According to Fixygen, major Bitcoin miners are accelerating the repurposing of some of their energy facilities and infrastructure into data centers for artificial intelligence and high-performance computing amid a deteriorating Bitcoin mining economy, Cointelegraph reports.
In this new model, the miners’ key asset is not ASIC equipment—which is unsuitable for AI computing—but rather access to electricity, substations, cooling systems, permits, and ready-to-use sites. It is precisely the shortage of grid-connected power that has become one of the main constraints on the development of AI data centers. The total capacity of AI data centers worldwide reached 29.6 GW by the end of 2025, whereas in 2022 it was less than 1 GW.
Publicly traded mining companies have already concluded a number of major deals in the AI and HPC segments. In particular, in November 2025, IREN signed a five-year agreement with Microsoft for GPU cloud services worth approximately $9.7 billion for a 750-MW campus in Texas. Hut 8 signed a 15-year, $7 billion contract with Fluidstack for the River Bend facility in Louisiana, while Core Scientific expanded its agreement with CoreWeave to $10.2 billion over 12 years.
According to CoinShares, public mining companies have already announced contracts in the fields of AI and high-performance computing totaling more than $70 billion. Companies with such agreements are valued significantly higher by the market: their price-to-earnings ratio for the last 12 months stands at 12.3, compared to 5.9 for miners that remain primarily focused on Bitcoin mining.
Analysts estimate that the share of AI revenue among public mining companies could rise to approximately 70% by the end of 2026, compared to about 30% in the first quarter. This trend is effectively transforming some mining companies into infrastructure operators for the AI market.
Pressure on traditional mining has intensified due to declining margins. According to JPMorgan’s estimates, the average cost of mining a single Bitcoin is about $78,000, and approximately 20% of miners are operating at a loss. Based on current prices, Bitcoin is trading at around $62,500, which is below the estimated average cost of production.
At the same time, the transition to AI is not cheap. According to CoinShares, a typical crypto mining infrastructure costs $700,000 to $1 million per 1 MW, while liquid-cooled AI facilities may require $8–15 million per 1 MW. This increases companies’ debt burden and makes them dependent on large clients—hyperscalers.
For the market, this signals a shift in investment logic within the mining sector. Whereas Bitcoin price, hash rate, and electricity costs were previously the main factors, long-term contracts with AI clients, access to capital, and the ability to quickly repurpose facilities for GPU infrastructure are now becoming increasingly important for some companies.
Publicly traded Bitcoin miners are under pressure following the halving due to the reduction in block rewards, high network difficulty, and Bitcoin price volatility. Expansion into AI and HPC allows them to diversify their revenue, but at the same time shifts their business into the capital-intensive data center segment, where debt, facility commissioning timelines, and customer concentration remain key risks.
AI, BITCOIN, DATA CENTER, HPC, MINING
The current investment boom around artificial intelligence may slow sharply if the expected return from the technology turns out to be lower than forecasts, the Bank for International Settlements (BIS) warns in its new annual economic report.
According to Experts Club, optimism around AI has become one of the factors that supported the global economy and financial markets in recent months. Investments in semiconductors, data centers and energy infrastructure have grown, while large technology companies have become one of the main drivers of capital expenditures.
However, it is precisely the scale and speed of this process that create new risks. BIS compares the current AI boom with previous technological investment cycles — the construction of canals in the 1830s, the railway boom in Great Britain in the 1840s, electrification in the late 1920s and the dot-com boom of the late 1990s.
The common feature of these periods was that a real technological breakthrough attracted more capital than commercial returns could justify. As a result, such booms ended with a reversal of investment and a downturn that affected not only individual companies but also the economy as a whole.
According to BIS, the five largest hyperscalers — major providers of cloud and computing capacity — may spend more than $1 trillion on AI-related capital investments in 2025-2026. These commitments are already outpacing companies’ profits and free cash flow, which is why part of the financing is being raised through debt markets.
BIS General Manager Pablo Hernández de Cos, quoted by The Wall Street Journal, said that competition for future market share may have led to excessive investment in AI. If the technology does not deliver the expected return, the sector may prove vulnerable, and the current investment boom may abruptly come to an end.
