In the wake of the week…

AI’s promises around hiring, productivity, and organizational efficiency continue to collide with operational reality. Companies that rushed to replace workers with automation are now walking it back, at least for now. Meanwhile, Big Tech is not retreating. They’re laying the groundwork for leaner teams led by humans managing fleets of AI agents.

This week’s stories reveal a growing divide between the intentions of tech leadership and the lived experience of workers. Whether measured by morale, motivation, or market performance, AI's integration into the workforce is proving far more complex than early narratives suggested.

And in Extra Credit: Behavioral research shows GenAI boosts output but erodes motivation. A laid-off engineer shares what it’s like to go from six figures to DoorDash. And Vox delivers a hands-on guide to which AI model does what best.

Let’s dive in. 👇

AI Promised to Revolutionize Hiring. It Might Be Breaking It Instead.

Deloitte’s 2025 outlook on talent acquisition tech imagines a seamless, AI-powered future: autonomous agents handling sourcing, screening, and interviews with precision and personalization. But job seekers and hiring managers tell a very different story. According to The Washington Post, the real job market is a chaotic tangle of ghost jobs, AI-written résumés, and mounting distrust, where automation often creates noise, not clarity.

While Deloitte highlights strategic transformation, candidates face a sea of fake job postings and bots that schedule interviews no one attends, managers are blindsided by deepfake applicants, and recruiters are drowning in AI-generated résumé spam. The disconnect reveals a market where AI adoption is outpacing organizational readiness, creating friction where it promised fluidity.

By the Numbers

• 70% of companies now use AI in at least one part of the hiring process (McKinsey)

• 150 job applications submitted in 7 minutes for a single LinkedIn post

• 15+ nearly identical résumés received for a single job, written by the same optimization service

• 56% of companies using AI in TA aim for productivity, not transformation (Deloitte)

Why It Matters

Talent acquisition is one of the most aggressive adopters of AI, but many systems prioritize speed over substance. Deloitte’s vision depends on precision, integration, and trust. In reality, most companies deploy fragmented tools without the governance, training, or design needed to deliver a better experience. The result? A credibility crisis on both sides of the hiring desk.

Leadership Insight

A fractured hiring experience weakens employer brand and undermines long-term talent strategy. Leaders should resist the urge to automate for its own sake and instead focus on coordinated AI deployment that prioritizes candidate experience, recruiter workflow, and ethical safeguards. Transformation demands orchestration, not just tools.

The Bottom Line: The future of AI in hiring looks promising in a consultant’s vision deck, but messy in practice. Until organizations align implementation with intention, the talent experience will remain inconsistent, inefficient, and too often inhuman.

Sources
Deloitte: 2025 talent acquisition (TA) technology trends
Washington Post: Job hunting and hiring in the age of AI: Where did all the humans go?

Backfire or Backpedal? Give It a Name, but Workforce AI Replacement Faces a Reckoning.

The gap between AI vision and on-the-ground reality is not limited to hiring. Some companies are now reversing course entirely after moving too quickly to replace elements of their workforce with automation.

Klarna once touted itself as the perfect AI test case. After cutting marketing contractors in 2023 and replacing hundreds of customer service agents in 2024, the company declared that AI could handle everything from chat support to creative production. That vision has changed. Klarna’s CEO now says the company will launch a major recruitment drive to restore live human service. In his words, “what you end up having is lower quality.”

Duolingo, which announced an AI-first policy earlier this year, has not reversed course but is facing heavy backlash online. Users on TikTok and other platforms have called out the company’s decision to replace contractors, questioning whether language learning can remain effective or ethical without human teachers in the loop.

Multiple reports confirm what these cases suggest: rapid replacement rarely delivers lasting value. Most companies still investing in AI are struggling to scale their results. Only one in four executives reports seeing significant impact. Many now face stalled adoption, rising frustration, and internal pressure to prove ROI.

By the Numbers

• 64% of customers prefer that companies avoid AI in service roles (Gartner)

• 55% of UK leaders who replaced workers with AI now regret the decision (Futurism)

• Klarna claimed $10 million in marketing savings and 700 AI-driven agent equivalents

• 25% of executives report measurable impact from AI (BCG)

• 67% of companies plan to maintain or increase AI investment in 2025 (Coastal)

What to Expect

The next phase of workforce design will emphasize measured integration over wholesale automation. Hybrid teams are emerging as the default model—AI for acceleration, people for nuance and accountability. Klarna is reportedly exploring gig-style staffing to balance flexibility with human support. This pivot and similar reversals at firms like Target and Walmart reflect a growing realization: AI is supplemental, not a full-scale workforce replacement.

But don’t get too comfortable. Many tech leaders remain committed to automation as an economic imperative. If full replacement does not work the first time, they will try, try again. Anthropic’s cofounder Jack Clark recently described a future where managers supervise “fleets of AI agents” rather than teams of people. Startups are already operating with fewer staff. Meta’s Mark Zuckerberg and Y Combinator’s Garry Tan echoed similar views, each pointing to AI’s role in reducing headcount and compressing teams. The economic incentive is clear. The ambition has not changed.

Leadership Insight

Technology without workflow design, trust, and human oversight produces unreliable outcomes. Leaders must stop treating AI as a shortcut and start treating it as an operating model shift. Hiring, service design, and team composition all require realignment when humans and AI operate together. Efficiency gains are possible, but only when people remain central to the equation.

