Tech Trends 2025: AI Agents, Small Language Models, AI Security

‍Current technological trends no longer predict whether AI algorithms will impact life and the economy because they have long become part of reality. Today, they talk about the extent and scope to which people and organisations will experience them. Most trends result from earlier ones, but some will attract more attention due to their innovation or potential to drive progress. The year 2025 becomes critical for changes in management style and integrating AI technologies with company systems.

The role of AI in 2025 trends

In 2025, AI is entering higher levels but also unknown territories. The observed trends indicate a fundamental transformation in how we work or do business. They determine changes in companies' strategy and business model. Forrester emphasises that the leaders' dilemma, “whether to implement AI,” has definitely changed course to “how to do it most effectively,” and over 70% of companies declare that they will adopt AI.

The technological vision of 2025 is also marked by economic and geopolitical uncertainty. Research shows that while leaders are aware of AI-based progress, they constantly need to check their trust in its tools and distinguish between media hype and technologies that are really necessary for their companies' development. Adaptability, data management, system security, and energy efficiency will shape leaders' decisions in 2025 and beyond.

Tech Trends 2025 – what do the studies say?

While 2024 focused on developing generative AI, 2025 will shift towards specialised AI tools and their practical applications. AI will evolve from simple automation to autonomous action, significantly transforming work environments.

Among data and AI leaders in 125 organisations, 98% say they're increasing their investments in data and AI (82% last year), and it is a top priority for 91% of them. 94% believe that the development of AI leads to a greater focus on data.

• Accenture's study showed that leaders are aware of the new future: high initial investments in AI technologies, centralisation, good-quality data, new talents and skills. And 77% believe that unlocking the benefits of AI is only possible on the foundation of trust – in digital systems and AI models, customers and employees, by ensuring accuracy and predictability.
• Gartner identified 10 technology trends with the biggest impact on: companies' strategy, innovation potential, and business models change. There are three areas of these trends: 1. AI-related needs and threats (Agentic AI, AI governance platforms, Disinformation security); 2. New frontiers of computing (Post-quantum cryptography, Ambient Invisible Intelligence, Energy-efficient computing, Hybrid computing); and 3. Human-machine synergy (Spatial computing, Polyfunctional robots, Neurological Enhancement).‍
• The McKinsey Global Institute report identified 18 future arenas (promising industries) that will shape the global economy in 2025–2040.The 12 "arenas of today" identified based on 2005-2020 data gathered among 3,000 largest companies (e.g. biopharmaceuticals, cloud services, e-commerce, and electric vehicles) were joined by new arenas: AI software and services, cybersecurity, air mobility, robotics, and non-medical biotechnology.‍
• Deloitte's Tech Trends 2025 report shows how much AI is entangled in the fabric of life and examines the consequences of its ubiquity and connections with other technologies. It concludes that “ultimately, we will think about AI as we think about HTTP or electricity. We will not use it proactively, but we will experience a world where [AI] makes everything work smarter, faster, and more intuitively.”‍
• The IEEE Computer Society has identified trends that will drive the future of computer science and engineering, evaluating them based on their likelihood of: commercial and research success, impact on the global ecosystem, progress, maturity, and market adoption. These include: new LLM deployment forms, drones as a service (DaaS), AI agents commercialisation, AI-assisted robotics, and medical wearables/biomarkers.

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1. LLM and small language models

The evolution of language models has led to large language models (LLMs) dominating GenAI and integrating it with chatbots and AI agents. However, achieving full benefits and optimal growth from GenAI remains uncertain, as the costs of test implementations do not necessarily translate into value for companies. The widespread use of LLMs such as ChatGPT or Claude has proven low due to their inadequacy for many tasks and the quality of performance achieved at the expense of enormous data resources and computing power. The environmental impact is also significant – GPT-3 training contributed to 500 tons of CO₂ emission.

The game is no longer about the fastest scaling of GenAI capabilities by increasing training data and computing power but rather about finding other solutions to develop AI cheaply and efficiently. As a result, there is a growing interest in smaller models that can be adapted to specific tasks.

