January is the month for making predictions for the new year, but let’s be honest, it’s hard to be a prophet in the tech world, where changes happen quickly and often unpredictably.
That’s why we looked at what major analysis and media companies, such as Gartner, Deloitte, and Forbes, have to say to outline an overview of the directions that will define the future of technology in 2025. Read on for a selection of the most interesting perspectives for this year, reflecting how current developments are shaping the digital world.
1. Agentic Artificial Intelligence, the Next Step in the AI Revolution
Artificial Intelligence promises to dominate the tech landscape again this year. According to Deloitte analysts, we will soon shift from “there’s an app for that” to “there’s an AI agent for that,” and from “knowledge augmentation” to “execution augmentation.”
AI agents represent the new generation of Artificial Intelligence, capable of making decisions and executing autonomous actions (without prompts) to achieve specific objectives, with the potential to revolutionize productivity and adaptability in business. Examples include even AI agents collaborating to solve problems or perform tasks. On the Xanadu platform, one AI agent analyzes customer issues (based on a history of similar incidents) and suggests next steps. Then, another autonomous agent implements the recommendations, while a human oversees the communications between agents, only to approve the solutions.
By 2028, Gartner predicts that 15% of daily business decisions will be made autonomously by AI agents, and 33% of enterprise software will incorporate AI agents to manage 20% of interactions on e-commerce platforms. Unlike conventional GenAI, these systems operate without human intervention, excelling in areas such as managing complex projects, automating customer experiences, and detecting fraud.
To harness this potential, organizations need a robust workflow engine and seamless integration with IT infrastructure and business applications.
2. Major Advances in Robotics: Physical AI
“The world is about to change dramatically. Soon we’ll have billions of physical and virtual robots,” announced Rev Lebaredian, Vice President at Nvidia, during the CES 2025 event in early January. Physical AI extends existing GenAI models, such as GPT and Llama, by adding the ability to understand spatial relationships and the physical behavior of the 3D world.
Trained on data from precise simulations of physical reality, Physical AI models can generate actions in the real world. Nvidia considers Physical AI essential for automating and revolutionizing industries and processes in factories, warehouses, traffic control systems, and even operating rooms.
At CES 2025, Nvidia announced the launch of “World Foundation Models” (WFMs) for training physical GenAI. For example, Cosmo, a system based on WFMs, will enable the generation of photorealistic synthetic data, using physical simulations to accelerate the training process for robots and autonomous vehicles in less time and at lower costs.
3. Small Language Models (SLMs) for Specific Tasks
SLMs can be trained by organizations on smaller datasets and are specialized for solving specific problems, such as analyzing inventory information or summarizing an inspection report, saving time and costs compared to using Large Language Models (LLMs). These SLMs can run on devices and be customized for different needs, with direct applications across various fields.
Companies like Meta and Microsoft are working on developing and refining SLMs with fewer parameters. Progress is particularly evident through open-source models from platforms like Hugging Face or Arcee.AI, which can be tailored to specific requirements. Over 70% of companies opt for smaller, open-source models that they can adapt to their particular needs, according to a Databricks report.
4. Multimodal Models Enable Interaction Through Text, Audio, Photos, and Video
We use multimodal models, for example, when we talk to a digital assistant and receive replies in the form of images or text. AI tools that work with varied data, such as text, images, video, and sound, eliminate the differences between different data sources. Although multimodal GenAI models are still in the early stages of development, they promise to revolutionize interactions by integrating various media types. Examples such as Google’s Project Astra, OpenAI’s GPT-4 Omni, and Amazon Web Services’ Titan are among the first major models of this type. Although their development is slow due to high data, resource, and hardware requirements, business applications are promising.
GenAI multimodal models could be trained with text but deliver responses in the form of sound or even video. They could also be trained using data from sensors and cameras in warehouses, optimizing supply chains and warehouse management. Deloitte analysts predict that in the next 18-24 months, we will see more and more use cases for this technology.
