Incoming: The AI upheaval for blue-collar jobs

Hardly a week passes without fresh headlines about white-collar jobs falling prey to AI. Most recently, Meta Platforms Inc. laid off nearly 8,000 employees globally as part of CEO Mark Zuckerberg’s broader AI-driven restructuring strategy, while LinkedIn announced more than 600 job cuts set to take effect in mid-July. According to layoffs.fyi, 152 tech firms have cut 115,430 jobs so far in 2026.

That number is likely to rise as Generative AI increasingly writes reports, generates code, analyses data, creates presentations and mimics human conversation with startling fluency. AI agents are pushing automation even further by planning, reasoning and carrying out multi-step tasks with minimal supervision.

Optimists argue that, like previous technological revolutions, AI will augment workers, boost productivity, and create entirely new jobs and industries. For instance, Sam Altman believes AI will not trigger a global “jobs apocalypse”. Pessimists counter that this wave is fundamentally different because AI is scaling cognitive capability at an accelerated pace and at near-zero marginal cost.

Speaking at a Vatican gathering where Pope Leo XIV formally released his first AI-focused encyclical, Magnifica Humanitas, and called for AI to be “disarmed” to protect humanity from its unchecked dangers, Anthropic PBC co-founder Christopher Olah warned that AI could trigger “large-scale” job displacement, echoing co-founder and CEO Dario Amodei’s warning.

In this week’s edition of Tech Talk:

• Your boss may be quietly sharing your data with Big Tech
• Flipkart bets AI can turn internet users into shoppers
• Seven AI gadgets of 2026 that actually feel useful
• AI tool of the week: OpenAI’s Verify

White-collar to blue-collar

Anxiety over AI is no longer confined to white-collar work. There is growing concern that AI robots can increasingly disrupt physical labour as well. In May 2025, Bank of America Global Research predicted that humanoid robots will see mass adoption in highly unstructured environments—from households to elderly care—by 2035. The firm forecast annual humanoid shipments could reach 1 million units between 2030 and 2035, before eventually rising to 3 billion globally by 2060.

Those projections rest on bold assumptions: humanoids replacing 20% of industrial workers and 50% of service-sector workers; each robot substituting for 2.5 industrial workers or 1.5 service workers; and household penetration eventually reaching 0.7 robots per home.

Whether those estimates materialise remains uncertain. What is clear, however, is that humanoids are becoming increasingly capable as Gen AI and Agentic AI are fused into robotic systems, giving machines the ability not just to execute commands, but also to reason, adapt and autonomously complete tasks.

The trajectory is striking. Back in 2017, Sophia—the humanoid developed by Hanson Robotics—became the world’s first robot to receive citizenship from Saudi Arabia. This month, Unitree Robotics unveiled the GD01, a nearly 10-foot-tall mecha capable of shifting between bipedal and quadrupedal movement, evoking something closer to the movie ‘Transformers’ than traditional industrial machinery.

Attention is all you need

China is reportedly planning to assign digital identities to every humanoid robot manufactured in the country, enabling lifecycle tracking from production to recycling. According to reports, more than 100 Chinese humanoid manufacturers and over 28,000 robots across 200 models have already been assigned such IDs.

Yet the larger question is no longer whether robots will enter workplaces, but how deeply they will reshape labour itself.

Amazon.com Inc. offers perhaps the clearest glimpse of that future. Since acquiring Kiva Systems in 2012 and launching Amazon Robotics, the company has deployed more than one million robots across its operations network. The company now integrating Gen AI and Agentic AI into its robotic ecosystem to create increasingly autonomous machine labour. Its DeepFleet Gen AI foundation model is designed to make the company’s robotic fleet smarter and more efficient. Project Eluna uses agentic AI to optimise workflows and improve operational safety.

The machines themselves are also becoming more sophisticated. Hercules robots can lift and transport up to 566 kg of inventory. Pegasus uses precision conveyor systems to sort individual packages. Proteus, Amazon’s first fully autonomous mobile robot, can navigate around workers in open environments while hauling heavy carts. Vulcan adds another layer of capability with a sense of touch, allowing it to detect and adjust contact with objects.

Costs: Robotic labour vs Human labour

For years, humanoid robots were sold as the ultimate cheap workforce—tireless, scalable, and immune to wages, unions, or burnout.

But a single advanced robot may contain thousands of components and hundreds of moving mechanical parts—actuators, motors, gearboxes, sensors and cameras. Many systems also require expensive graphics processing units and continuous AI inference to operate in real time. That hardware stack is costly. The likes of Unitree Robotics, Boston Dynamics, Tesla Inc. and Figure AI are pushing prices down, but even then, commercial humanoids can cost anywhere between $20,000 and $150,000, or more.

And the robot itself is only part of the bill. Deployment also involves software integration, safety systems, cloud infrastructure, maintenance, remote monitoring, and human supervisors. In many cases, so-called autonomous systems still rely on tele-operators and engineers working quietly behind the scenes. The irony, hence, is that replacing labour currently requires enormous amounts of human labour.

Yet, the economics may change precisely because robots are starting to participate in manufacturing itself. Industrial robotic arms already build components used in other robots. Unitree Robotics is already experimenting with humanoids on assembly lines, while Boston Dynamics’ Atlas is being positioned for industrial logistics and manufacturing environments.

