- AI has not replaced people, but has become a new basic skill
- Energy independence is becoming a new labor market
- Engineering, embedded and hardware are becoming relevant again
- From trucks to drones: women in the new technical reality
- Soft skills as a new professional foundation
The idea that artificial intelligence will displace all professions remains a topic of discussion, but let's take a look at what is actually happening this year. The labor market is changing under the influence of AI, war, and new societal needs. Some people are leaving the country, some are being mobilized, while businesses and consumers are gradually forming entirely different demands.
Here, for example, is a real story: the UNITED NATIONS DEVELOPMENT PROGRAMME IN UKRAINE conducted training for women on installing solar panels. Here is the story of one of the participants, Maria Burienina, who is now working. We see how women are mastering professions that were previously considered purely male. At the same time, a new market is forming in Ukraine — the market of energy independence and solutions that help maintain comfort even in difficult conditions.
And here is an article that Ihor Pylypiv wrote for "Economic Truth" — about how top managers from IT are transitioning to miltech, another sector that is currently rapidly developing in Ukraine. This sector needs specialists who understand complex systems using AI, as well as people capable of scaling complex business processes.
This is broader than previous forecasts. Artificial intelligence has not replaced all professions, but the ability to work with it has become extremely important. Not everyone has moved to miltech, but this sector is steadily growing and requires new people. Not all women have massively transitioned to traditionally "male" professions, but increasingly, they are installing solar power plants, driving trucks, or assembling drones. Life is always more complex than simplified forecasts. At the same time, trends can be observed in it — and they can be utilized when choosing a direction for development and work.
Almost everything we will consider now lies at the intersection of several fields.
AI has not replaced people, but has become a new basic skill
If you look at what people write every day about their experiences with artificial intelligence, it's easy to notice two polar positions. Some are convinced that AI constantly makes mistakes, hallucinates, and only complicates work. Others believe that it is already capable of working almost at the level of a human or even completely replacing certain specialists.
In reality, both sides are partially right — it's just that they are talking about different types of tasks.
A few years ago, there was much talk about how all professions would eventually turn into "prompt engineers," and the main job of people would be writing queries to AI. But so far, the labor market does not confirm this. A separate mass profession of "a person who simply writes prompts" has not formed.
Instead, something else is happening: working with artificial intelligence is gradually becoming a basic skill — just like working with the internet or spreadsheets once was. It's not about "replacing a person with AI." It's just that the ability to work with AI tools is becoming an important skill for a significant number of professions.
Along with this, the need for digital infrastructure is also growing — from cloud services to VPS and dedicated servers for data storage and work automation.
This is already evident in labor market research. The PwC AI Jobs Barometer notes that industries that actively integrate AI demonstrate higher productivity and faster growth rates. The same study states: people can become even more valuable resources, even in highly automated industries, than they were before. They just need to acquire new skills.
There are already specific quantitative assessments of this effect. For example, a study published in the journal Science analyzed the use of ChatGPT in professional writing tasks among specialists with higher education. Participants performed typical work tasks — letters, short reports, analytical texts — and with AI, they completed them on average about 40% faster, while the quality of the result increased by 18%.
It is important to understand the context of this study. It was specifically about structured text tasks, where AI acted as an auxiliary tool, not as a complete replacement for a person. Moreover, the biggest gains were seen among less experienced participants — the gap between stronger and weaker workers decreased.
Similar results were shown by the NBER study on AI in customer support: employee productivity increased by about 14%, but AI particularly helped newcomers, while more advanced employees did not see such productivity growth — possibly because they were tackling more complex cases.
In complex expert work, everything is still less straightforward. In 2025, researchers from METR conducted an experiment with experienced open-source developers and found that when working with complex tasks, AI tools can even slow down work due to the need to constantly check and correct results.
It seems that AI works best where there is structure, repeatability, and clearly defined tasks:
- routine operations;
- simple support;
- basic analytics;
- typical texts;
- some tasks in programming or design.
But at the same time, it tends to hallucinate — inventing facts, mixing sources, breaking code or layout (this is my own experience with news digests) or confidently giving incorrect answers where there is insufficient information.
