{"id":699775,"date":"2025-12-16T10:15:15","date_gmt":"2025-12-16T08:15:15","guid":{"rendered":"https:\/\/eba.com.ua\/?p=699775"},"modified":"2025-12-16T10:17:13","modified_gmt":"2025-12-16T08:17:13","slug":"yakym-bude-rozvytok-shi-u-2026-mu-fahivtsi-softserve-vydilyayut-try-najrealistychnishi-napryamky","status":"publish","type":"post","link":"https:\/\/eba.com.ua\/en\/yakym-bude-rozvytok-shi-u-2026-mu-fahivtsi-softserve-vydilyayut-try-najrealistychnishi-napryamky\/","title":{"rendered":"[:ua]\u042f\u043a\u0438\u043c \u0431\u0443\u0434\u0435 \u0440\u043e\u0437\u0432\u0438\u0442\u043e\u043a \u0428\u0406 \u0443 2026-\u043c\u0443? \u0424\u0430\u0445\u0456\u0432\u0446\u0456 SoftServe \u0432\u0438\u0434\u0456\u043b\u044f\u044e\u0442\u044c \u0442\u0440\u0438 \u043d\u0430\u0439\u0440\u0435\u0430\u043b\u0456\u0441\u0442\u0438\u0447\u043d\u0456\u0448\u0456 \u043d\u0430\u043f\u0440\u044f\u043c\u043a\u0438[:en]What’s next for AI in 2026? SoftServe tech experts name three key directions to watch[:]"},"content":{"rendered":"

<\/p>\n

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Artificial intelligence has become fundamental to business operations and product innovation. According to <\/span>PwC<\/span><\/a>, AI has the potential to contribute up to 15% to the global GDP over the next decade. This can become one of the most significant economic impacts in modern history.<\/span><\/p>\n

In 2026, AI development is set to accelerate as companies integrate it into production, software engineering, and data-driven processes. <\/span>SoftServe\u2019s <\/span><\/a>tech experts highlight tech areas that will influence how businesses automate operations, develop digital products, and manage information.<\/span><\/p>\n

Physical AI: Integrating GenAI and Robotics in the Real World<\/strong><\/h4>\n

Machines are becoming capable of understanding and interacting with the physical world. It gives robots the ability to perceive, predict, and act \u2014 turning them from mechanical tools into intelligent teammates. This marks the rise of Physical AI, representing a significant leap in the evolution of robots and autonomous systems.\u00a0\u00a0<\/span><\/p>\n

In 2026, Physical AI is set to drive major change across multiple industries. From autonomous mobile robots in complex industrial facilities to robotic manipulators and surgical systems that perform highly precise tasks, its applications are expanding rapidly.<\/span><\/p>\n

The shift goes beyond humanoid or collaborative robots. Autonomous systems of all kinds can now be trained and tested in simulations and digital twins \u2014 virtual replicas that mirror real environments of warehouses, stores, or factories. They allow companies to safely test scenarios before they ever touch the real floor. While simulations are used to design and test operations, digital twins are used to monitor and optimize them continuously. Together, they create a <\/span>safe, data-driven loop<\/b>, dramatically accelerating development and deployment cycles.<\/span><\/p>\n

\u201cFor one of our clients, we developed a solution that reduced the simulation time of a production line from several hours to just five minutes per cycle,\u201d <\/span><\/i>explains <\/span>Liubomyr Demkiv, Director of Robotics & Advanced Automation at SoftServe.<\/b> \u201cThis approach improves efficiency, safety, and deployment speed in real-world environments, where autonomous robots need to navigate complex spaces, adapt, and work reliably alongside people.\u201d<\/span><\/i><\/p>\n

According to <\/span>Gartner<\/span><\/a>, by 2028, five of the top 10 AI vendors will offer physical AI products, while 80% of warehouses will use robotics or automation.\u00a0<\/span><\/p>\n

