Artificial Intelligence in the Workplace: How to Automate Tasks

You know that feeling, at 6:30 p.m. on just another Thursday, when you look up from your phone and realize you’ve spent the last hour answering the same three questions? “What are your hours?”, “Can you send me a quote?”, “Is shipping included?” Your real job—the one you’re paid to do—is still sitting there, waiting.

This isn’t a problem of workload. It’s a problem of prioritization. And that’s exactly where artificial intelligence is coming in: not to do your job, but to free you from everything that isn’t work.

The Blind Spot: AI Doesn’t Affect Professions Equally

There’s a structural fact that’s often overlooked when discussing the future of work. According to McKinsey’s analysis, tasks accounting for up to 30% of hours worked in the United States will be automated by 2030. Note the word: “tasks,” not “jobs.” This means that no profession will disappear overnight because of an algorithm. It’s much more nuanced than that, because it will be individual tasks that are absorbed, hollowing out some professions from within and filling others with new content.

An employment consultant will still exist. But the part of their day spent sifting through documents in search of a circular—that part, yes—will be handled by an automated assistant. The consultant will still be a consultant, just with less paperwork and more time to talk to clients.

Jobs That Are Changing (Even Without You Realizing It)

The message from economists is clear: companies are underestimating the speed of change. Not because a technological apocalypse is coming, but because AI is already finding its way into processes we take for granted. In administration and back-office operations, for example, managing invoices, orders, and standard communications is the first test case. An AI agent on WhatsApp can qualify a lead while you’re in a meeting, without the customer realizing they didn’t speak with you.

Even junior and front-line roles are changing. Those who currently do data entry or basic customer service will see their roles transform—not disappear. Their work will become more like exception handling than mere execution. The same applies to creative and consulting professions, where the ability to produce text, images, and project drafts will become a starting point, not the end goal. Value will shift toward selecting, customizing, and supervising what the machine produces. The real difference won’t be made by the robot. It will be made by the professional who learns to use it before their colleagues do.

How Your Way of Working Is Changing

The point isn’t “what will AI do in my place?” The point is: “Which part of my job is really worth doing myself?” Take an architect, for example. They spend hours producing variations of a design to satisfy the requests of an indecisive client. If a generative model provides them with three alternatives in a matter of seconds, their work isn’t done—it’s just begun. Because now they have time to discuss with the client the details that make all the difference—the very details for which the client is paying them. The same is true for a financial advisor: if an algorithm handles the market data analysis, the advisor can focus on understanding the real concerns of the family sitting across from them. Trust isn’t built by software.

The question to ask yourself today isn’t “Is my industry at risk?” It’s: “What are the three things I do every day that I could stop doing without affecting my revenue?” Those are the tasks that AI will take over first.

Mistakes to Avoid (I See Them Every Day)

The first mistake is thinking that AI is an oracle. You give it a prompt, and it returns the truth. It doesn’t work that way. Generative AI is an amplifier: if you feed it confused processes, it will return chaos multiplied a thousandfold. Another common mistake is ignoring it and hoping it will go away. It won’t go away—not because someone will force you to use it, but because your competitor will use it to respond to customers in minutes while you take much longer to reply. The market punishes slowness, not technology.

The third mistake is jumping on the first tool you come across without a plan. Before choosing what to use, decide what to delegate. What’s the task you hate the most? Start there. Technology adoption is successful only if it solves a real pain point, not if it adds complexity.

Three Practical Steps to Get Started

To proceed methodically, keep track for a week of all the tasks you repeat more than five times a day. You don’t need software—just a sheet of paper and a little honesty. Those tasks are your first automation targets. Then choose just one tool, such as a general-purpose AI assistant to handle email drafts, standard replies, and document summaries. The key is to stick to just one at first, so you can learn to use it well before moving on to something else.

Finally, measure the results in terms of time saved, not technology used. After a month, check how many hours you’ve saved. If the answer is zero, you’ve either chosen the wrong tool or automated the wrong task. Change one of those two variables and try again.

When It’s Not Worth It (For Now)

If your business is based on a hands-on, artisanal approach where every interaction with the client is unique and one-of-a-kind, don’t automate communication. A luthier, a restorer, a criminal defense attorney handling a few complex cases: in these contexts, the client pays to speak with you, not to get a quick response. Artificial intelligence is a fantastic tool for handling high volumes, not for absolute uniqueness.

The same applies to internal management. If you have a team of two people who talk to each other from one desk to another, you don’t need an automated task-assignment system. You need a shared spreadsheet and a cup of coffee. Technology should follow real-world complexity, not create it.

If you want to start delegating simple client conversations (schedules, appointments, basic requests) to an automated assistant without having to connect five different tools, Leader24 lets you set up an AI agent on WhatsApp in just a few minutes, with a 30-day trial to test it out with no obligation.

Frequently Asked Questions

Do I need to know how to code to use AI in my work?

No. Most generative AI tools work with natural language. Just write down what you want to achieve, as you would explain it to a colleague. The challenge isn’t technical—it’s about having a clear understanding of what you want to delegate.

Which professions are most at risk in the coming years?

The professions most at risk are those with a high percentage of repetitive and standardizable tasks: data entry, first-level customer support, basic translations, and document processing. But be careful: rather than disappearance, we’re talking about transformation. Data entry becomes data quality control. Customer service becomes complex case management.

How much does it cost to get started with AI?

The entry cost is often zero or nearly zero. Many generative AI tools offer free versions that are sufficient for testing small workloads. Once the time savings become evident and you want to scale up, you can consider upgrading to paid plans. The initial investment is in time, not money.

What should I do if my employees are afraid of AI?

Don’t hide the change. Explain that the goal isn’t to replace anyone, but to lighten the load of tedious tasks. Involve the team in choosing the first task to automate: they’ll be the ones to tell you what slows them down the most. If they see a tangible benefit in their daily work, their fear will turn into curiosity. If they see it only as something imposed from above, they’ll put up passive resistance, and the project will fail.

Leader24 Insights

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