Also read: Long live GEO: How to dominate in AI search in 2026
Therefore, the key skill becomes not just "getting an answer from AI," but correctly formulating the task and verifying the result:
- clearly formulate the query;
- provide context;
- limit sources;
- understand the limits of the tool;
- verify the obtained information.
In this sense, AI rather enhances the skills of the specialist than replaces them. It programs best in the hands of a programmer, and it "paints" best when used by a designer. And this difference — between using AI as a button and using it as a tool — is what is now called AI literacy.
In Ukraine, AI literacy is still rarely taught as a separate discipline — but working with artificial intelligence is already gradually being taught.
For example, the Ukrainian platform Prometheus already has several popular courses not only about artificial intelligence itself but specifically about its practical use at work. Among them is From Beginner to AI Expert, which discusses everyday and work scenarios for using AI, as well as Getting Started with ChatGPT, which separately explains in which cases AI is effective and where its answers require verification.
It is noteworthy that these courses are aimed at a wide audience. AI is increasingly seen as a basic work skill for people from various fields — from business and education to marketing or analytics.
Universities are also gradually responding to this trend. For example, at the Lviv National University, they have been conducting the Artificial Intelligence Technology Summer School for several years, and at the European University, they launched the Artificial Intelligence Academy for students in 2025.
A significant number of people are still learning to work with AI independently — through practice, mistakes, and daily use of tools. This is evident even from professional discussions: specialists are gradually developing their own ways of interacting with AI, learning to narrow tasks, limit sources, verify answers, and understand where AI truly saves time and where it creates additional work. Sometimes, examples of successful prompts for various tasks can be found online, which people share during discussions or in blogs. We are observing not only the process of teaching artificial intelligence to work with texts or data but also teaching people how to use artificial intelligence. This is a mutual process.
Also read: How to write prompts for AI correctly: learning to use artificial intelligence
Artificial intelligence does not create new professions but integrates into existing ones in such a way that the employee becomes several times more productive. Artificial intelligence becomes an assistant to marketers, teachers, journalists, data analysts, and designers. However, it must be used correctly; otherwise, productivity will decrease.
Here is what, for example, people I interviewed say.
Olena, methodologist, teacher:
"I receive the lesson from the author and give it to Claude. Usually, I first ask him to check the logic of the presentation, the absence of repetitions, and correct the language. Sometimes I immediately indicate what I don't like; sometimes the text is such that I can't start editing until Claude brings it to its senses. Then I start: here it’s better this way, and there it’s better that way. If I, as a person, do not give clear instructions on how I want to see the final result, then AI will not do what I need by itself. It will create some gray and bland lesson. Although sometimes it provides quite interesting ideas.
But still, it does best what I always struggle with — technical work: numbering slides, ensuring the presence of references to handouts, etc. It adds materials to the list of materials, describes games well, logically, where some of our authors get confused. A person, that is, I, must manage and choose the best option from what AI offers. We are already a good team in this. He is trained. I do not limit him in using any materials, but then I edit if he goes off track. Together we work, if not faster, then definitely better."
Daria, game designer:
"I use AI where I could rely on a not very experienced and attentive secretary. To write a draft text, gather a bunch of disparate documents into one wiki, scan a resource and make summaries of sources so that I decide which ones to read in more detail, make ten variants of 'small talk' phrases for third-plan characters so that I choose the appropriate ones and edit them.
For more serious tasks, AI is often my 'rubber duck,' with which I discuss ideas the night before a meeting with live people. The internal dialogue takes more energy than talking to a robot; moreover, AI's mistakes or banalities trigger healthy aggression: 'that's not how it is, let me show you how it should be,' and do not allow me to relax or gloss over while thinking.
Where it is irreplaceable is in translations and technical proofreading of text, finding equivalents for idioms and phrases in a certain style for languages where I have B2 and below. With English, AI mainly corrects my punctuation (I still tend to place commas according to Ukrainian rules) and cleans up the language in a British or American direction. The problem with working in an international company and studying at international seminars is that your English becomes a 'surzhyk' of all its variations, and to adjust the linguistic barometer, you have to go read literature — and there is not always time for that."
Miltech is looking for not just AI specialists, but people at the intersection of several disciplines
A separate area where AI is already actively used in practice is Ukrainian miltech. This is not about "conversational AI," but about real engineering systems: computer vision for drones, autonomous navigation, signal analysis, geospatial intelligence, and processing data from sensors.
