AI Jobpocalypse Or Market Correction?

Ever since OpenAI’s ChatGPT revealed itself to the world in 2022, the internet has been flooded with speculation about AI replacing human jobs. Then came the inevitable. Witnessing AI-native companies do more with less, several others started talking about leaner teams, too. Every productivity gain achieved on the back of coding copilots and autonomous agents nudged humans closer to the exit door until companies came out in the open, blaming restructuring on AI-led automation.

However, underneath this, a more complicated reality is emerging. Companies may simply be using AI as a convenient cover for post-pandemic corrections, restructuring and cost-cutting.

The rationale is simple: If AI coding tools are getting so powerful, why are software engineers still in demand? 

AI is undeniably changing workflows and speeding up certain tasks, but that does not mean human roles have suddenly become redundant. And if AI has truly become capable of replacing humans across organisational structures, why is its impact still far from visible? 

In fact, many enterprises are still struggling with basic adoption and workforce integration, exposing a gap between the promise of AI-driven transformation and its actual impact inside organisations.

Whatever the case is, the internet is abuzz with chatter around the AI job apocalypse. Facts, however, tell a different story — the one we are going to bring to the limelight in this edition of The AI Shift…

The Truth Behind The AI Job Losses

The “AI jobpocalypse” narrative grabbed headlines last week after AI researcher and Coursera cofounder Andrew Ng argued that fears around mass AI-led unemployment are becoming disconnected from reality.

“… Businesses have a strong incentive to talk about layoffs as if they were caused by AI. Talking about how they’re using AI with fewer staff makes them look smart. This is a better message than admitting they overhired during the pandemic when capital was abundant due to low interest rates and a massive government financial stimulus,” he said in a post on LinkedIn. 

Over the last three years, the global tech industry has already been undergoing a painful reset after pandemic-era overhiring. Companies hired aggressively under the assumption that digital adoption curves would continue indefinitely. However, growth slowed, capital became expensive again and organisations suddenly found themselves carrying inflated workforce structures built for a very different market.

AI simply arrived in the middle of this correction cycle.

Pankaj Goel, the CTO of an AI-powered CRM platform LeadSquared, too, reckons that AI has become an ‘easy headline’ for changes that were already underway. In his view, the current moment is less about AI taking jobs and more about companies redistributing work toward higher-order problem-solving and decision-making.

“In engineering, a single developer with the right AI tools can now ship what used to take a small team. If anything, this is just a productivity story more than a replacement story,” he added.

This distinction matters because the current AI narrative often assumes that higher productivity automatically means fewer jobs. But, historically, technology shifts have rarely worked this way. Instead, they tend to compress repetitive work while expanding entirely new categories of demand. The internet automated some workflows while creating massive digital industries. 

However, even inside enterprises aggressively deploying AI, the reality still appears far more complex.

While noting that much of the current layoff cycle is tied to post-pandemic corrections, Whatfix, an Indian SaaS-based digital adoption platform’s cofounder and CEO Khadim Batti underlined that many organisations are still struggling to get employees to use the AI tools meaningfully.

“Companies are selling an AI-first future while employees are still figuring out how to use the tools already available to them,” Batti said.

Terms like AI jobpocalypse, he added, have scared businesses and employees alike, slowed adoption at the exact moment organisations should be focused on learning, experimentation, capability building, and helping people adapt to new ways of working.

The Perfect Layoff Cover

Industry experts believe that AI has become the perfect corporate narrative for difficult business decisions. Earlier this year, Oracle reportedly laid off several employees globally while reallocating capital toward AI infrastructure, cloud expansion, and compute-heavy investments. 

Some are of the view that the layoffs were less about AI replacing workers and more about freeing up resources for future AI bets.

A similar pattern is emerging elsewhere. 

Earlier this month, Coinbase CEO Brian Armstrong announced a 14% workforce reduction while describing the crypto exchange’s shift toward becoming an “AI-native” company. 

But buried inside is another explanation. Crypto remains cyclical, markets remain volatile and Coinbase wants to reduce costs during a downturn. 

Such realities are increasingly arriving together across the tech industry.

Another example is Freshworks, which, citing AI-led productivity improvements and restructuring efforts, recently announced that it would lay off around 500 employees globally. At the same time, the SaaS major is also consolidating teams and redirecting spending toward higher-priority verticals.

For many companies, AI has effectively become a cleaner framing for operational tightening, margin protection and restructuring.

Beerud Sheth, cofounder and CEO of Gupshup, a conversational AI and enterprise messaging platform, agrees that AI will inevitably create some redundancies, but argues that reducing the conversation to layoffs misses the larger shift underway.

“The companies fixated on cost-cutting are the ones that have run out of ambition before they run out of opportunity… For companies with vision, AI-driven superproductivity unlocks entirely new markets and product lines. AI is fundamentally a growth engine, not a cost lever, unless you choose to use it that way,” Sheth said.

AI’s Real Impact Lies Beyond Layoffs 

The stronger long-term impact of AI may not be mass unemployment, but how companies hire, structure teams, and define work.

Explaining to Inc42, Gupshup’s Sheth said that AI has completely restructured workflows inside the SaaS company. According to him, engineering teams that once required 10 to 15 people are increasingly operating through much smaller AI-assisted pods.

“The question was never how do we do the same with less. It’s what we can build that was previously impossible,” Sheth said. 

That may explain why software engineering hiring has not collapsed despite rapid improvements in coding agents. Perhaps software engineering was never just about writing code. There exist various deeply human layers of software creation. AI can accelerate parts of the stack but it does not eliminate the complexity surrounding it.