5. AI Becomes the “Brain” Behind Cloud Computing
In 2025, Artificial Intelligence will redefine cloud computing, transforming it into an autonomous and highly efficient ecosystem. AI is no longer just a service hosted in the cloud but becomes the engine that optimizes every aspect of operations, analyzing data in real-time, identifying patterns, and anticipating workload requirements. AI technology brings essential improvements through proactive monitoring, which prevents disruptions by detecting anomalies, dynamic scaling, which automatically adjusts resources based on user demands, and enhanced security, which quickly identifies and neutralizes threats before they become a problem. According to Forbes, companies that adopt these solutions will benefit from significant cost reductions, improved performance, and greater efficiency. As AI evolves, its integration into the cloud will lead to the development of increasingly intelligent and adaptable solutions.
6. AI vs. AI, a Normality in Cybersecurity
AI plays a double role in cybersecurity: on the one hand, it can automate hacking processes, increasing the frequency and complexity of attacks, while on the other hand, it is used to enhance the protection of organizations. In phishing attacks, AI generates highly convincing false messages, but it also quickly analyzes large amounts of data to identify system vulnerabilities, providing more effective protection against both traditional and AI-powered attacks. With superior speed and accuracy, AI quickly detects threats, automates routine tasks such as log analysis and vulnerability scanning, and predicts future attacks by anticipating patterns from previous incidents.
Additionally, AI improves real-time response by proactively intervening to isolate affected systems and block harmful IP addresses. AI technologies are also used to simulate phishing attacks, test employee preparedness, and provide guidance to improve their responses. Furthermore, AI monitors regulatory changes, sending alerts about compliance modifications that may affect operations and automating audits for greater speed and accuracy.
7. AI Governance Platforms for Data Usage Transparency
The expansion of AI usage brings significant challenges, such as poorly defined regulations regarding sensitive data and the use of external data. Deloitte studies show that 55% of organizations avoid certain AI applications due to these issues, opting for solutions that strengthen data security. In this context, adopting AI governance platforms becomes crucial to ensuring the responsible, ethical, and secure use of technology, helping to mitigate privacy risks and monitor the performance of AI models.
According to Gartner, companies that integrate AI governance platforms will experience a significant increase in trust from customers and regulatory compliance, recording 30% and 25% respectively, more than their competitors. Moreover, they will reduce ethical issues by 40%, a priority, especially in highly regulated sectors such as finance and healthcare.
8. Serverless Computing: DevOps Need Solutions
Serverless computing means users run code without having to worry about managing servers. Major providers, AWS Lambda, Google Cloud Functions, and Microsoft Azure Functions, offer developers significant benefits in scalability, cost efficiency, and ease of use. While in 2025, serverless computing is expected to become an essential pillar in web development, supporting the creation of robust and innovative applications, the field still depends on finding solutions to challenges such as cold start latency issues, vendor lock-in risks, and security and compliance implications. Cold start latency can affect the performance of workloads dependent on real-time processing, while lock-in reduces flexibility, increasing an organization’s dependence on a cloud provider’s services and APIs. Other challenges include the lack of cost predictability, especially in high-traffic applications, inadequate debugging tools, and overly complex troubleshooting processes.
We can expect to see new solutions to these challenges in 2025, including better cost prediction tools, hybrid deployment options that combine serverless computing with traditional hosting, improved portability of serverless applications, and advanced pre-warming strategies to avoid cold start issues.
M247 aligns with global trends through a firm commitment to energy efficiency, sustainability, and technological innovation. Prioritizing the implementation of AMD and ARM architecture equipment, a focus on green energy, and the adoption of 400G technology for fiber optic networks, M247 ensures increased performance, fast data transfer, reduced latency, and energy efficiency. Additionally, the company offers servers hosted in Tier 3 data centers, configured for Artificial Intelligence applications, thus supporting complex tasks and innovation in business environments. By expanding its global network and strengthening infrastructure security, M247 enables clients to place their computing resources as close to end-users as possible, meeting performance and scalability requirements in the rapidly transforming digital environment. Thus, M247 continues to be a trusted partner in the digital transformation of businesses.
