Recent advertisement from Artificial intelligence company Narwhal Labs An image of a woman who is half human and half electronic machine appeared next to the slogan: “She beats everyone. She will never ask for a raise.”
I’m not here to add to the gender criticism the company has already taken with this ad (although it’s deserved), but to highlight a larger point. This campaign revealed something bigger about how many companies are approaching AI, and it said the quiet part out loud.
Wouldn’t work be easier if you didn’t need people?
This assumption underlies much of today’s corporate AI strategy. Companies see the potential for unprecedented efficiency gains and envision a future with fewer employees, lower labor costs, and less operational friction. However, what is very similar to every efficiency trend that came before it, are the negative impacts on people, and the unintended consequences on businesses that result when efficiency becomes a goal in itself.
Let’s look at history. Remember the open office floor plan? This has been widely hailed by executives and consultants as the best thing since sliced bread. The thinking goes, physical barriers will be removed, creativity will flourish, teams will communicate more naturally, and productivity will reach levels never before seen. Shared spaces took off like wildfire, not because they were a good idea, but because they saved money.
In fact, many companies adopted open offices for a much simpler reason: they were cheaper. The employees hate them. Introverts struggled. Workers will compete for reservations to shelter in conference rooms. Complaints about distractions and stress in the workplace increased. The intimidating shared environment sparked a work-from-home trend, even before the pandemic. Productivity gains are often not achieved.
However, companies clung to this narrative for years before finally acknowledging the basic economic logic: that this setup led to lower real estate costs, whether employees liked it or not.
The outsourcing wave of the late 1990s followed a similar pattern. The promise was tempting: highly skilled labor at a fraction of the cost. Entire departments were moved offshore on the assumption that companies could treat organizational capability like a black box, feeding in requirements, cutting payroll expenses, and getting seamless deliverables on the other side. Once again, companies have underestimated the human dimension.
Most outsourcing initiatives struggled until companies realized a basic truth: that remote workers are still people. They required management, communication, context, accountability and motivation. Outsourcing’s ultimate success depended on investing more in coordination, leadership, and relationship building than many executives originally expected.
The hoped-for cost savings often diminished as companies added layers of local management to bridge time zones, communication gaps and cultural differences with remote teams. The dreamy cost savings never materialized. Outsourcing teams eventually become good extensions of organizations, with the same human needs and work practices as on-premises teams. When we finally figured out how to work together across distance and culture, the benefit became more about workforce growth than cost savings. Because the only way for low-cost outsourcing projects to succeed is to make them more affordable again by taking care of people.
And now, here we are again with AI companies looking to achieve the holy grail of efficiency and trying to remove human dependency entirely. If we say the quiet part out loud, just like in the Narwhal Labs ad, it’s: “Imagine a workforce that doesn’t need annoying, expensive humans.”
Companies are attracted by the promise of a workforce that doesn’t need to eat or sleep, never disagrees with you, and never needs to be cared for or fed, let alone ask for a raise. What could be better?
We’re already seeing the early stages of what’s not working with this AI efficiency revolution. Across industries, organizations are removing humans before AI systems are mature enough to reliably replace them. Teams are directed to “use AI” without clear workflows, operating models, or expectations. So programs break down, and the remaining humans need to bear enormous burdens. One employee recently described it to me this way: “It’s like participating in the Hunger Games. Everyone is judged on how well they use AI, with no idea what to do with it, and we wonder who will be eliminated next. It’s chaos.”
Companies are discovering that their AI service agents Real limitations In solving human customer problems. We have been shown AI CV readers Bias towards AI-written resumes Compared to those written by humans. In many cases, it has become difficult to serve both workers and customers effectively.
Again, the kind of utopian efficiency that AI promises makes companies more excited about the kind of black-box magic that outsourcing once promised, but again underestimates the human and business consequences of an efficiency-based transformation strategy. They confuse employment cuts with strategic transformation.
While AI offers transformative capabilities, few companies – or jobs – are likely to remain competitive without learning how to use it effectively. But if companies want real transformation, they will benefit greatly from saying the quiet part about what to do with humans out loud.
If a company’s AI strategy is to accept lower levels of customer service in exchange for lower costs, executives need to say so clearly. If the strategy is to free employees from repetitive work so they can focus on solving higher-value problems, companies must explain how this shift works and invest meaningfully in employee development. If the strategy is to augment the secret sauce in product development with AI-powered engineering teams, organizations must train employees accordingly and build systems that support this goal.
But if the real strategy is simply: “We want to reduce labor costs by 40% and hope technology catches up later,” then leaders need to be honest about that, too. At the very least, it would force a more realistic conversation about risks.
Many organizations try to simultaneously promise better customer experience, lower costs, fewer employees, faster growth, and happier workers, without acknowledging the trade-offs or explaining the rules of the game to employees.
Every major efficiency revolution has ultimately faced the same truth: organizations still operate based on human motivations. Thriving humans create thriving businesses and motivated customers. Because, by the way, customers are still people.
AI does not remove leadership’s responsibility to understand, respect, and communicate with humans. If anything, it adds to it. The chance to win with AI should sharpen leadership’s focus on ensuring people use it with clear goals, rules, and support — because it’s the humans with superior AI who remain motivated who will become a true competitive advantage.
The companies that win with AI won’t be the ones that eliminate humans the fastest. They will be the ones to decide more clearly where humans matter most, where AI adds real leverage and how the two will work together to deliver on the promise of the business.