This creates a potential feedback loop: Humans build early robots. Robots help manufacture future robots. Production costs fall. Automation deepens. And even more robots become economically viable. While the vision of factories automating their own expansion is seductive, there is a massive gap between robot-assisted manufacturing and fully autonomous robotic self-replication. Humanoids remain poor at delicate wiring, troubleshooting, repairs, and handling chaotic real-world variability.

For now, human labour is cheaper, more adaptable, and easier to deploy. A warehouse worker can improvise, recover from mistakes, navigate uncertainty, and perform multiple physical tasks without needing millions of dollars in training data or precision engineering. A humanoid robot, by contrast, may struggle with something as simple as a loose cable or an unexpected object placement.

You may also read about the disillusionment with AI software tools that are proving more expensive than human labour: ‘AI promised cost savings, but Microsoft and Uber say it’s costing more than human workers’.

Economics depends on Geography

In high-wage economies facing labour shortages and aging populations, robotic labour may eventually make sense. In lower-wage environments like India, the numbers are far less compelling.

That said, like early computers or electric vehicles, humanoids may currently appear inefficient, expensive, and overhyped until scale changes the equation. If hardware prices fall, AI models improve, and factories become increasingly automated, robotic labour could eventually become dramatically cheaper than human labour in repetitive industrial work.

But that future is not here yet. Today’s AI humanoids are less a replacement for human workers than a reminder of how much invisible human effort still underpins the automation revolution itself. But we need to prepare ourselves for a future where robots take over routine chores and tasks, similar to how washing machines, vacuum cleaners and food processors are complementing—and, in some cases, even replacing—house help.

🔗 Why Pronto’s physical AI training pilot is drawing scrutiny

AI TOOL OF THE WEEK

By AI&Beyond, with Jaspreet Bindra and Anuj Magazine

The AI hack we unlocked today is: OpenAI Verify

What problem does Verify solve? Here is a friction point that is becoming impossible to ignore: you receive an image, a product shot, or a photograph, and you have no reliable way to know if it was AI-generated. The image looks real. And you are expected to make a judgment call with nothing but instinct.

OpenAI’s verification tool addresses this directly. Upload any image, and it checks for two types of provenance signals: C2PA Content Credentials (cryptographic metadata that identifies origin) and SynthID (an invisible watermark embedded in the image’s pixels that survives screenshots, crops, and format conversions).

A positive match confirms the image came from ChatGPT, the OpenAI API, or Codex, along with details on how and when it was created.

How to access: https://openai.com/research/verify

The tool can help you:

• Confirm before you share: Check any image before publishing, forwarding, or approving it for official use.
• Surface what metadata hides: SynthID detection works even after screenshots or edits strip the original file metadata.
• Build a verification habit: A 30-second drag-and-drop check that turns provenance from a vague concern into a concrete step.

Example: A communications lead at a financial services firm receives images from an external agency for an upcoming campaign. Before sign-off, she wants to confirm none were AI-generated without disclosure.

• Upload the image: Drag and drop or click to upload, one image at a time
• Run the check: The tool scans automatically on upload, no prompt required.
• Read the result: Returns whether it detected C2PA metadata, a SynthID watermark, or no supported signal.
• Act on the finding: A positive signal confirms OpenAI origin with creation details; a negative result narrows but does not eliminate AI involvement.
• Switch formats: If the original file returns an error, re-upload as a cropped screenshot for better signal detection.
• Document it: Screenshot the result for internal records or compliance reporting.

Edge case worth knowing: A missing signal does not mean the image is not AI-generated: metadata can be stripped, watermarks can degrade, and the tool currently only detects images from OpenAI’s models, not those from other AI platforms.

What makes this tool special?

• Dual-signal detection: Combines C2PA metadata and SynthID watermarking, catching what either method alone would miss
• Watermark that survives transformation: SynthID is embedded in image pixels, not file headers, so it holds through screenshots, resizing, and format changes
• Free, public, no account required: Accessible to anyone verifying content, not just OpenAI users or paying customers.

Note: The tools and analysis featured in this section demonstrated clear value based on our internal testing. Our recommendations are entirely independent and not influenced by the tool creators.

AI BITS & BYTES

Your boss may be sharing your data with Big Tech

The app your employer uses to track attendance, productivity or work hours could also be sending your data to tech giants like Google, Meta and Microsoft. A new study has found that these workplace monitoring apps, often referred to as “bossware”, are also sharing employee data with digital advertising platforms and data brokers.

Not a fan of Google AI Search? Try these instead

As Google expands AI Summaries and conversational search, many users are exploring alternatives. Here are six search engines offering privacy, fewer ads and a cleaner web experience. You may also read: Google won’t let you disable AI in Search, but these tricks still work.

7 AI gadgets of 2026 that are actually useful

AI gadgets in 2026 are finally moving beyond hype, with smart glasses, AI rings, fitness trackers, and wearable assistants offering practical features. From Fitbit’s AI-powered wellness insights to Meta’s smart glasses and Samsung’s Galaxy Ring, these devices focus on convenience and productivity.

🔗 ALSO READS

• OpenAI new job will pay ₹3.7 crore. The task: stop AI from building itself
• AI battle: Altman beat Musk in court but OpenAI could lose Wall Street
• Flipkart bets games and AI can turn internet users into shoppers
• Spotify is using AI to turn long-form articles into in-app podcasts
• The wonderful world of whimsical websites: How to beat scrolling, AI slop

Tech Talk is a weekly newsletter by Leslie D'Monte on everything happening in the world of technology and AI. Want this newsletter delivered to your inbox? Subscribe here.