The year 2025 will bring special-purpose Small Language Models (SLMs), which can strengthen companies with specialised, autonomous solutions – for financial, manufacturing and retail operations.

The progress of SML will reduce hardware requirements and bring easier tuning to AI agents, and open-source solutions will enable model and data ownership. Optimised for performance and cost, they will become available to smaller companies with limited IT resources. Cloud services can increase their availability with graphical interfaces using low-code. We can also expect significant progress in scientific and research environments thanks to small models.

2. AI agents gain more autonomy

In 2025, the development of technology is shifting towards agent AI. Compared to an AI assistant, an AI agent is a more autonomous and versatile system. AI agents will evolve into advanced business assistants capable of performing specialised tasks and learning and adapting in real-time. What distinguishes the new generation of agents is their proactive action – the ability to make decisions independently and manage many processes simultaneously without human control.

AI agents will be used in professional and complex environments that require fast decision-making, high efficiency, and precision, as well as market data analysis, automated trading, fraud detection, supply chain optimisation, diagnostic support, and medical data management. In customer service, AI agents will conduct natural conversations in many languages, responding to complex problems. According to research, companies already have them, noting a 61% increase in work efficiency.

AI agents are creating a space for applications in the following areas:

• industrial – through integration with IoT devices and robotics, e.g. in smart homes to manage energy consumption, safety and maintenance;
• logistics – to manage warehouse operations, predict demand and automatically replenish stock;
• marketing – to run multi-channel personalised campaigns as a digital avatar (AI Influencer).

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3. Balancing sustainability and technological progress

AI is a powerful tool for investigating complex environmental issues, resource management and sustainable development. To optimise energy consumption and energy efficiency, it analyses data from smart grids in real-time and monitors industrial emissions to reduce waste and pollution and, as a result, carbon footprint.

Energy-efficient computing is the design and operation of computers, data centres, and other digital systems that minimise energy consumption and carbon footprint

The development of AI is also a paradox in the field of sustainable development. The computing power needed to train and run AI models consumes enormous energy, consequently leading to high CO₂ emissions. Therefore, balancing the benefits of AI with its environmental costs by investing in energy-efficient technologies and efficient operations is now becoming the most critical challenge for a sustainable future.

Research shows that in 2025, more companies will declare investing in technologies and processes that reduce energy consumption and their carbon footprint – more precise energy management, waste reduction and the use of renewable energy sources. Closed-loop systems will take over the place of the linear economy. A growing trend for years – clean technologies are gaining ground. Global efforts on its behalf and the energy demand for scalable AI technologies are to support renewable energy systems (including virtual power plants).

It is predicted that in 2025, companies will seek partners who will help them build systems that optimise energy consumption, distribution and storage and reduce the negative impact on the environment while helping to achieve zero emission commitments and sustainable development goals.

At the same time, the World Economic Forum notes that no single technology will solve the energy transformation issue on its own; a set of solutions is needed, including energy storage, advanced nuclear power, clean fuels, hydrogen, and CO₂ removal.

4. Spatial computing and augmented reality (AR)

Spatial computing is a technology that takes the interaction between the real and digital worlds even further and is expected to become one of the key trends in 2025 (Gartner). Using AI to measure physical space, it transforms 2D into interactive 3D space. It offers users experiences that are close to the concept of augmented reality (AR) in new industries on a broader scale.

Immersive technologies are already transformative tools in many fields, and the latest data predicts that their market will explode from $183.96 billion in 2024 to $1.7 trillion by 2032, with a CAGR of 32.1%! In 2025, AR will be integrated with consumer applications – as a visualisation tool in e-commerce, education, healthcare, real estate, and manufacturing – to make purchasing decisions and predict customer needs.

Spatial computing technology will be widely used in various contexts, such as employee training, product visualisation for customer engagement, engineering designs and more advanced simulations, e.g. surgical operations.

5. Development of quantum technology

It is expected that 2025 will be a breakthrough year for quantum technology and quantum computing, among other things, due to the UN's declaration of it as the International Year of Quantum Science and Technology (IYQ) – the effect of the Quantum 2025 initiative.