BIS is particularly concerned not only about the volume of investments itself, but also about how they are financed. This concerns the debt of hyperscalers, AI laboratories, equipment suppliers, construction and engineering contractors involved in creating data centers, energy capacity and other infrastructure.
If the largest customers slow down or stop capital expenditures, companies in the supply chain may face a sharp drop in revenue and difficulties servicing debt. This may increase pressure on fixed-income markets, corporate bonds and private credit.
BIS emphasizes that this is not about denying the long-term potential of artificial intelligence. On the contrary, AI may increase productivity in the economy, but the transition to this model is accompanied by uncertainty: it is still unclear how quickly companies will be able to introduce the technology into real production processes and monetize it on a scale sufficient to justify current investments.
Another risk is related to infrastructure constraints. The development of AI is already facing shortages of electricity, network equipment, powerful semiconductors and opportunities for rapid construction of data centers. These constraints may increase the cost of projects and at the same time intensify overinvestment if companies seek to secure capacity in advance through long-term contracts.
For the financial system, the key threat is that possible disappointment in the return from AI may coincide with already existing vulnerabilities — high valuations of technology company stocks, rising debt, activity in the non-bank financial sector and increased market sensitivity to changes in interest rate expectations.
In this scenario, the AI boom may turn from a source of growth into a factor of financial instability. First, there may be a decline in capital investment and a fall in orders in the infrastructure chain, then a deterioration in the position of borrowers, a widening of credit spreads and a revaluation of AI-related assets.
For businesses and investors, the main conclusion of BIS is that technological progress does not cancel financial discipline. Even if artificial intelligence really becomes one of the key technologies of the coming decade, this does not guarantee that all current investments will pay off, or that all companies participating in the race will remain resilient.
BIS, or the Bank for International Settlements, is an international financial organization headquartered in Basel, Switzerland. The bank was established in 1930 and is considered one of the oldest international financial institutions. Its main task today is to promote global monetary and financial stability through cooperation among central banks, research, statistics, analytical reports and support for international financial standards. BIS is often called the “bank for central banks” because it works primarily with central banks and international financial organizations.
Under a memorandum between the Ministry of Community and Territorial Development of Ukraine and the Kyiv National University of Construction and Architecture, and with the support of the flagship project “Movement Without Barriers,” a team of researchers has developed a pilot AI accessibility consultant in ChatGPT.
The tool helps users quickly obtain basic answers with references to DBN standards, which, in particular, regulate issues of inclusivity and accessibility, as well as advice for specific spaces or situations.
The AI consultant does not replace architects and accessibility experts, but it can serve as a convenient first step to get oriented, verify solutions, or prepare for working with specialists.
“For me, the topic of accessibility isn’t an abstract policy, but a personal story. My dad is a veteran with a disability who uses a wheelchair, and every day I see the barriers he faces. That is why the launch of the AI accessibility consultant is an important step toward making spaces in Ukraine truly accessible, not just ‘on paper.’” — Artem Goncharenko, Accessibility Ambassador at the Ministry of Education and Science
This approach is intended to make the process of creating an accessible environment more systematic, consistent, and understandable for communities, businesses, and everyone who works with public spaces.
The AI consultant is constantly updated with materials and technical data. The project is coordinated by the KNUBA Veterans Institute and the KNUBA Expert Working Group on Accessibility. If you have any questions while using the tool, please contact us at: veterano@knuba.edu.ua.
The materials generated by the AI Consultant are for informational purposes only. It is recommended to verify the information in accordance with current regulations and consult with specialists if necessary.
The use of artificial intelligence has already become an everyday practice for most students and employees; however, in the labor market over the coming years, the key competitive advantage will remain not technical but human skills — communication, leadership, emotional intelligence, critical thinking, and the ability to work with people. This was the conclusion reached by participants in the press conference on the topic “Higher education and MBA education in the era of artificial intelligence. Which professions and skills will remain with humans?”, which took place at the Interfax-Ukraine agency on Wednesday.
As Director of the Center for Business Education and Advanced Training of the Institute of Psychology and Entrepreneurship Maria Furman reported, the study, conducted on the basis of cooperation between students and business, covered more than 250 respondents from the fields of law, HR, IT, consulting, marketing, management, foreign economic activity, education, sales, and finance.
