Artificial intelligence (AI) is no longer just a futuristic buzzword or the domain of niche experiments. Over the past few years, it has become one of the most powerful forces transforming the global economy, business models and our daily lives. The pace of innovation in this field is unprecedented – what seemed like a distant future just a year or two ago is today becoming standard or opening up entirely new and exciting possibilities. In such a dynamic environment, passively observing changes is a simple way to lose competitiveness. For business leaders, strategists, innovators, in fact, for anyone who wants to consciously shape their professional and business future, actively following and understanding key trends in AI becomes absolutely fundamental. It’s not just a matter of being “up to date” with technological innovations, but more importantly, the ability to anticipate change, identify new opportunities, minimize risks and make strategic decisions that will allow you to not only survive, but thrive in an era of intelligent transformation. This article is your compass around the world of the most important AI trends for 2025/2026 – we’ll take a look at what’s driving the revolution, what technologies will dominate the landscape, and how your company can prepare for it to make artificial intelligence your powerful ally.
Key trends in artificial intelligence for 2025/2026 – what will dominate the technology landscape and how will it affect our strategies?
The artificial intelligence landscape is extremely vibrant and multidimensional. However, certain developments are drawing particularly clearly, promising the greatest impact on business and society in the next several months.
- The relentless expansion and democratization of generative AI (GenAI): What began with spectacular language models and image generators is entering a new phase of maturity and practical applications. Expect to see increasingly sophisticated, specialized GenAI models capable of producing not only text and graphics, but also code, music, video or even 3D designs. A key trend will be the further democratization of access to these tools (see our article on No-Code/Low-Code AI for more on this) and their deeper integration into existing business platforms, from CRM to ERP systems. GenAI will become a daily assistant in an increasing number of professional roles.
- Development and convergence of large language models (LLMs) and multimodal models: LLMs will become increasingly powerful, better able to understand the context and nuances of human communication. But the real breakthrough will be the growing popularity of multimodal models that can process and generate information in different formats simultaneously (text, image, audio, video). Imagine an AI that can watch a video presentation, create a textual summary of it, generate key graphics to illustrate key theses, and answer questions about the content by voice. This opens up entirely new possibilities in education, marketing, content creation or data analysis.
- Growing importance of explainable AI (XAI) and accountable AI (Responsible AI): As AI enters more critical and sensitive areas (medicine, finance, recruitment), there is increasing pressure for transparency, fairness and auditability of its operations. Regulatory requirements (such as the EU’s AI Act) and growing public awareness will make investment in XAI (which we wrote about in detail in the article “Explainable AI (XAI): how to understand and trust…”) and building a comprehensive framework for responsible AI (more in “Ethics and Accountability in AI…”) not only a standard, but a prerequisite for building trust and acceptance of intelligent systems.
- Increasingly broader and deeper application of AI in specific industries – from medicine to industry: We are seeing a shift away from one-size-fits-all AI models to increasingly specialized, “tuned” solutions that address the unique needs and challenges of specific sectors. In medicine (see “AI in the healthcare sector…”), AI will revolutionize diagnostics and personalize treatment. In industry and logistics (read “AI in logistics and supply chain management…”) it will drive automation and optimization. In finance (read “AI for Chief Financial Officers (CFOs)…”) it will improve risk management and forecasting. These are just a few examples – virtually every industry will find its own unique “AI-powered use cases.”
- The dynamic development of Edge AI and the Internet of Things (AIoT) – intelligence closer to the action: Data processing and AI inference will increasingly take place not in a distant cloud, but directly on or in close proximity to end devices (sensors, machines, vehicles) (more in “Edge AI: data processing closer to the source…”). This is crucial for applications requiring minimal latency, high reliability and data privacy, such as autonomous systems, robotics and smart cities.
- Advancing hyper-automation with AI: This is the trend of combining artificial intelligence with other automation technologies, such as Robotic Process Automation (RPA), Business Process Management (BPM) or low-code tools, to comprehensively automate entire, complex end-to-end business processes, rather than just individual tasks. The goal is to create a “smart enterprise.”
- AI as a key player in cyber security – both on the defense and attack side: AI is becoming an indispensable tool for detecting advanced threats, automating incident response and proactively managing risk (more in “AI in cyber security…”). At the same time, we need to be aware that cybercriminals will also become increasingly active in using AI to create more sophisticated attacks, fueling a kind of “arms race.”
- The growing role of AI in supporting sustainability goals (Green AI / AI for Good / AI for ESG): Companies and organizations will increasingly use AI to optimize energy consumption, reduce emissions, protect biodiversity, promote a circular economy or support social goals (more in “AI and sustainable development (ESG)…”). At the same time, awareness of the need to minimize the environmental footprint of AI technology itself will grow.
- Maturity and specialization of No-Code/Low-Code AI platforms: these tools will offer increasingly sophisticated, off-the-shelf AI modules, enabling an even wider range of business users to create their own, simpler AI applications without the need for specialized development teams (recall our article on NC/LC AI).
