Artificial intelligence is changing the way we work at a speed few people expected. Tasks that used to take weeks now get done in hours, and what once required a full team can now be handled by a single person with the right tools. The individual productivity curve has skyrocketed in a way that would have been hard to believe just five years ago, and anyone in the workforce knows this from experience, not just in theory.
But something curious is happening in the middle of all this: while technical productivity is soaring, the meeting calendar just keeps growing. 🤔
Dan Sirk is what they call a fractional executive, a professional who serves as head of marketing for not just one, but two companies at the same time. With the help of tools like Claude, Gemini, and ChatGPT, he can compress months of work into weeks. Building a custom website, for example, used to take three to six months with a team of contractors. Now he does it alone in about a month. Developing a communications strategy used to eat up an entire week. Last time, he knocked it out in under eight hours. He even plans to take on a third company soon.
But when asked if he planned to go beyond that in the future, the answer was straightforward: no way.
The reason is not a lack of technical ability or tools. It is the meetings. Dan estimates he already sits through about ten meetings a week between the two companies. There are standing meetings with executives at each company, one-on-ones with each CEO, check-ins with direct reports, meetings with the sales team, and sessions about specific projects like an investor presentation. Adding a third company, he figures the meeting volume will jump by around 50%. If he went any further, he would spend practically the entire week on calls and in conference rooms, with zero time left for anything else.
That detail opens a question that goes way beyond Dan’s routine: if AI already does so much, why does the human side of work only keep growing?
The answer might sit right at the intersection between automated task execution and something no language model has been able to replicate so far: the ability to build real human relationships, to persuade, to reassure, and to simply be present.
What AI still cannot do for you
There is a huge difference between executing and relating. Artificial intelligence, no matter how sophisticated, operates within an input-output framework. You provide a prompt, it delivers a result. You tweak the command, it refines the response. That cycle can be incredibly powerful for content production, data analysis, strategy creation, and even managing entire projects. But when it comes to sitting across from a nervous client, reading the room during a tense negotiation, or calibrating the tone of a difficult conversation with a team member going through a rough patch, the language model simply does not step onto the field.
This is not a temporary limitation that will get fixed in the next version of GPT or Gemini. It is a structural issue. Human relationships require presence, and presence is something that does not fit inside a token. The trust built over months of working together, the handshake that seals a deal, the strategic silence in a sales meeting, the genuine empathy that shows up when someone is overwhelmed — all of it belongs to a dimension that AI observes from the outside without ever truly participating.
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And that is exactly why the time people dedicate to these interactions does not shrink as automation advances. In fact, it tends to grow, because when operational tasks disappear from the table, what remains are precisely the situations that demand human judgment.
David Deming, economist and dean of Harvard College, reinforces this point. According to him, skills like telling a story from data, turning large volumes of text into something people actually want to consume — these have always been important. But as the information landscape gets more saturated, they become even more valuable. A study Deming published in 2017 already showed that as computers grew more powerful, a growing share of jobs required intense social interaction, while roles that demanded heavy math skills but little social ability, like certain engineering positions, were shrinking.
Automation, in practice, was pushing people toward jobs where interpersonal relationships mattered most. And the professionals who thrived were not simply the most charismatic ones, but those who combined social skills with solid technical knowledge.
Technical productivity is the new baseline
When Dan Sirk says he can handle two jobs simultaneously with the help of AI, he is describing something that will become increasingly common. The compression of operational time is real and it is happening right now, across every field. A marketing professional can produce in a single day what a small team used to produce in a week. A lawyer can review contracts in a fraction of the time it used to take. A developer can write and test code at a speed that would have been unthinkable without automated assistance. This shift is not marginal — it is structural, and anyone who has not noticed yet will feel the impact in the coming years in a very concrete way.
But here is the point a lot of people still have not connected: if task execution has become a commodity, what sets one professional apart from another is no longer speed of delivery — it is the quality of their decisions, their relationships, and the judgment they bring to the table. Anyone with access to the same AI tools can deliver the same volume. What will separate those who grow from those who stagnate is exactly what cannot be delegated to a model: the ability to understand what the client actually wants beyond what they said, to build alliances inside an organization, to position yourself with authority in a room full of decision-makers, and to manage expectations without losing anyone’s trust.
Dan’s case illustrates this very directly. The limit was not his productive capacity, nor the tools he uses. The limit was the time available to be present, to participate in conversations, to maintain the relationships that keep both jobs actually running. The meetings are not a sign of a poorly managed calendar. They are a reflection of something essential: people still need people. And that goes for the client who wants to feel heard just as much as for the teammate who needs alignment before making an important decision. AI speeds up the work, but it does not replace the web of trust that makes an organization function. 🤝
From the interview room to the consulting floor: the new professional profile
In interviews conducted by The New York Times, professionals across various fields reported that artificial intelligence has drastically accelerated this shift in how skills are valued. A data scientist at a software company shared that he and his colleagues used to write code for every new feature or improvement they wanted to test. Now, all you need is the idea — AI writes the code and runs the analysis.
The ripple effect even showed up in the company’s hiring process. Before, interviews were dominated by programming questions and favored candidates with a pure technical profile, even if they were not great communicators. Today, the focus has shifted to evaluating whether the candidate can identify good ideas and, more importantly, whether they seem capable of convincing colleagues to support them.
