Agentic AI, Disinformation Security, Polyfunctional Robots Among 2025's Top Technology Trends
Disinformation security is an emerging category of technology that aims to provide systems for ensuring integrity.
The top strategic technology trends in 2025 span artificial intelligence imperatives and risks, new frontiers of computing and human-machine synergy, according to a report by research and consulting firm Gartner Inc.
Below is the list of 10 technology trends for 2025:
1. Agentic AI: Agentic AI systems autonomously plan and take actions to meet user-defined goals, which can offload and augment human work. Gartner predicts that by 2028, at least 15% of day-to-day work decisions will be made autonomously through agentic AI, up from 0% in 2024.
2. AI Governance Platforms: AI governance platforms enable organisations to manage the legal, ethical and operational performance of their AI systems. These solutions can create, manage and enforce policies for responsible AI use and provide transparency. Gartner predicts that by 2028, organisations that implement comprehensive AI governance platforms will experience 40% fewer AI-related ethical incidents compared to those without such systems.
3. Disinformation Security: Disinformation security is an emerging category of technology that aims to provide systems for ensuring integrity, assessing authenticity, preventing impersonation and tracking the spread of harmful information. By 2028, Gartner estimates that 50% of enterprises will begin adopting products, services or features designed to address disinformation security use cases, up from less than 5% today.
4. Postquantum Cryptography: Postquantum cryptography provides data protection that is resistant to quantum computing decryption risks. As quantum computing developments have progressed, it is expected that several types of conventional cryptography will end. Gartner predicts that by 2029, advances in quantum computing will make most conventional asymmetric cryptography unsafe to use.
5. Ambient Invisible Intelligence: Ambient invisible intelligence is enabled by small smart tags and sensors that will deliver large-scale tracking and sensing. In the long term, ambient invisible intelligence will enable a deeper integration of sensing and intelligence into everyday life. Early use cases include retail stock checking or perishable goods logistics.
6. Energy-Efficient Computing: Compute-intensive applications such as AI training, simulation, optimisation and media rendering are likely to be the biggest contributors to organisations' carbon footprint. It is expected that starting in the late 2020s, several new compute technologies, such as optical, neuromorphic and novel accelerators, will emerge for tasks such as AI and optimisation, using less energy.
7. Hybrid Computing: Hybrid computing combines different compute, storage and network mechanisms, including central processing units, graphic processing units, edge, application-specific integrated circuits, neuromorphic and classical quantum, to solve computational problems. The technology will be used to create efficient innovation environments that perform more effectively than conventional environments.
8. Spatial Computing: Spatial computing digitally enhances the physical world with technologies such as augmented reality and virtual reality. The use of spatial computing will increase organisations' effectiveness in the next five to seven years through streamlined workflows and enhanced collaboration. By 2033, Gartner predicts spatial computing will grow to $1.7 trillion, up from $110 billion in 2023.
9. Polyfunctional Robots: Polyfunctional machines have the capability to do more than one task and are replacing task-specific robots that are custom designed to repeatedly perform a single task. Gartner estimates that by 2030, 80% of humans will engage with smart robots on a daily basis, up from less than 10% today.
10. Neurological Enhancement: Neurological enhancement can improve human cognitive abilities through technologies that read and decode brain activity by using unidirectional brain-machine interfaces or bidirectional brain-machine interfaces. This has potential in human upskilling, marketing and performance. By 2030, Gartner predicts 30% of knowledge workers will use technologies such as BBMIs to stay relevant with the rise of AI, up from less than 1% in 2024.