This is evident even from job vacancies. For example, in miltech vacancies on DOU, specialists in computer vision, embedded systems, robotics, RF engineering, and signal processing are regularly sought.
In the vacancy Jr. Perception Engineer, tasks directly mention video processing, multi-sensor systems, and work with autonomous drones. And the company Swarmer describes its specialization as software for autonomous drones capable of working in coordinated teams.
Interestingly, miltech almost does not seek "AI specialists" at all. Instead, there is a high demand for people at the intersection of several disciplines: embedded engineering, robotics, RF, Linux, computer vision, and AI. In some vacancies, skills in working with AI tools like ChatGPT or Copilot are already separately indicated as a desirable part of everyday work.
However, this is not something that can be quickly mastered in a couple of days in courses, but rather a direction for current students of engineering specialties.
By the way, here the Kyiv School of Economics offers a master's program "Unmanned Aerial Vehicles."
Energy independence is becoming a new labor market
The need to have some backup source of energy is becoming increasingly urgent each year, and many are opting for solar power plants instead of generators. It should be noted that in our case, this is still not a tribute to ecology and is not such an environmentally friendly solution.
From experience, I can say that a solar station in conditions of outages requires a powerful battery (when the power is off, it simply does not work without a battery, it does not even feed into the grid) and an inverter. Energy storage devices are not "green" in essence, are difficult to recycle, but we diversify as best we can.
Glancing through the vacancies for "solar panel installers," I see that in some places companies are willing to train a person themselves, as long as they are willing to learn. Salaries, as we see, vary, so there is room for negotiation.
Among the desired skills are the ability to install metal structures, lay cables, install, and use hand and power tools. Candidates who are not afraid of heights and are physically resilient are also sought.
Some of the necessary skills are directly mentioned in job vacancies and training programs. For example, the course Installer of Solar Power Plants for veterans includes:
- working with electrical equipment;
- installation and maintenance of solar systems;
- safety techniques;
- reading technical documentation.
In vacancies from companies like iSolar, they are looking for:
- installer of solar power plants;
- service power engineers;
- design engineers for electrical solutions.
Interestingly, the market is increasingly moving not only towards "solar panels" but also towards battery storage systems (BESS) — large energy storage systems. BESS is now considered one of the key elements of Ukraine's new energy infrastructure.
Therefore, along with classical electrical engineering, the following are beginning to be valued:
- energy monitoring;
- smart infrastructure;
- automation systems;
- working with digital energy management systems.
AI is also gradually being implemented in this sector — for example, in forecasting and energy management systems. In the RISE project by DTEK and Octopus Energy, the AI-powered Kraken platform is used to manage decentralized solar and battery systems.
Thus, one can start with some training course, or one can rely on old skills: companies installing solar electricity are still looking for sales managers, for example.
Engineering, embedded and hardware are becoming relevant again
In miltech, there is a direct discussion about the relevance of engineering close to "hardware," the need for people who understand physics, cables, can write code for hardware, work with sensors, drones, signaling systems, etc.
A few years ago, it might have seemed that the future of technical education was almost exclusively working at a computer. However, the development of miltech, renewable energy, and smart infrastructure has made the demand for practical technical specialties — installation, configuration, maintenance, and working with physical systems — more noticeable again.
We just talked about how in renewable energy, there is an increasing need not only for "classical" energy specialists but also for solar power plant installers, service engineers, and battery systems specialists.
The situation in miltech is similar. Working with drones or autonomous systems involves not only AI and software but also assembling electronics, working with embedded systems, testing sensors, signal processing, and configuring hardware. In the already mentioned vacancy for Jr. Perception Engineer, the requirements directly mention robotics, multi-sensor systems, video processing, and embedded Linux.
It seems that the boundary between "office" and "technical" work is gradually blurring. In many modern technical roles, a specialist works simultaneously with both physical systems and software, telemetry, monitoring tools, and AI-assisted workflows.
But this applies not only to the military industry. For example, logistics, automation of certain processes, "smart" technology, etc.
In fact, the market is again beginning to value people who can combine digital skills with the ability to work with real physical systems.