“Currently, more than 97% of respondents already use artificial intelligence in work or everyday life, and more than 50% turn to it at least once a day. The most widespread tools turned out to be ChatGPT, Google Gemini, Claude, and Copilot, while the main usage scenarios were explaining complex information, writing and editing texts, generating ideas, translation, data analysis, and preparation of summaries,” she noted during the presentation of the study “The Use of AI in Work and Everyday Life.”
At the same time, according to Furman, the spread of AI does not mean an automatic increase in trust in its answers. She drew attention to the fact that about 30% of daily functions are already being replaced by such tools; however, the largest share of respondents assessed the level of trust in AI answers as moderate — information can be trusted only on condition of verification. More than 50% of respondents always verify generated answers, another 33% do so if the information looks suspicious, and 13% do so when it concerns especially important work. In addition, more than 30% of respondents very often encountered distortion of information, while another 53.6% reported that such cases had happened to them several times.
“According to estimates by the World Economic Forum, by 2030 more than 40% of skills in the world will change, and this means a need for rapid retraining of both current employees and students. She emphasized that higher education must not simply familiarize young people with digital tools, but rebuild approaches to learning in such a way as to prepare specialists capable of working together with AI, rather than mechanically relying on it,” the expert stressed.
According to her, artificial intelligence has already become part of education and business, but its effect lies not in the complete replacement of humans, but in the transformation of their functions.
“That is precisely why analytical thinking, communication, adaptability, people management, emotional intelligence, and creativity are of particular value today,” Furman stressed.
She added that AI will not be able to displace managers, psychologists, HR specialists, communications managers, teachers, mentors, as well as those responsible for strategy and team development, since in these professions human trust, leadership, empathy, and the ability to work with context remain decisive.
For her part, Doctor of Economics, Professor, Vice-Rector for Scientific-Pedagogical and Educational Work of the Institute of Psychology and Entrepreneurship Iraida Zaitseva emphasized that even the most powerful algorithms cannot replace a leader, since they are devoid of consciousness, creativity, and moral reflection. She recalled that a machine can advise cutting staff for the sake of higher profit, but is not capable of assessing the social, ethical, and even geopolitical consequences of such a decision.
“Artificial intelligence is a powerful engine, but only a human should be the pilot who knows where and why they are flying. We teach students not simply to use the tool, but to validate decisions, critically treat the algorithm’s ‘black box,’ and bear personal responsibility for the result. At the institute, AI is allowed to be used as an auxiliary means for structuring material or searching for ideas; however, the student is obliged to indicate the fact of its use, verify sources, and be responsible for the content of the work, otherwise this may be regarded as academic dishonesty,” Zaitseva noted.
CEO of Capolavoro Group (Brazil), lecturer at the Brazilian AMF institute, and investor in technology startups Wesley Lacerda focused attention on the risks of the improper use of artificial intelligence in business. In his assessment, the main danger lies not only in the technology as such, but in the gradual cognitive weakening of a person, when the user becomes accustomed to transferring their own memory, analytical abilities, speech, and even elementary ability to make independent decisions to the machine. In his presentation, he separately named cognitive deterioration, decline of intelligence, weakening of the ability for reflection, and loss of social skills as the main risks of the broad implementation of AI.
“Artificial intelligence should be used as a tool for data analytics, not as a replacement for human thinking. When a person ceases to understand what stands behind the machine’s answer, they lose their own cognitive abilities, and together with them, the ability to make independent decisions,” Lacerda noted during his presentation.
He also drew attention to the fact that the new wave of automation is generating demand first of all for AI analysts, AI engineers, specialists in AI Ops, and algorithmic audit, and not only and not so much simply for IT specialists. However, even in these roles, what remains decisive is the human understanding of what is being done and for what purpose, and not only the ability to write the correct prompt for the machine.
