recent ads AI company Narwhal Labs The article featured an image of a woman who is half human, half cybernetic machine, with the tagline, “She works harder than anyone else. And she never asks for a raise.”
I’m here not to add to the gender-oriented accusations the company has already received with this ad (which is understandable), but to make a larger point. This campaign reveals something larger about how many companies are approaching AI. I said the quiet parts out loud.
Don’t you think business would be easier if you didn’t need people?
This premise underlies most of today’s enterprise AI strategies. Businesses are realizing the potential for unprecedented efficiency gains and are imagining a future with fewer employees, reduced labor costs, and reduced operational friction. But much like every efficiency trend before it, when efficiency becomes a goal in and of itself, there are negative consequences for people and unintended consequences for business.
Let’s look at history. Remember the open office floor plan? It was widely praised by executives and consultants as the best thing since sliced bread. When you remove physical barriers, your thinking will move forward, your creativity will flourish, your team will communicate more naturally, and your productivity will reach unprecedented levels. Shared spaces have exploded like wildfire, not because it’s a good idea, but because it saves money.
In reality, many companies adopted open offices for a simpler reason. Because it was cheap. Employees hated them. Introverts had a hard time. Workers were vying for reservations to hide in conference rooms. Complaints about distractions and workplace tensions have increased. Scary shared environments sparked the work-from-home trend even before the pandemic. Productivity gains were often not realized.
Yet companies clung to that narrative for years, until they finally acknowledged the underlying economic logic that the system reduced real estate costs, whether employees liked it or not.
The outsourcing wave of the late 1990s followed a similar pattern. The promise was seductive. It meant providing a highly skilled workforce at a fraction of the cost. Entire departments were moved offshore on the premise that companies could treat their organizational capabilities like a black box, inputting requirements, reducing labor costs, and receiving seamless deliverables on the other side. Once again, companies underestimated the human side.
Most outsourcing efforts struggled until companies realized the fundamental reality that remote workers are still people. It required management, communication, context, accountability, and motivation. Successful outsourcing ultimately depended on investing more in coordination, leadership, and relationship building than many executives had originally anticipated.
Promised cost savings were often narrowed as companies added layers of local management to bridge time zone, communication gaps, and cultural differences with remote teams. The dream of cost savings never materialized. Outsourced teams eventually functioned well as extensions of the organization, with the same human needs and work practices as local teams. Ultimately, when we found ways to collaborate across distance and culture, the benefits were more about employee growth than cost savings. Because the only way to make a low-cost outsourced project work was to make it expensive again by taking care of people.
This is where AI comes into play again. Companies are turning to the holy grail of efficiency and eliminating dependence on humans altogether. If you say the quiet part out loud, as in the Narwhal Labs ad, you’ll say, “Imagine a workforce that doesn’t require annoying and expensive humans.”
Companies are seduced by the promise of a workforce that never eats or sleeps, never disagrees, and never needs care or food, let alone asking for a raise. What could be better?
We are already experiencing the early stages of this AI efficiency revolution going awry. Organizations are eliminating humans in every industry before AI systems are mature enough to reliably replace them. Teams are being told to “use AI” without clear workflows, operating models, or expectations. As a result, the program is halted and the remaining humans have to carry a heavy burden. One employee recently described the situation to me this way: “It’s like being in the Hunger Games. Everyone is being judged on how well they use AI. They have no idea what to do with it and wonder who will be eliminated next. It’s just chaos.”
Enterprises are discovering that AI service agents: true limit in solving human customer problems. AI resume readers have been shown to: Biases against AI-generated resumes Compared to what humans wrote. In many cases, it has become difficult to serve both employees and customers effectively.
Once again, this kind of efficiency utopianism promised by AI has companies even more excited about the black-box magic that outsourcing once promised, but again it underestimates the human and business impact of an efficiency-only transformation strategy. They confuse workforce reduction with strategic change.
AI offers innovative capabilities, but few companies or careers can remain competitive without learning how to use it effectively. But if companies want real change, they can greatly benefit from saying out loud the quiet parts of what to do with people.
If a company’s AI strategy is to accept lower customer service levels in exchange for lower costs, management should say so clearly. If the strategy is to free employees from repetitive tasks so they can focus on higher-value problem-solving, companies need to explain how the transition will work and invest meaningfully in employee development. If your strategy is to power the secret sauce of product development through AI-enabled engineering teams, your organization must train its employees accordingly and build systems that support that goal.
But if the real strategy is simply “We want to reduce labor costs by 40% and hope technology will catch up later,” leaders should be honest about that, too. At the very least, it will require more realistic conversations about risk.
Many organizations try to simultaneously promise a better customer experience, lower costs, fewer employees, faster growth, and happier employees without recognizing the trade-offs or explaining the rules of the game to their employees.
All major efficiency revolutions ultimately face the same truth. That is, organizations are still run by human motivations. Thriving people create thriving businesses and engaged customers. After all, customers are humans too.
AI does not remove the responsibility of leaders to understand, respect, and communicate with humans. If anything, it will increase. If there is a chance to win with AI, leaders will focus even more on enabling people to use it with clear goals, rules, and support. Because the real competitive advantage is humans, powered by AI and still motivated.
The companies that win with AI will not be the ones that get rid of humans the quickest. They will be the ones who most clearly decide where humans matter most, where AI adds real impact, and how the two work together to deliver on the promise of the business.