DOU and Djinni have distinguished miltech and defense tech into separate categories of vacancies in recent years, and companies themselves are increasingly looking for people with a combination of software + electronics + robotics skills. This sharply contrasts with previous years when the Ukrainian IT market was much more focused on web development and outsourcing.
Some may not need to learn anything new: even vacancies in new and updated fields (miltech, automation, etc.) do not consist exclusively of engineering roles; sales managers, translators, copywriters, etc., are still needed.
Also read: Vibe Coding: how to create websites and smart widgets using AI without coding knowledge
From trucks to drones: women in the new technical reality
Many years ago, a few of my female acquaintances decided to train as blacksmiths. And while they successfully completed their training, they could not work in the field and returned to their previous professions: the rejection in the new team was too aggressive.
However, now women are learning to drive trucks, there is a women's taxi, women are mastering public transport, and installing solar panels. One of my acquaintances underwent training in demining to participate in humanitarian demining programs. In fact, there are plenty of opportunities to utilize their skills.
Although this section is dedicated to women, men can also view it: if traditionally male vacancies are being actively filled by women, it means that everyone will be welcome.
Regarding IT, there is an interesting trend: women are being encouraged to join not only where conditional soft skills, "soft IT," are needed, but also in more complex areas.
For example, in 2025, the program Women in Tech 2025 was launched with the support of Huawei Ukraine, Women in Tech Ukraine, and the Ministry of Education. The program includes modules on AI, programming, digital skills, marketing, and launching one's own tech projects.
A separate area is cybersecurity. On the Diia.Education platform, in 2025, a free program Women in Cyber was launched for women who want to transition into the field of cybersecurity. The training covers:
- cyber hygiene;
- OSINT;
- threat intelligence;
- compliance;
- basic skills in cybersecurity.
Professional communities are also working in parallel. For example, Women4Cyber Ukraine develops mentorship programs, networking, and career support for women in cybersecurity, while the project Ukrainian Women in Cyber directly speaks about involving women in cyber defense, cyber intelligence, and leadership roles in national security.
Interestingly, most of these programs emphasize not only "learning technology" but also practical cases.
This also highlights another trend for 2026: AI, cybersecurity, and the digital economy are no longer perceived as a narrow "male technical niche," but as part of a new mass professional education.
From everything we have discussed, I believe an important conclusion emerges: new professions are not appearing in the market, but rather new combinations of skills. At the same time, most programs still remain quite "entry-level": the market already requires specialists with deeper technical skills, but mass education often still focuses on basic AI literacy and the digital economy. Therefore, a significant portion of people continues to learn through practice, self-education, and professional communities.
And this is probably one of the most characteristic features of 2026: new skills are already needed by almost everyone, but there is still no universal learning model for them.
Soft skills as a new professional foundation
In fact, we have already touched on this topic. But we can summarize: relevant skills with which artificial intelligence helps weakly (or only helps if it is shown what specific help is needed) include flexibility, creativity, the ability to learn quickly, critical thinking, and the ability to verify facts.
English, especially technical English, remains the foundation. And this is even despite the fact that AI translators lower the entry threshold for reading and understanding texts or correspondence. It is still much easier to work when you understand the context, can speak verbally, etc. AI, if used correctly, also helps in learning — you can ask it about synonyms, translations of complex words, source searches, and grammar examples. Some of my acquaintances, while learning a foreign language, ask artificial intelligence to create additional exercises for them, and teachers approve of this.
However, English is not the only valuable language in a rapidly changing world. International projects are unpredictable, and it may turn out that German or Polish learned in school will also come in handy, providing an opportunity to recall what seemed unnecessary.
And if we summarize here as well, knowledge of a foreign language requires not only knowledge of rules, especially since compliance with rules can also be adjusted by AI, but also the ability to work with people and information, to catch contexts.
In a world that is constantly unpredictably changing, flexibility is particularly important. However, we must admit that we have all somewhat lost it: fatigue, stress, and constant uncertainty make professional and educational searches less enjoyable and sometimes even overwhelming. If you acknowledge that you simply do not have the energy for an extra hour of English, I am with you.
But in reality, considering what we constantly adapt to every day, and still flow, I can say: our flexibility is already fine. We can export it. Therefore, we just need to continue doing everything we are already doing.