- Quantum Machine Learning (QML) – the first swallows of a revolution: Although still at a very early stage of development and research, QML raises great hopes for solving computational problems that are beyond the reach of classical computers and AI algorithms. Between 2025 and 2026, we are likely to see the first, more concrete demonstrations of QML’s potential in areas such as the discovery of new materials, drug design or the optimization of extremely complex systems. EITT is keeping a close eye on this direction.
How will these trends affect business – from new operating models to a complete redefinition of familiar markets?
The convergence and acceleration of the aforementioned trends in AI will have a fundamental impact on the way companies operate, compete and create value. Some of these changes are already visible, while others are just taking shape.
Expect the emergence of entirely new business models and revenue streams based directly on AI capabilities – from hyper-personalized services, to “as a Service” products powered by intelligent algorithms, to data sharing platforms and AI models. Companies that can creatively leverage these technologies will gain the opportunity to define new markets or revolutionize existing ones.
There will be a further transformation of customer expectations, who will demand even more personalized, immediate and contextual interactions with brands at every stage of their journey. AI-based customer experience (CX) will become a key competitive field.
Further profound effects on the labor market and the structure of needed competencies will also be inevitable. Automation and augmentation of tasks will redefine many job roles, while creating demand for new specializations (as we wrote about in the article “The Future of AI Jobs…”). The ability to collaborate with AI and continuously learn will become absolutely critical. Organizations will need to invest in building AI-ready cultures and effective AI teams (as we have discussed in dedicated publications).
Value chains and relationships between companies will also change . AI will support the creation of more integrated, transparent and resilient business ecosystems, where collaboration and data sharing (with respect for security and ethics, of course) will become the norm.
How can companies prepare for the coming waves of AI innovation – building an organization that is agile, aware and ready for the future?
Adapting to such dynamic changes requires an organization not only to be technologically ready, but above all to have a strategic vision, flexibility and a culture that fosters innovation.
First, it is crucial to constantly monitor the development of AI technology and analyze its potential impact on your own industry and business model. This is not a task for a single IT department, but the responsibility of the entire management. It is worthwhile to use industry reports, attend conferences and even create internal teams of “trend hunters.”
Second, strategic investment in education and competency development of teams at all levels of the organization is essential . From basic “AI literacy” for all employees, to specialized training for technical and analytical teams, to developing leadership skills for managing the AI transformation.
Third, companies need to cultivate a culture of experimentation and rapid prototyping (Proof of Concept, PoC). Instead of multi-year, costly projects, it makes sense to bet on smaller, agile initiatives that will allow new AI solutions to be tested quickly, learn from mistakes and adapt strategy as experience is gained.
Fourth, it is necessary to build a flexible and scalable AI strategy that is an integral part of the overall business strategy. This strategy should take into account not only technological aspects, but also issues related to data (as we wrote about in the article on Data Strategy for AI), ethics, change management and talent development. It should be reviewed and updated regularly.
EITT’s role in navigating the world of AI trends – your trusted partner in understanding, adapting and harnessing the potential of the future
At EITT, we understand very well that keeping up with the dynamic development of artificial intelligence and turning trends into real business benefits is a huge challenge. Therefore, our mission is not only to provide the highest quality training, but also to be your trusted partner and guide on this fascinating journey. We share knowledge, analyze the most important changes, help you understand their implications, and support you in building competencies that will enable your organization to consciously and effectively leverage the potential of AI. Our Knowledge Base, including an entire series of articles on artificial intelligence, is a prime example.
Summary: The future with AI is an exciting journey into the unknown – the key is curiosity, courage, strategic preparation and a willingness to keep learning
The future driven by artificial intelligence is drawn as a landscape full of extraordinary opportunities, but also inevitable challenges. Key trends for 2025-2026 point to a further acceleration of innovation, an ever-deepening integration of AI into every aspect of business and society, and a growing need for a responsible and ethical approach to this powerful technology. For companies and professionals who can combine curiosity and courage in exploring the new with the wisdom of strategic preparation and a constant readiness to learn, the AI era opens the door to unprecedented growth and value creation. This is not a time for passivity, it is a time for conscious action and co-creation of the future.
EITT and AI trends for 2025/2026 – stay on top of the future of technology with our specialized training and knowledge resources
Want to not only understand trends, but also be able to put them into practice? EITT offers a wide range of training courses to help you and your team gain the competencies you need to navigate the world of artificial intelligence and prepare for the future:
- AI in Business and Society – The Future of Artificial Intelligence (Code: IT-AI-14) ([Link to offer on eitt.co.uk]) – is a fundamental training course that provides a strategic overview of the most important trends in AI, their business, social and ethical implications, helping leaders make informed decisions.
- All of the specialized AI training courses EITT offers (such as those on GenAI, XAI, MLOps, AI in marketing, cybersecurity, data analytics, etc. – [Link to the full catalog of AI training courses at eitt.co.uk]) respond to specific trends and market needs, providing practical skills and “timely” knowledge.
- Our regularly updated Knowledge Base (eitt.co.uk/knowledge-base/) is a valuable source of articles, analysis, and guides to help you keep abreast of developments and deepen your understanding of the dynamic world of AI.
