts. Their job is to create wealth, improve efficiency and maximize output. AI does exactly that after the initial investment. It does not tire. It does not negotiate. It does not have moods, politics, fatigue or human inconsistency.

And AI will almost certainly become one of the major productivity engines driving India toward a $5 trillion economy.

And yet.

AI may well help drive GDP growth toward 10% a year — but increasingly without proportional employment growth alongside it. That is the real disruption here. 

Jobless growth: as a parent, it keeps me awake at night. 

Because if AI creates jobless growth at scale, where do the 93,000 of this year and the millions coming go?

 

He Predicted the Digital World Before It Existed Including AI: Arthur C. Clarke’s Reality Check

One can't but wonder at the vision, skill and technical understanding of the author Arthur C Clarke, who lived in Sri Lanka for most of his life and where the famous novels "Space Odessey 2001" was written along with the sequels. 

A lot of what he wrote and may be inferred is already true- 50 years after he wrote it. I thought it may be instructive to skim through some of his writings and state of realization today. The result is astounding. Arthur C Clarke would be justifiably very proud! Check this out, and as befitting the topic, AI has been used to good effect! Without the use of AI, it's very likely it would have taken me a day or more to compile this, or more, with results not as complete as I got! 

One of the striking passages in Space Odessey 2001, his seminal work, refers to the four genetically altered chimpanzees on board the space craft. These had been so genetically altered to be docile, low- maintenance, high energy servants, freeing up the humans on board for higher-level work. This is one of the radical ideas I think in his book, which hasn't yet come true. But we see the glimmerings of it: cloning and DNA spicing are known now. In Space Odessey 3001, Clarke actually writes about Velociraptors being modified to an extent that the joke is that if you leave a Velociraptor with a child, the Velociraptor is more likely to be hurt than the child! See the underlying assumption of Michael Crichton's Jurassic Park and its sequels, in one of which scientists actually make the dinosaurs docile enough to market them as companions! 

Was Clarke so far out?  

If we were to break it up into decades, what he wrote between 1960 and 1975 all came true- satellites and all. The next decade, while directionally he was right, he may be overestimated the speed at which his tech would be real. Nevertheless, there's no doubt he was one of the visionaries of his age! 

If you haven't read his books, do so : you will realize quickly enough the truth of the matter! 

    source: compiled by AI, guided by me. 

AI is a double edged sword!

The penetration of AI tools is rapidly increasing in daily life for mundane as well esoteric purposes. What was once generic for information -"google it"-  is fast becoming the preserve of the AI engines. Unconsciously we seem to click on the first result at the top of the search list- and once again we have boosted the AI world. 

The pace of change, and adoption are unprecedented! 

Inevitably perhaps, we tend to ascribe infallible status to AI, leading to a relaxation of standards which otherwise would have been rigorous. Intuitive , and often institutionalized checks and balances begin to dissipate or relax, leading to sometimes embarrassing gaffes and always chipping away at reputations and brands! 

Scan through linkedin, and you will find many examples. The latest was of a large MNC FMCG company which used AI generated images in its ads without checking that the fine print was all gibberish- the AI tool could not generate the lettering or words. These MNCs and their agencies pride themselves on top tier management/ brand management. How did this get through the sieve? 

There have been other such gaffes but equally there have been other terrific AI usages. Another rival MNC FMCG company apparently published a YouTube ad entirely made with AI- and using real life digital twins. In the fast paced ad, at first or even second glance, it wouldn't be possible to detect AI use. Perhaps this is what the company meant by "rationalizing ad spend". ( Interestingly, the use of digital twins opens up another discussion which I discussed in my previous post on NILP on this blog as well. Check it out). 

It is even more critical now for the HITL - Human in The Loop. AI cannot be the final word- that has to be the human, not perhaps for the dominance of Homo Sapiens over the AI army ( though that may soon be a concern) , but for the sheer skill and experience of the fabulous non-linear computer that is the human brain! 

Personality Digital Rights: the new AI battle

In the recent past, there's been a lot of news about celebrities going to the courts for protection against unauthorized use of their persona in social media. In other words, social media, apps, digital companies using the NILP (Name, Image, Likeness and Persona) of the celebrity without paying for it. 

That's a gross violation because the celebrity has full right to earn from his NILP- just as a company has full right to earn from its brand, product and service. It's like a fraudulent use to earn money. In addition, many celebrities have a moral hazard clause where they can refuse to endorse or give their rights to a product or service even if within the contract - say, Paan Masala or cigars and liquor. This is where highest risk lies, as the government of India now holds the endorser also liable for products / services he endorses. 

    compiled by AI 

The digital rights space is exploding as the social media markets boom. Unlike in the old days, an unauthorized use could have been restricted to one area or time; today it goes viral globally within seconds. In turn this means a product that would have cost crores for such an endorsement would get it for free if they could get away with illegal use of digital asserts. 

The root cause of concerns are deepfakes, voice cloning, imagery enabled by AI software that's getting ever more sophisticated and cheaper. The remedies fall into four main categories- cease and desist orders against John Doe (all unknown people), platform takedowns ( Youtube/ Insta/ X etc), ex-parte relief where the offender is known; and commercial bans (prevention of use in ads etc). 

The courts route is post facto action; given the scale, speed and sheer scope of NILP offenses, celebs need to look at proactive measures to protect and monetize their rights. 

How can this be done? 

For starters, it may be useful to create a repository with a firm ( like a celeb management firm or a law firm) to hold their NILP assets; this can be purely the rights to use a particular digital asset ( gait / speech/ image etc) which can be paid for and integrated by third party creators like ad agencies; and a tech database much like a vending machine in which you pay in the money, get the digital asset for a particular time and occasion, and which automatically disables once the contract is over. The former is an agency model, the latter a full-blown tech solution that allows full control and monetization. The celebs need to understand there will be a fee for this- after all, they get a majority of monetization, which is better than losing it all! 

India's AI sentiment meter trends down : anxiety on job losses increases

In December 2025 I had created and published an AI Sentiment meter in India. This was a simple assignment of weights to the headlines on AI carried in ET, Mint, HT and TOI. I chose these as the leading reflectors of business, policy and investment climate. You could choose another set if you prefer.

All headlines that mentioned job loss were assigned a weight of -5 ; all those that had job gains +5 ; all those that had efficiency and social gains were +3 , while all those that carried news on government control and support for AI use, were +3. The period I chose for analysis was March to May 2026.

The result is this - the net score is -35, with 11 negative headlines and 6 positives. there were some spikes with news of big-ticket AI data centres investment, but for the majority of people whom these papers reach, this is news that won't directly impact them, and if it does, not in the mass scale that India needs.  

There seems to be a clear anxiety in India on the job loss, actual and potential, due to AI and its adoption. As a nation, we are still at a stage where job and job losses can cause considerable social and economic friction, which would negate to some extent industrial efficiency gains. After all, if your consumers can't buy, how much will your efficiency help?

AI Sentiment Meter March- May 2026. Based on headlines on AI in ET, Mint, TOI and HT. 

That said, there is excitement on AI - and new jobs and roles will be created- but how fast and how many? Clearly, a tech that is predicament on efficiency cant crearte a billion jobs. 

If I were the government, I would be walking a tightrope. I want industry and India to grow fast, but I cannot risk social, economic and eventually political losses!