The Bottom Line: AI-first was easy to market but difficult to operationalize. The companies reversing course are learning that real transformation requires more than model access. It requires judgment, coordination, and a people-first operating model.

Sources
Fast Company: Going ‘AI first’ appears to be backfiring on Klarna and Duolingo
Futurism: Company Regrets Replacing All Those Pesky Human Workers With AI, Just Wants Its Humans Back
Business Insider: The AI mistake companies are making — and how they can fix it, according to a BCG tech leader
Business Insider: The age of incredibly powerful 'manager nerds' is upon us, Anthropic cofounder says
Fortune: Here’s what your future workforce will really look like

AI Is Changing What It Means to Be Human. Work May Never Be the Same.

Today’s automation efforts may be faltering, but the long arc of AI still bends toward full-scale cognitive disruption. The question is no longer if AI will take over more work—it will, and a lot of it—but what that means for us humans when it does.

A new essay by renowned economist Tyler Cowen and Anthropic’s Avital Balwit lays out a profound shift already underway: as AI systems exceed human performance across a growing range of intellectual tasks, the nature of human identity, contribution, and work is being challenged.

Recent advances in models such as GPT-4 and Claude 3.5 reveal capabilities that rival or surpass professionals in medicine, law, writing, and emotional support. What once served as a foundation of individual value, subject matter expertise, cognitive ability, even personal insight, is now being replicated and scaled through generative AI. The implications are moving from theoretical to practical and immediate.

For many, this signals a change in how value is created and how purpose is sustained. The workplace is no longer a space where knowledge alone defines worth. Instead, the premium shifts toward adaptability, agency, and emotional intelligence. These shifts will shape hiring, leadership, and team design in the years ahead.

By the Numbers

• 94% accuracy on complex scientific questions by Claude 3.5 (Anthropic internal benchmarks)

• GPT-4 scores in the 90th percentile on the U.S. bar exam

• 40% of employers expect to reduce workforce size through automation (World Economic Forum)

• 67% of executives plan to maintain or increase AI investment in 2025 (Coastal)

Finding Purpose Post-AI

AI is reshaping value creation across industries. This shift requires more than reskilling. It demands a reexamination of what work is for and how individuals maintain a sense of progress and contribution. Employees who once differentiated themselves through speed, precision, or expertise now compete with systems that outperform them on each of those dimensions. The workplace of the future will place a higher premium on traits machines cannot replicate, such as intuition, moral judgment, and social presence.

Leadership Insight

Executives must prepare their organizations for a cultural transition. The psychological impact of AI on employees will vary widely, depending on how roles evolve and how leaders communicate purpose. The ability to build meaningful hybrid workflows, provide growth pathways, and reinforce human strengths will become a key differentiator. Leaders should invest in environments that promote agency, collaboration, and identity alongside efficiency and scale.

The Bottom Line: AI is reshaping the conditions under which humans find purpose and make decisions. The companies best prepared for this future will recognize that the most important design challenge is not how to optimize the machine, but how to support the human working beside it.

Source
The Free Press: AI Will Change What It Is to Be Human. Are We Ready? [paywall]

Extra Credit

For the overachievers: These are the stories that didn’t crack the top group this week but are too important to ignore—quick hits on what’s happening and why it matters.

GenAI Boosts Output, But Drains Motivation

Key Takeaway: A new behavioral science study finds that while generative AI improves immediate performance, it reduces intrinsic motivation and increases boredom when workers return to non-AI tasks.

Why It Matters: The productivity gains of GenAI come with hidden psychological costs. Without intentional workflow design, overreliance on AI may erode the engagement, creativity, and satisfaction that keep employees motivated over time.

Source
HBR: Research: Gen AI Makes People More Productive—and Less Motivated

From Six Figures to DoorDash: One Engineer’s AI Wake-Up Call

Key Takeaway: After losing his $150,000 software engineering job to AI, Shawn K has applied to 800 positions with little response and now lives in a trailer, delivering food and selling items online to survive. He calls it the early edge of a “social and economic disaster tidal wave.”

Why It Matters: While CEOs accelerate AI investments, individual workers are already experiencing the fallout. K’s story reflects a broader trend of displacement in knowledge jobs, as companies prioritize cost savings over workforce transformation.

Source
Fortune: Software engineer lost his $150K-a-year job to AI—he’s been rejected from 800 jobs and forced to DoorDash and live in a trailer to make ends meet

Which AI Does What Best? A Field Test Across the Big Models.

Key Takeaway: A new review from Vox ranks the major AI platforms ChatGPT, Claude, Gemini, and Grok across writing, image generation, conversation, and practical tasks. ChatGPT leads overall, Claude shines in thought partnership, and Gemini excels in free-tier fiction writing.

Why It Matters: As enterprise AI use scales, tool selection matters. Each model has distinct strengths, and users are beginning to tailor their workflows accordingly. Leaders need to understand the capabilities and limitations behind the brand names shaping their teams’ daily output

Source
Vox: ChatGPT or Grok? Gemini or Claude?: Which AIs do which tasks best, explained.

This edition of The Big Shift: AI @ Work may have been edited with the assistance of ChatGPT, Claude, Copilot, Gemini, Perplexity, or none of the above.

Want to chat about AI, work, and where it’s all headed? Let’s connect. Find me on LinkedIn and drop me a message.