However, the nature of engineering appears to be changing. Product managers are becoming builders. Designers are prototyping code. Engineers are operating across broader layers of execution. And when the cost of building software falls, organisations tend to build more, not less.

Overall, AI won’t eliminate work the way the internet fears it will. It is quietly redefining who gets hired, what skills matter and how organisations operate. The real shift is not fewer humans but fewer repetitive roles and far greater demand for people who can work alongside AI.

Top Stories From India & Around The World

• Inc42 AI Summit 2026: India’s AI market is heading toward $126 Bn by 2030, and the people building toward that number will be in one room on May 28 at The Inc42 AI Summit 2026. The agenda is now live, and it is everything you would expect from India’s largest invite-only AI summit
• Cerebras Chip Lands In India: Last week, the President of the UAE gifted the AI chip to PM Narendra Modi, formally advancing the 8-exaflop supercomputing partnership. The project will deploy 64 Cerebras CS-3 chips to build one of the largest compute clusters in the country.
• Mobavenue’s Q4 Profit Zooms: The listed adtech company reported a 60% YoY jump in profits to ₹8.4 Cr in Q4 FY26, while revenues rose 42% YoY to ₹62.6 Cr. Mobavenue offers an AI-powered platform that helps digital-first brands advertise more effectively.
• Numero Acquires Royu: The US-based AI finance platform has acquired the Chennai startup in a “double-digit million-dollar” cash-and-stock deal. The combined entity plans to build an “agentic AI worker layer” for enterprise CFO offices.
• Codex Comes To Mobile: OpenAI has launched the offering as a preview on the ChatGPT mobile app, allowing developers to manage coding agents remotely from their phones. Users can review outputs, approve commands, monitor terminal activity and steer coding workflows across laptops and remote environments.

The Weekly Buzz: Razorpay’s AI Coworker

AI is no longer confined to copilots and coding assistants. It is increasingly becoming an operational coworker embedded across organisations. In a recent post, Razorpay cofounder Shashank Kumar revealed how the fintech giant internally built its AI assistant, Slash, which is now deeply integrated into the company’s workflows.

Accessible directly through Slack, Slash can read Razorpay’s codebase, debug production incidents, write code, analyse logs, review and raise pull requests (PRs) autonomously. 

Adoption inside the company has also exploded rapidly. From handling 122 tasks in its first week six weeks ago, Slash processed more than 14,800 tasks last week alone.

The company said Slash raised over 2,150 PRs in a week, with 45% shipping without any human rework. Engineers are increasingly using it for incident resolution, Kubernetes optimisation, testing and security remediation, while product and analytics teams are leveraging it for research, SQL pipelines and workflow automation.

What stands out is that Slash is not limited to engineering teams. Razorpay claims more than 250 non-engineers actively used the AI assistant last week, including account managers tracing payment failures and support teams triaging tickets before escalating them to developers.

The broader signal is that enterprises are moving beyond isolated AI tools toward organisation-wide AI operating systems embedded into everyday collaboration platforms. At Razorpay, Slack itself is increasingly becoming an AI-native workspace where debugging, operations, support and software shipping happen through conversational workflows.

Startup In The Spotlight: Pixie

As parents increasingly struggle to balance screen time, learning and entertainment for young children, a new category of AI-native products is emerging around personalised, voice-first experiences. 

Founded in 2026 by Shiv Bansal and Rahul Agarwal, Pixie is building an AI-powered audio platform designed for kids. The startup generates personalised audio stories, educational content and interactive experiences tailored to a child’s age, interests and learning stage. Parents can input scenarios such as anger control, sharing or bedtime routines, while Pixie’s AI engine creates custom stories with voice modulation, sound effects and multilingual narration.

Under the hood, Pixie uses an LLM orchestration layer with multiple AI models, guardrail agents and prompt tuning systems to ensure age-appropriate and safe content generation across languages including English, Hindi, Tamil and Telugu. A key part of Pixie’s product strategy is its focus on adaptive learning and long-term personalisation. Every interaction helps the platform better understand a child’s learning curve, vocabulary familiarity, behavioural patterns and content preferences. 

The platform currently has over 6,000 monthly active users and offers subscription plans in both India and the US. Beyond entertainment, Pixie is increasingly being used for language learning, public speaking practice and concept-based education, positioning itself at the intersection of AI, parenting and child-focused edutainment.

The company is also experimenting with voice-controlled interactions, weekly parent reports and bilingual learning experiences, particularly targeting Indian and global households looking to preserve regional language familiarity among children growing up in multilingual environments.

Prompt Of The Week

What prompts and hacks are CTOs, CEOs and cofounders using these days to streamline their work? 

Here’s the prompt used by Jay Jenkins, CTO of Cloud Computing at Akamai to turn large proposal reviews and scattered project updates into an AI-powered executive auditing and decision-support workflow.

“Act as an expert auditor. 

Review the source titled  [our current draft] against all other selected sources in this notebook (the customer’s requirements). 

Be brutally direct. Cite sources.

Please provide:

• Alignment Check: Does our draft accurately address the customer’s primary goals, pain points, and explicit requests found across the other sources? Summarize the key strengths and weaknesses.

• Gap Analysis: What did we forget? Provide a bulleted list of any critical requirements, technical constraints, or specific requests mentioned in the customer sources that are missing, understated, or completely overlooked in our draft.”

Editor’s Note: Some prompts may need to be adjusted by users for best results or may not work as intended for certain users.

[With inputs from Shraddha Goled]
[Edited by: Shishir Parasher]
[Creatives by: Varshita Srivastava]

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