It is already known that for specific tasks, quantum computers rapidly process information and solve complex problems that are insoluble for traditional computers. In 2025, we will witness further development of quantum computing and the increasingly widespread use of quantum technology, potentially revolutionising many industries. The most promising opportunities lie in banking and finance, but quantum computing will impact almost every sector, especially pharmaceuticals, chemistry, biology, medicine, energy, and logistics. It will streamline research processes, such as simulating molecular structures, which could significantly accelerate drug discovery.

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6. Humanoid robots – changing the dynamics of work

Recently, there has been significant development of next-generation robots based on innovations in mechatronics, going beyond their traditional industrial applications. GenAI has enabled the creation of advanced humanoid and collaborative robots (cobots) that can adapt to situations and constantly learn based on their environment.

According to Capgemini TechnoVision's Top 5 Tech Trends to Watch in 2025 report, 24% of leaders and 43% of venture capitalists indicate AI-based automation and robotics as one of the most important technology trends in the area of data and AI. AI-powered humanoids will become part of the future workforce, with the first cases occurring in 2025.

However, for humanoids to operate effectively, they must be provided with an appropriate level of bandwidth – their performance depends on their ability to process and analyse data in real-time. It is essential to adapt security strategies to protect them from attempts to modify their software and commands and manipulations.

Robot autonomy will leave a mark on the future of work, creating a hybrid environment and influencing traditional roles – understanding leadership, responsibility and cooperation – and forcing us to rethink what role humans should play in a reality where people and machines pursue common goals.

7. Cybersecurity and information protection

It is predicted that in 2025, generative cyberattacks based on AI will be more common and more sophisticated, increasing the risk for every organisation.

At the same time, AI is transforming cybersecurity. It enables increasingly advanced defence, sophisticated risk assessment, and threat detection in real-time, analysing network patterns, identifying anomalies, and predicting attacks. It applies to companies as well as all critical infrastructure, military intelligence, strategic planning, and national security.

Another threat is related to cybersecurity – the ongoing development of disinformation and false propaganda.

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The new AI-based technology, disinformation defence, is becoming necessary for every critical infrastructure, including companies, to protect their brand. It is designed to proactively authenticate content, stopping fake news and disinformation in its infancy by:

• identifying existing vulnerabilities that are potentially exposed to threats;
• monitoring content distributed by mass and social media;
• detecting impersonations of people doing business with a given organisation.

Defending against disinformation requires a holistic approach, and multi-layered defences are essential for business – maintaining trust online and a well-informed public opinion, Gartner believes, making it one of the most important trends of 2025. By 2028, 50% of companies are expected to implement systems to protect against disinformation (in 2024 only 5%).

8. The evolving role of IT – supporting companies in AI implementation

Regardless of which trends will gain momentum in 2025, they represent not only the potential for innovation and growth for companies but also a new approach to technological issues – creating a solid and scalable IT infrastructure, preparing data for promising tools, providing them with the appropriate level of computing power to handle big data.

The performance of AI infrastructure depends on the right equipment, and its key elements are processors (CPU), advanced integrated circuits and graphics (GPU) necessary for calculating and training large data sets, innovations in personal computers and IoT devices.

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For companies to meet current and future requirements, the role of IT will evolve in 2025. IT teams will become an essential cell in company transformations – preparing infrastructure, optimising and automating processes, and especially organising databases. Data management, its selection and analysis, and the creation of security and the protection of sensitive data are essential steps to creating an AI-based company.

Summary

Technology trends in 2025 bring both new opportunities and challenges for businesses. These changes affect how companies work, innovate, and connect with the new technologies. The new technologies can help companies work smarter and faster, but they need to be chosen and used wisely.

To stay competitive, businesses need to make smart decisions about which technologies to invest in. This means picking solutions that truly fit their needs and budget. It's also important to think about security and making sure employees have the right skills to use new tools effectively.

Do you need help making sense of these technology trends? WEBSENSA's experts are here to help. We'll work with you to find the right solutions for your business and show you how to use them successfully. Contact us today to turn these new technologies into real benefits for your company.