Multi-Agent Systems: A New Logic of Software Development<\/strong><\/h4>\n

The volume of data and the complexity of digital products are growing faster than engineering teams can scale. As a result, organizations are moving toward multi-agent systems \u2014 environments where dozens of specialized agents collaborate and divide tasks much like human teams, rather than relying on a single universal AI.<\/span><\/p>\n

\u201cWhat we are witnessing with multi-agent systems is a shift from AI tools to real AI collaboration,\u201d <\/span><\/i>notes <\/span>Zoriana Doshna, AVP of Technology and Head of the Gen AI Lab at SoftServe.<\/b> \u201cAgents can now take on entire stages of development \u2014 defining requirements, writing code, running tests, performing security audits. This changes the operating model: people focus on complex decision-making, while routine work is handled by specialized agents.\u201d<\/span><\/i><\/p>\n

Demand for such solutions is rising rapidly: SoftServe\u2019s AI practice is growing by 85% year over year, and more than 150 experts \u2014 from Data Scientists to agentic engineering specialists \u2014 are already working on agent-driven projects.<\/span><\/p>\n

Agents developed at SoftServe analyze technical documentation, propose architectural solutions, generate modules, create unit tests, and prepare final technical documentation. Depending on the scenario, this can reduce software development cycle time by 30\u201370%.<\/span><\/p>\n

\u201cOur goal is to bring software development to a new level with multi-agent systems, turning it from an experimental concept into a practical reality,\u201d <\/span><\/i>says <\/span>Volodymyr Karpiv, R&D Director at SoftServe.<\/b> \u201cThis is why we created a solution, which enables not only the execution of individual agents but also orchestrating their collaboration, tracking solution quality, and automatically integrating outputs into DevOps processes. It is a foundation for AI-driven engineering in the years to come.\u201d<\/span><\/i><\/p>\n

Multimodal AI: A New Era of Data Comprehension<\/strong><\/h4>\n

Generative models have become a standard business tool in just two years for tasks like text generation, data summarization, and communication support. However, the majority of real-world business processes rely on a wider range of data types, including photos, videos, blueprints, document scans, tables, and presentations.<\/span><\/p>\n

This is why the next stage of development is Multimodal AI, capable of processing various data formats and unifying them into one context. For instance, SoftServe has implemented this approach with Multimodal RAG, a solution developed in partnership with NVIDIA. This technology simultaneously analyzes text, images, tables, or diagrams to formulate a comprehensive response based on all data sources. As a result, it boosts accuracy by over 70% and cuts information search time by roughly 40%. For teams managing vast document archives, this translates to a significant reduction in manual labor and substantially faster decision-making.<\/span><\/p>\n

In the coming years, Multimodal AI is expected to become the core for process automation across finance, manufacturing, medicine, and logistics. It enables businesses to handle data the way human specialists do: by seeing the whole picture, evaluating context, and making decisions based on all available information.<\/span><\/p>\n

* * *<\/p>\n

About SoftServe<\/b><\/p>\n

SoftServe<\/span><\/a> is the largest global IT company with Ukrainian roots, specializing in software development and consulting services. More than 11,000 employees work in more than 60 offices located from San Francisco to Dubai. The company’s headquarter is located in Austin (USA).\u202f\u00a0<\/span><\/p>\n

The company is working on more than 900 active projects for clients in North America, the EU, and Asia. SoftServe’s clients include IBM, Cisco, Panasonic, Cloudera, Henry Schein, Spillman Technologies, and others. SoftServe is a partner of Google Cloud Platform, Amazon Web Services, Microsoft Azure, NVIDIA, and other major technology companies.<\/span><\/p>\n

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Artificial intelligence has become fundamental to business operations and product innovation. According to PwC, AI has the potential to contribute up to 15% to the global GDP over the next decade. This can become one of the most significant economic impacts in modern history. In 2026, AI development is set to accelerate as companies integrate […]<\/p>\n","protected":false},"author":4489,"featured_media":699777,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false},"categories":[24,23],"tags":[],"yoast_head":"\nWhat's next for AI in 2026? 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