Mark Ozaki, a director at KPMG, confirmed this trend in the consulting world. According to him, the firm traditionally encouraged younger consultants to specialize in a technical area, like tax law, or an operational skill, like programming. But AI is devaluing that kind of isolated specialization and rewarding generalists who take initiative and stand out when it comes to cultivating client relationships.
Ozaki leads a team developing an AI-powered sustainability platform called Sustainlit.com. He said that in the past, his team depended heavily on skilled programmers. Now, most of the coding is done by artificial intelligence, and what he really needs are connected people — the ones who keep their phone glued to their ear, who are friends with everyone, and who have the energy to never stop.
At Accenture, another consulting giant, the pattern repeats. Consultants frequently use AI to create presentation slides, but the ones who truly stand out are those who have absorbed client preferences over many hours of meetings. They know exactly how the person they are trying to persuade likes to consume information. Are they driven by metrics? Do they prefer case studies or personal stories? That kind of contextual reading is still exclusively human.
When vulnerability becomes an advantage
An interesting case comes from a customer success professional at Salesforce. She uses chatbots daily to guide clients on how to use the company’s sales software and connect them with technical specialists when needed. But, worried about the possibility that she was effectively training her own digital replacement, she started investing heavily in something no bot can replicate: genuine closeness.
She makes a point of getting to know her clients beyond text messages and emails. She visits them in person, attends conferences, and dedicates time to having real conversations. Recently, she listened to a client who opened up about the fear of being laid off. That kind of moment, where someone lets their guard down and shows vulnerability, is something no artificial intelligence will ever reproduce with authenticity.
Salesforce, for its part, said that AI has freed up its employees to focus on priorities like deepening client relationships and that it has reassigned hundreds of workers to faster-growing areas within the company.
Fewer programmers, more relationship people
The story of PolicyFly, a company that sells software to insurance carriers, is perhaps the most concrete example of how this transition is playing out in practice. In 2024, it took four or five employees and an average of six months to configure the software for a new client. Each type of insurance policy has countless variables, and the way each carrier handles them is different, which required heavy customization for every case.
With AI handling the customization, a single PolicyFly employee now gets a new client up and running in about two weeks. Cory Crosland, the company’s CEO, expects that timeline to drop to under a week by the end of this year. The cost reduction has allowed them to charge significantly less for initial onboarding, which is apparently driving up demand for the company’s services.
Over the last six months, PolicyFly grew from 20 to 28 employees. But here is the revealing detail: only two of the new hires are software engineers. The rest are younger professionals focused on initial setup and customer success, helping clients get the most out of the software.
Even so, Crosland said he does not believe he will be able to automate the process much further than where it stands today, at least not anytime soon. The reason? Clients want to talk to real people. They want PolicyFly to reassure them, confirm that the software will work across different scenarios, that billing is configured correctly, that proration policies make sense. And of course, there are meetings to discuss all of this. Lots of meetings.
With larger companies, the challenge multiplies. There are multiple stakeholders from different departments weighing in, and reaching a consensus takes time, patience, and a healthy dose of interpersonal skill. No algorithm solves that with a prompt. 😅
Social skills as a real competitive advantage
For a long time, social skills were treated as a nice complement to a technical resume. Something that helps, but is not essential. The professional who could code really well or who had mastered financial analysis had a clear path forward, regardless of whether they were a brilliant communicator or not. That landscape has shifted significantly, and the rise of artificial intelligence in the workplace has accelerated that change in a way nobody expected.
Now that the technical side can be amplified by tools accessible to anyone, the human differentiator has returned to center stage with full force. Building solid human relationships inside and outside an organization is a skill that develops over time, with attention and intention. There is no automated shortcut for it. You learn to negotiate by negotiating, learn to lead by leading, learn to communicate clearly and persuasively by practicing in real situations with real consequences. No language model is going to do that work for you.
And more importantly: no company, in any industry, is going to stop needing professionals who can move naturally between technical execution and human connection. On the contrary, that profile is becoming increasingly rare and, because of that, increasingly valuable in the market.
The professional who uses AI as a lever, not a crutch
What is emerging now is a new professional profile: someone who uses AI as an extension of their operational capabilities, freeing up time and energy to invest in the very dimensions that technology does not cover. This professional does not compete with artificial intelligence. They use it as a lever and channel the productivity gains toward where it truly matters: building trust, leading people, and navigating the human — and often unpredictable — side of organizations.
The pattern that emerges from The New York Times reports is consistent across different industries. From consulting to software development, from enterprise sales to the insurance market, the message is the same: AI is automating technical work and raising the value of relational work. Professionals who were once valued exclusively for their coding or analytical skills now need to show they can present, debate, lobby, persuade, reassure, and yes, sell. Not necessarily sell products, but sell ideas, sell confidence, sell the assurance that there is a human on the other side who understands and cares.
That meeting that feels like a waste of time might paradoxically be the most important thing you do all week. Because that is where trust is built, where decisions actually get made, and where relationships solidify in a way no chatbot can replicate. Those who understand this sooner will come out ahead — not because they will work more hours, but because they will work the right hours, in the right conversations, with the right people. 🚀
