Top 7 ‘tech innovations’ IT firms used to possibly ‘gaslight’ investors and the public in the last 10 years

Technology does not fail because it is new. It fails when companies sell a vague future as though it were a present-day product.

Over the past decade, the tech industry (technically, the IT services industry when it comes to India) has repeatedly, allegedly, renamed old problems, attached a buzzword, raised prices and asked customers to believe that transformation was just around the corner.

Yes, good tech requires research. But not every GitHub-level commit is a business model. It might sell in the boardroom when looking for seed funding, but it barely has any use case when it trickles down to the people who really matter—the end-user customer.

So, here are ten innovations that prompt us to ask whether they were innovations or desperate marketing stunts:

1. The meta in Metaverse

The metaverse was sold as the next internet: offices, concerts, shopping malls and entire economies rendered in headsets. McKinsey projected in 2022 that it could generate up to $5 trillion in value by 2030, while more than $120 billion flowed into the space that year.

Then reality knocked on the door. Gartner placed the metaverse in the “trough of disillusionment”, where interest falls as experiments fail to deliver. Microsoft shut its industrial metaverse team in 2023, and Meta’s multibillion-dollar Reality Labs losses became a recurring reminder of how virtual even the dreams built on the Metaverse were.

Back when the hype reached India, we saw many a hollow pitch. For a country still negotiating data costs, device affordability, and digital literacy, asking its citizens to believe that virtual real estate and avatar meetings were the next productivity frontier was the true meta.

2. Developing for VR, AR and XR headsets

When virtual reality arrived, it was supposed to replace screens. Instead, it mostly became an expensive accessory for gaming and corporate demonstrations.

The only place a VR headset was not expensive was in the 2018 Steven Spielberg hit Ready Player One. All it took to wane was the sheer impracticality of it, hefty entry prices, and a pandemic that should have—ideally—made the tech more adoptable. But it went the other route.

By 2023, worldwide AR/VR headset shipments fell 23.5 per cent according to IDC. Omdia later estimated consumer VR sales fell another 10 per cent in 2024 to 6.9 million units.

Apple’s Vision Pro was the one thing that kept the attention, but its high price meant that these Daft Punk helmet wannabes remained a premium curiosity rather than a mass-market accessory.

But tech companies did not immediately accept the failure. They kept rebranding the category as “mixed reality” and “extended reality”. Whatever the label, they couldn’t solve the basic issue: most people do not want to strap a computer to their face to read WhatsApp messages and doomscroll Instagram.

3. The advent of the ‘Metaverse clones’

How much meta can Metaverse get? This one takes the cake.

When the original metaverse pitch faded, many firms did not abandon it. In a frenzy to “provide value to stakeholders”, they repackaged it.

Virtual showrooms became “immersive commerce”. 3D training modules became “digital twin ecosystems”. A browser-based meeting room with avatars became an “enterprise metaverse platform”.

The underlying product was often a web app with better graphics, but this time it carried a larger invoice.

Was it fraud? Inherently no. But was it misleading when sold as a technological leap? You be the judge of that.

In all of it, many firms forgot that a 3D catalogue is not a new economy, and that a virtual meeting room was not a replacement for a functioning workplace (unless 2020 does a repeat, that is!).

4. Introducing Digital Twins

Among the VR tech and Metaverse was one solid concept—digital twins. It had legitimate industrial uses: simulating a factory line, a jet engine or a power grid can help engineers test changes before committing capital.

But then ‘PowerPoint artists’ adopted it, and the problem began when the word migrated into sales decks.

Suddenly, every dashboard, sensor feed and visualisation became a “digital twin”. In many cases, it was simply monitoring software with a 3D model attached.

But the original concept was solid: a real twin required reliable data, validated models and a decision-making loop. Without those, it was a costly animation of a business “pain point”.

5. Blockchain here, Blockchain there, Blockchain everywhere

When Bitcoin and Ethereum exploded into the scene, it brought with it a great logical technology innovation—Blockchain. Once again, IT fellows powered by MBA-led marketing departments pounced on it.

Soon, Blockchain was promoted as the fix for trust itself: supply chains, land records, voting, music royalties, healthcare, and even loyalty points. Like any solid tech logic, some uses were very good. But most of them were solutions looking for a problem.

The core value proposition was decentralised, tamper-resistant records. But most of the time, they were irrelevant—almost pointless—when a single company controlled the network, the data, and the participants. Gartner then went on to do a damning commentary on early Web3, where it noted that some projects were possible scams and others lacked sustainable business models.

In India, blockchain was then marketed for everything from farm-to-fork traceability to certificate verification. Tech parks championed it. Most companies slapped it on their frontpage. But they forgot the underlying issue that no amount of tech could solve in later stages: garbage data entered at the source remains garbage on a blockchain.

6. ‘AI-powered’ everything

Post the metaverse hype and the Blockchain trend, the latest vibe is artificial intelligence. Every app now has an AI assistant, an AI summary, an AI search bar or an AI-generated suggestion. Did users ask for it or not? No one bothered to check.

Yes, the technology can be useful. But adoption does not equal value. MIT’s NANDA report found that 95 per cent of enterprise generative-AI pilots in its dataset produced no measurable profit-and-loss impact.

In India, once again, the latest in tech is championed by IT service firms (most of whom are wrapper makers with no original end-to-end product), and they have championed something that once again follows a similar pattern: AI chatbots are added to a banking app, an e-commerce site or a government portal, then marketed as transformation.

But if they cannot resolve a complaint, retrieve the right document or reduce waiting time, are they really transformative? Or are they just virtual chatbots with better branding?

7. Premium hardware for unfinished software

In the AI wave, the latest trick is pricing ambition as innovation. Due to AI, more chips are required. Who buys them? Tech firms. Who makes them? Other tech firms. Who controls supply? Tech firms. Who controls demand? You guessed it. And somehow, the loser is the human consumer.

Now, we have “AI PCs” with premium badges, and a 15-50 per cent hike in prices. A basic mid-tier processor laptop with internal graphics, which used to be ₹40,000-45,000, is now in the ₹50,000-80,000 range. ₹90,000-1,20,000 high-end laptops now retail for ₹2,00,000 to even ₹4,00,000.

And enterprise software for small businesses was now repositioned with AI add-ons, but with almost no noticeable improvement in underlying workflow.

By 2024, AR/VR headsets that barely any common consumer wanted saw their average selling price of AR/VR headsets rise above $1,000, as per IDC. Back in India, NASSCOM found that only 10–15 per cent of enterprise generative-AI proofs of concept in India had moved to full-scale production.

Simply put, ‘AI hardware’ arrived, and customers are asked to buy the future at steep prices before any of it works. If you are disappointed, that is the price of “early adoption”.

Are we being gaslit?

“Gaslighting” is a strong word. Not every failed technology is a scam, and innovations involve uncertainty. But when companies repeatedly oversell immature products, obscure limitations, rename failures, and charge customers for speculative capability, it presents us with something even more profound: people are made to doubt their own reasonable judgement.

For the decade that was, tech firms have not done themselves any favours in terms of trust. But the Litmus test for the next decade is much simpler. All they have to ask themselves is:

Does it solve a real problem?

Can an ordinary user see the benefit?

Does the price reflect delivered value rather than projected hype?

Until then, “innovation” will keep meaning the same thing it has too often meant: a new way to sell old inconvenience, and one more way to “deliver value to key investors and stakeholders”.