For her part, 3S Agency recruiter Sofia Vorushko emphasized that in the hiring sphere, artificial intelligence creates an illusion of objectivity, but still cannot replace a live recruiter. According to her, candidates are increasingly better prepared for interviews with the help of AI, use correct wording and socially desirable answers; however, the algorithm is not capable of fully reading non-verbal signals, understanding a person’s motivation, their real experience, and their fit with the culture of a specific company. She gave the example of two seemingly identical executive assistant vacancies, for which in practice completely different candidates were needed due to the different management styles of the managers.
“Today the market is evaluating an employee less and less only by hard skills and more and more by soft skills. Communication, resilience, flexibility, adaptability, leadership, and the ability to build relationships are becoming critically important, because they are the hardest to automate,” Vorushko added.
She referred to global estimates according to which 63% of employers call the shortage of soft skills a barrier to business development, 67% of companies are looking for flexibility and adaptability, 61% — leadership and social influence, while demand for social and emotional skills will grow by another 24% by 2030. According to the recruiter, currently 75% of an employee’s long-term success depends specifically on soft skills, while hard skills account for only about 20%.
At the same time, Director of LLC “Formatsiya” Mykola Hoi noted that for a business built on communication with clients, partners, dealers, manufacturers, and suppliers, the direct transfer of decisions to AI is extremely limited. According to him, in his company, which operates in the field of solar energy, about 95% of working time is precisely work with people, and therefore template algorithms are not capable of fully replacing live contact either in sales, in team selection, or in the development of marketing solutions.
“In business, artificial intelligence can be used, but only if its limits are understood very clearly. Founding a business, selecting a team, marketing, sales, work with the client, and rapid decision-making in a changing environment remain the zone of human responsibility, because here what is needed is not templates, but knowledge, experience, and understanding of another person,” Hoi stressed.
He added that the use of AI in HR processes can lead to mistakes if a company tries to assess candidates only by formal features, without giving a person the opportunity to reveal their potential in live communication.
Separately, the participants noted that the Institute of Psychology and Entrepreneurship is focusing on specialties that, in the opinion of the organizers, are least susceptible to automation: personnel management, communicative management, and psychology. The institution reported that the cost of bachelor’s studies is UAH 42 thousand per year, and at the college — UAH 28 thousand per year; cooperation was also announced with partners in the Baltic countries, as well as in Poland, the UAE, and Brazil, where students can undergo internships. Thanks to the ontological approach, which helps develop the personality, and the combination of psychology with up-to-date knowledge from business practitioners, the institute’s students comprehensively develop personal and professional skills. This helps them become high-level managers and not be dependent on technologies. This level of training allows students, starting from the second year, to work in business projects in their professional specialty.
Summing up the discussion, the experts agreed that Ukrainian higher education and MBA programs can no longer ignore artificial intelligence, but also should not make it an end in itself. It is not about a struggle between human and machine, but about a new distribution of roles, in which AI takes over routine, analytical, and technical functions, while strategy, ethics, creativity, empathy, team management, and responsibility for decisions remain with humans. It is precisely these qualities, in the opinion of the event participants, that will determine a specialist’s competitiveness in the next 5–10 years.
AI, EDUCATION, Formatsiya, HR, INSTITUTE OF PSYCHOLOGY AND ENTREPRENEURSHIP, IRAIDA ZÁITSEVA; CAPOLAVORO GROUP, LEARNING, MARIA FURMAN, MYKOLA HOI, RECRUITING, SOFÍA VORUSHKO, WESLEY LACERDA; 3S AGENCY
Schneider Electric, a global leader in energy technologies, showcased new developments in its strategic partnership with Microsoft at Hannover Messe, demonstrating how their combined technologies help manufacturers modernize operations, accelerate engineering processes, and enhance sustainability.
Schneider Electric provides the industrial foundation for this collaboration through EcoStruxure Automation Expert—its open, software-defined automation platform that operates seamlessly in on-premises, edge, and hybrid environments. Microsoft extends this foundation with Azure cloud services and artificial intelligence solutions that analyze and optimize industrial processes. The result is a unified approach to agent-driven manufacturing, open automation, and end-to-end sustainability.
Today, manufacturers face increasing product variability, supply chain volatility, and heightened pressure to modernize safely. Schneider Electric addresses these challenges by combining engineering design with real-time operations. Their joint platform enables teams to standardize reusable logic, validate automation through simulation, ensure traceability throughout the entire lifecycle, and scale interoperable operations across different sites and equipment.
