Emerging Technologies

AI and automation are significantly enhancing the sophistication and efficiency of cyberattacks. AI-powered tools are being used to automate complex attacks at scale, including phishing campaigns that achieve higher success rates than human-crafted attacks. Additionally, AI is accelerating malware development, allowing for the rapid creation of highly evasive malware. This trend poses substantial challenges for defenders, who must adapt quickly to counter these evolving threats.

AI plays a crucial role in tracking cybercriminals on the dark web by providing real-time threat detection and automating the analysis of intelligence. AI-powered systems can monitor vast volumes of dark web data, identify emerging threats, and differentiate between legitimate discussions and harmful intent. This enables organizations to stay ahead of cybercriminals and enhance their cybersecurity defenses.

The LTE IoT 10 Click board is a compact add-on board designed to provide reliable LTE-M and NB-IoT connectivity for industrial and commercial IoT applications. It is based on the Monarch GM02S module from Sequans, which supports global LTE bands and offers low power consumption, robust security, and dual-mode LTE-M/NB-IoT connectivity. The board is suitable for smart metering, industrial sensors, asset tracking, smart home and city applications, wearables, and healthcare monitoring solutions that require power-efficient cellular IoT connectivity.

Security in embedded systems is crucial for smart homes and Industry 4.0 because these systems often control critical infrastructure and sensitive data. Ensuring robust security protects against unauthorized access, data breaches, and cyberattacks that could disrupt operations or compromise privacy. As embedded systems become more connected and integral to automation and smart environments, maintaining their security is essential to safeguard both users and industrial processes.

Invisible interfaces, also known as screenless or zero UI, are user interfaces that minimize or eliminate the need for visible screens by enabling interactions through natural inputs such as voice, gestures, movements, and contextual data. Unlike traditional interfaces that rely on screens and manual navigation, invisible interfaces aim to make technology seamlessly blend into the background, allowing users to focus on their tasks without being distracted by the interface itself. This approach leverages AI, sensors, and contextual awareness to anticipate user needs and automate responses, effectively flipping the human-computer interaction so that technology adapts to humans rather than the other way around.

In the next three to five years, invisible interfaces will fundamentally transform business interactions by enabling more natural, intuitive, and context-aware engagements with technology. Businesses will move beyond screen-based interactions to adopt AI-powered systems that understand user intent through voice, gestures, and environmental context, thereby streamlining workflows and enhancing operational efficiency. This shift will allow companies to deliver personalized, seamless experiences that reduce cognitive load and improve accessibility, ultimately reshaping industries and redefining operational strategies.

Gartner has identified technologies such as generative AI-enabled code architecture, disinformation security, and Earth intelligence as key disruptors. These technologies are expected to become standard in business operations and offer significant opportunities for differentiation and growth.

Prioritizing these emerging technologies allows technology leaders to gain a first-mover advantage, which is crucial for competitive differentiation and growth. Early adoption can help enterprises pull ahead in terms of data and product offerings, as these technologies will eventually become standard across businesses.

LakeDB is a unified data management system that integrates storage, ingestion, metadata management, and query processing. It allows users to define trade-offs for freshness, cost, correctness, and indexes, optimizing these requirements automatically. This approach addresses the fragmentation and complexity seen in current Lakehouse technologies like Apache Iceberg, Delta Lake, and Apache Hudi.

Zero ETL refers to the elimination of the traditional Extract, Transform, Load (ETL) process in data management. Instead, data is loaded directly into a data lake and transformed as needed, reducing latency and increasing flexibility. This approach is part of the evolving data architecture landscape, where technologies like LakeDB and advanced data lakes support real-time analytics without the need for extensive data preprocessing.

AI agents will evolve from simple chatbots to sophisticated systems capable of handling complex tasks, reasoning, planning, and learning from interactions. This evolution will enhance productivity by automating tasks and improving decision-making processes, while also fostering creativity through more efficient workflows and innovative solutions.

In 2025, AI models will become more capable and efficient, with advancements in reasoning and data curation. These models will be able to solve complex problems more effectively and perform specialized tasks with greater precision, thanks to innovations like synthetic data and high-quality data curation.

The key emerging technology trends in 2025 include the widespread integration of AI, especially generative and agentic AI, advancements in quantum computing and the adoption of quantum-resistant cryptography, spatial computing for immersive experiences, cybersecurity enhancements to address new AI-related threats, and the expansion of IoT in enterprise and public sectors. These trends are driving innovation, operational efficiency, and new business opportunities across industries.

In 2025, AI will not only enhance business operations by enabling smarter, faster, and more intuitive processes but will also introduce new cybersecurity challenges such as prompt injection attacks in generative AI systems. Organizations are expected to adopt AI-augmented security measures to defend against sophisticated threats, while also preparing for quantum computing risks by implementing quantum-resistant cryptography. AI will increasingly act as a collaborator in IT functions, helping to automate network management and reduce human errors, thereby improving resilience and operational efficiency.

Edge AI refers to deploying artificial intelligence applications on devices located near the user, allowing data to be processed locally. This setup enhances real-time decision-making, reduces latency, and improves data privacy and security by minimizing the need to transmit data to cloud servers[1][3][4].

Edge AI contributes to cost efficiency by reducing the need for expensive cloud infrastructure and minimizing data transmission costs. It also enhances sustainability by using local, low-power data processing, which reduces energy consumption and greenhouse gas emissions[2][5].

Spatial computing integrates augmented reality (AR), virtual reality (VR), and mixed reality to enhance interactions between the physical and digital worlds. It is expected to revolutionize industries like healthcare, education, and retail by providing immersive experiences and improving productivity. Spatial computing will enable more sophisticated collaboration, data visualization, and storytelling, leading to unique insights and innovative business models.

AI governance platforms are essential for managing the ethical, legal, and operational risks associated with AI. These platforms ensure responsible AI use by providing tools to monitor and control AI systems, addressing privacy concerns, and obtaining consent for data use. They will play a critical role in aligning AI decisions with organizational goals and mitigating potential risks.