3 AI truths no one wants to hear — But will become reality in 2026

As the topic turns toward AI, everyone usually starts discussing new possibilities and capabilities that AI can provide. But today, I must put on my evil hat and offer some uncomfortable truths: 2026 will not merely be another AI hype year. I suspect that this year will be the one when painful realities hit scale — socially, economically and technologically.

Three things are coming faster than most leaders want to accept:

• Mass layoffs driven by AI will only increase.
• Privacy will (sort of) disappear.
• The era of endless AI pilots will end — and the AI “killing season” is about to begin.

Let’s discuss each.

1. Mass layoffs driven by AI will only increase

If you want to safeguard your job, better improve your skills fast. I bet you have seen numerous well-known, global companies, such as Microsoft, Siemens, Google, Meta and Amazon, laying off thousands of people globally. There is even a real-time firing chart to follow that. The greatest mass cost-cutting event in history has already begun and even though many don’t talk about it openly, it is, in fact, powered by AI.

Not because business leaders are villains thirsty for some bloodshed. But because, mathematically and logically speaking, salary cost is the largest expense in most large-scale organizations, for many, 60% to 80% of operational cost is people. Once automation provides results that it can perform a large portion of work that employees perform more efficiently and economically, the board and CFOs will take action.

Individuals who are not willing or able to improve their workflows using AI will stay behind. Some employees will get redeployed through internal mobility programs or will take up positions moving up the value chain. But many won’t. Which is why it should be a wakeup call for everyone to increase their AI literacy and think of ways — in fact, the more the better — to improve their output and work efficiency using AI tools.

Unfortunately, a lot of people think that mass firing is a long and tedious process that takes a lot of time. Quite the opposite. AI adoption compounds it. The fruits of the AI harvest usually take 24–36 months to mature. That implies that the first major wave of AI productivity programs initiated after ChatGPT’s launch is about to mature right now. Check out this McKinsey report for more details.

We are, in fact, about to reach the harvest phase of AI transformation, when individuals are beginning to become obsolete and the money that was invested more than two years ago is beginning to pay off.

“But won’t companies regret cutting their workforce so ruthlessly and so quickly?” you may ask.

Some might. Some departments will discover that institutional knowledge cannot be replaced at ease. Others will soon find out that training new hires is a slow and much more expensive process than they thought. But if  AI gives organizations a 30% to 50% efficiency lift, the job cuts will still come. Which is why now (if not yesterday) is the best time to improve your skills in AI so you improve your game. The market is ruthless; it will only penalize those who fail to optimize.

But then what should employees do?

There are only three options, really:

1. Upskill fast (pick up additional strategic, creative or technical work skills)
2. Become an AI-empowered individual contributor (that is, someone who uses AI tools better than others)
3. Reskill entirely into a new domain not yet impacted

Sitting around and doing nothing is not a strategy. The loss of jobs due to AI is not hypothetical; it is already happening. The harsh reality is that, unfortunately, the majority of people do not have a financial safety net that would allow them to spend a year rediscovering their passions and talents.

2. Privacy will (sort of) disappear

For years, we said that data is the new oil. That phrase is now outdated – data is not oil; it has become the whole new gold mine. Data became the foundation of every competitive AI model.

The following two years will be the most invasive period in human history due to the AI quest for this gold. Why? Because AI is data-driven. AI runs on volumes of persistent and diverse data — and the volume of this data is so big, that is even difficult to digest. This implies that computer companies are now obsessed with extracting as much customer data as they legally can, frequently going beyond what many would consider legal.

We’ve already seen leaks and allegations that major AI companies trained on user data, including content users believed was deleted. And if that happened publicly once, imagine what happens quietly at scale. When incentives are this high, boundaries become stretched and negotiable.

Unfortunately, data laws are slow. Since AI is such a fresh and new field, it is not surprising that the legal framework is still developing, making it an ideal area for legal interpretations. Companies with billion-dollar pockets are not intimidated by the potential legal battles: even if they eventually lose, they will have already captured the value of the data. And the fine that they might pay is as insignificant as a droplet in an ocean, since they have already profited from the usage of that data. In other words, fines turn into a cost of innovation.

Yet another aspect here — many believe that privacy loss happens only when they feed their own data to the AI willingly and consciously. That is not always correct. In fact, you may have never provided any specific data to the AI, but AI already knows plenty about you. Privacy disappears because others surrender data that reveals information about you. This is the birthday paradox applied to digital identity: with enough overlapping data points, platforms can infer almost everything — even without your consent. As your friends save your number into their contacts, the system can identify you. If your phone can be located in a specific location every night, AI knows where you live. If you meet someone regularly, AI knows your relationship. You never said this, but your actions and/or network did.

Our phones already track large amounts of repetitive data: the phones track our sleep patterns, our heart rate, geolocation, step count, search history and only God knows what else. I wear my smartwatch day and night. Apple might even know when I blink. I personally don’t care and I am okay with giving up my privacy in exchange for daily convenience and progress. But many people value their privacy deeply and feel rather protective of their own data inputs. To them, sharing such input feels like betrayal.

Will it feel uncomfortable for some people? Absolutely. Will it be stopped? No. Because AI needs data and economies need AI.

3. The AI-killing season will begin

I expect that already in the first months of this year, the boardroom mood will shift from “What can AI do?” to “Show me ROI or shut it down.” It is likely that over four-fifths of the corporate AI pilots will die or will be killed within the coming months. This is about to happen simply because too many pilots lacked real business cases and were more of an AI theatre. Now, AI is shifting from experimentation to execution.

This is nothing but realism. Hype, experimentation, value extraction, structural economic impact and regulatory catch-up are all part of the cycle that every significant technology revolution goes through. AI started its mass-market phase only two years ago and we are already approaching stage four, so it is about time we stop labelling AI as being “about the future.” The future has already come. And 2026 will become the AI correction year, when industries, governments and societies absorb the true scale of the shift.

2026 will separate futurists from executioners. And for now, all you can do is be on the right side of that line.

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