Schneider Electric is collaborating with Microsoft to develop the next generation of agent-based, software-defined manufacturing—an integrated workflow spanning design, engineering, construction, commissioning, and operations. At its core is EcoStruxure Automation Expert, which allows manufacturers to create, model, test, and deploy automation logic once and run it anywhere without additional reconfiguration. Schneider Electric’s deep expertise in safety, compliance, and industrial integration ensures reliability in highly regulated environments.
“From agent-based design to software-defined operations, Microsoft and Schneider Electric demonstrate a unified, interoperable workflow that enables the consistent verification, simulation, and deployment of automation logic both in the cloud and at the edge,” said Gwenel Yue, Executive Vice President of Industrial Automation at Schneider Electric.
While traditional automation software requires separate tools and handoffs between stages—design, simulation, commissioning, and operations—the shared platform unifies them into a single, transparent workflow. Specialized AI agents, coordinated by a centralized control system, automate routine engineering tasks and verify logic before implementation, reducing time from design to launch and increasing efficiency on the first attempt. Schneider Electric’s industrial copilot for manufacturers, powered by Azure AI, is already delivering results in the field: engineering teams report a 50% reduction in time spent configuring control systems and preparing documentation, and changes to production lines that previously took weeks are now completed in hours.
In one project to implement autonomous green hydrogen production in real-world conditions in collaboration with H2E Power, an Indian pioneer in the green hydrogen sector, the platform delivered over 6,000 hours of stable autonomous operation in one of the most demanding industrial environments — high-temperature solid oxide electrolysis for green hydrogen production — reducing the levelized cost of hydrogen by 10%, equivalent to approximately €500,000 per year for a typical 10 MW plant.
“Thanks to agent-based design, we close the loop from engineering concept to operational reality by automating solutions, ensuring early validation, and delivering reusable automation packages that Schneider Electric can model and consistently deploy both in the cloud and at the edge,” said Dayan Rodriguez, Corporate Vice President of Manufacturing and Mobility at Microsoft.
At their booths at Hannover Messe 2026, Schneider Electric and Microsoft presented hands-on demonstrations of early-stage joint innovation capabilities, including live demos, engineering AI, and an ecosystem of open standards, as part of a large-scale program to develop the next generation of manufacturing.
About Schneider Electric
Schneider Electric is a global leader in energy technologies, driving efficiency and sustainability through the electrification, automation, and digitalization of industry, business, and residential spaces. The company’s technologies enable buildings, data centers, factories, infrastructure, and power grids to function as open, interconnected ecosystems, enhancing productivity, resilience, and sustainability.
The company’s portfolio includes smart devices, software-defined architectures, AI-based systems, digital services, and professional consulting services. With 160,000 employees and 1 million partners in over 100 countries, Schneider Electric consistently ranks among the world’s most sustainable companies.
Learn more at https://www.se.com/ua/uk/
Indian Prime Minister Narendra Modi called on the international community to shape a “human-centric” future for artificial intelligence and presented the MANAV framework for global AI governance at the AI Impact Summit 2026 in New Delhi.
According to Modi, AI has the potential to accelerate change to a scale that was previously measured in decades, so it is crucial to adopt an approach where technology serves people, not the other way around, and where the well-being of society is at the center.
Within the framework proposed by India, MANAV (meaning “human”), the prime minister outlined five pillars: moral and ethical principles, accountable governance, respect for national sovereignty over data, accessibility and inclusiveness, and the legality and verifiability of AI systems.
Modi separately emphasized the need to counter deepfakes and disinformation, proposing the introduction of common standards for labeling digital content, including watermarks and source verification, and stressed the importance of protecting children when interacting with AI.
As examples of the practical application of AI in India, he cited the digital assistant for farmers, Sarlaben, which, according to him, provides advice on livestock health and dairy farm productivity, as well as initiatives for multilingual consultations for farmers, including Bharat-VISTAAR.
The Prime Minister also said that as part of the India AI Mission, India is rolling out computing infrastructure and a national repository of data and models to make access to capabilities cheaper for startups and accelerate the development of the AI ecosystem.
