Technology trends 2026: from agentic AI to 6G connectivity

A 2026 of real adoption

The year 2025 made it clear that generative artificial intelligence and hybrid infrastructures are no longer futuristic concepts. Companies built proofs of concept and began experimenting with autonomous agents, cloud platforms, robotics, and advanced analytics. However, many initiatives remained in the lab due to a lack of clear business cases or adequate governance. In 2026, things change: technical leaders (CTOs, CIOs, software architects, and data specialists) face a maturity phase in which the technology will have to prove its value in practice.

Agentic AI: From experimentation to digital companions

Artificial intelligence agents have evolved from simple assistants to digital colleagues capable of performing complex tasks on their own. It is predicted that by 2028, 15% of daily tasks in the workplace will be performed by autonomous agents, and that data teams will increase their productivity thanks to them. For technical departments, this means rethinking processes, designing APIs to delegate data discovery and cleaning tasks, and assuming that models must be securely integrated into the workflow. For the first time, agents are being incorporated into the core of the organization and are no longer an isolated experiment.

Data governance and AI ethics

The adoption of agentic AI necessitates taking data governance seriously. By 2026, many large companies will have appointed dedicated governance officers to ensure the quality, traceability, and ethical use of information. The mission is not only to comply with regulations but also to establish access policies, version control, and audits that enable models to make decisions with confidence. Robust governance reduces legal and reputational risks and accelerates AI scalability by providing clean and labeled datasets.

Collaborative robotics and microfactories

Automation is moving away from the rigid systems of Industry 4.0 to embrace collaborative robotics. Cobots work integrated with human operators, understand instructions in natural language, and correct their errors without human intervention. These capabilities open the door to microfactories: smaller-scale production plants located close to customers and capable of manufacturing short runs and fully customized products. For engineers, this means incorporating machine vision systems, reinforcement learning, and distributed control in heterogeneous manufacturing environments.

Smart payments and blockchain maturity

In the financial sector, AI and biometrics are redefining payment flows. In B2B processes, AI agents automate negotiations and authentications, while for the end consumer, innovation focuses on security: advanced biometrics and QR code payments aim to eliminate intermediaries and reduce fraud. At the same time, the Blockchain is moving beyond the speculative phase to focus on practical applications such as digital asset management and blockchain-to-blockchain transfers with stablecoins as an alternative to traditional financial infrastructure. For software architects, this means designing wallets, smart contracts, and interoperability protocols.

Multicloud infrastructure and AIOps

Workloads are migrating to multicloud environments: public, private, on-premises, and edge clouds are being combined to optimize costs and maximize flexibility. Dynamic orchestration demands AIOps, generative AI, IoT, edge computing, and infrastructure as code. These concepts are being integrated to automatically scale resources, detect anomalies, and ensure resilience. The ability to move workloads seamlessly between environments will be a key competency for operations teams.

Zero Trust Security and the fight against disinformation

The rise of offensive AI and the risks of disinformation are forcing the adoption of a Zero Trust strategy. Security officers will need to stop trusting any identity or device by default and implement continuous authentication and authorization for every transaction. Furthermore, it is predicted that half of all companies will be using specific products to combat disinformation by 2028. The development of post-quantum security algorithms is progressing to anticipate the ability of quantum computers to break current encryption methods. Protecting the data and model supply chain will be just as important as hardening the infrastructure.

6G connectivity and autonomous networks

The transition to 6G connectivity will bring networks that integrate artificial intelligence to autonomously manage resources and optimize energy consumption. These systems will enable near-zero latency, support for mission-critical applications, and more efficient spectrum management. For technical teams, designing services that leverage these networks means adapting architectures to a distributed edge model, with network function orchestration (NFV) and real-time optimization algorithms.

Generative AI in software development

Generative AI assistants are revolutionizing how we write, test, and deploy code. Autocomplete tools, unit test generation, and intelligent refactoring reduce development time and democratize access to programming. However, their tendency to generate unsafe or potentially insecure code means they don’t replace human expertise. Good version control practices, peer review, and automated testing are needed to integrate these assistants into DevOps workflows. On the other hand, AI learns the context behind repositories, understands why certain changes were made, and suggests architectural improvements, opening up new possibilities for predictive maintenance.

Interpretability and sustainability of AI

The complexity of large language models makes it essential to advance mechanistic interpretability, a discipline that attempts to open the “black box” of neural networks. Understanding why a model generates a particular response allows us to detect biases, errors, and vulnerabilities. Meanwhile, generative AI is driving the construction of hyperscale data centers that consume as much energy as a city. To ensure sustainability, companies are exploring modular nuclear power plants, liquid cooling, and energy management systems that prioritize efficiency. Optimizing resource use is vital to prevent AI from competing with humanity for water or electricity.

AI as a digital partner: collaboration and safeguards

Ultimately, AI is emerging as a digital partner rather than just a tool. Microsoft describes 2026 as the year AI amplifies what people can achieve together, transforming collaboration across all disciplines. Small teams will be able to launch global projects in days thanks to agents capable of analyzing data, generating content, and personalizing experiences, while humans focus on strategy and creativity. This collaboration brings with it the need for safeguards: each agent must have a defined identity, clear limits on information access, and protection mechanisms against cyberattacks. Only then can we trust agents that are no longer mere algorithms, but active members of a team.

Conclusion

For the technical departments of organizations, 2026 will be the year of true adoption. Agentic AI, collaborative robotics, multicloud, Zero Trust cybersecurity, and 6G connectivity will cease to be aspirations and will become an integral part of the technology stack. The challenge will be to integrate these trends securely, ethically, and sustainably, balancing innovation with rigorous data and energy management. At Imaginae, we are already working on AI, cloud, IoT, and digitalization to support our clients in this transition. Which trend will have the greatest impact on your organization?

References

InfoNegocios. (January 14, 2026). These are the technological trends that will mark 2026: from agentic AI and blockchain to 6G connectivity. InfoNegocios Madrid. Retrieved January 20, 2026, from https://infonegocios.madrid/enfoque/estas-son-las-tendencias-tecnologicas-que-marcaran-2026-de-la-ia-agentica-y-el-blockchain-a-la-conectividad-6g

CaixaBank. (January 14, 2026). These will be the 10 emerging technology trends of 2026, according to MIT. CaixaBank Sphere. Retrieved January 20, 2026, from https://www.caixabank.com/es/esfera/content/tendencias-tecnologicas-mit

Cvetko, J. (2025, December 10). What’s next in AI: 7 trends to watch in 2026. Microsoft Source. Retrieved January 20, 2026, from https://news.microsoft.com/source/emea/features/whats-next-in-ai-7-trends-2026/