Agentic AI will make decisions for users within 2-3 years.,AI governance platforms are being developed to combat model bias and ensure transparency.,Post-quantum cryptography will become a concern in just two to three years.
In the rapidly evolving world of technology, staying ahead of the curve is crucial. Gartner has identified the top 10 strategic technology trends that will shape the future of IT in Asia by 2025. From Agentic AI to neurological enhancement technologies, these advancements are set to disrupt and transform industries. Let's dive into the future and explore what's in store.
Agentic AI: The Next Big Thing
Agentic AI is poised to revolutionise decision-making. Within the next two to three years, this advanced AI will go beyond summarising information to actually taking actions on behalf of individuals. Imagine an AI that not only suggests the best route for your commute but also books your ride and adjusts your schedule accordingly. This shift will make our lives more efficient and streamlined.
AI Governance: Building Trust and Transparency
As AI becomes more integrated into our daily lives, concerns about model bias and ethics are growing. AI governance platforms and tools are being developed to address these issues. These platforms will ensure that AI-generated answers are explainable and prevent harmful outputs. For example, an AI governance platform could help a bank ensure that its loan approval algorithms are fair and unbiased.
Fighting Disinformation with AI
Generative AI has the potential to create synthetic media, such as deepfakes, that can impersonate people or organisations. Disinformation security tools will be essential in identifying and combating these threats. These tools will assess the truth and track the spread of disinformation, helping organisations maintain their integrity and trustworthiness.
Post-Quantum Cryptography: The Future of Security
Post-quantum cryptography standards have recently been released, and this technology will become a concern in just two to three years. IT leaders will need to replace every piece of encryption with a post-quantum algorithm that is unbreakable by classical or quantum computing. This shift is crucial for maintaining data security in an increasingly digital world. For more information on the standards, refer to the NIST Post-Quantum Cryptography Standardization program.
Ambient Wireless Tags and Sensors: Unlocking Hidden Data
The falling cost of wireless tags and sensors will enable organisations to access and respond to data from parts of their operations that were previously "in the shadows." These devices can track and monitor inventory, supply chain conditions, or physical assets, providing valuable insights and improving operational efficiency.
Energy-Efficient Computing: Sustainability Meets Technology
As energy consumption becomes a growing concern, organisations are exploring ways to make computing more energy-efficient. This could involve moving energy-intensive algorithms to green cloud providers, rewriting algorithms to consume less energy, or using technologies like optical, neuromorphic, and DNA storage. These innovations could create vast efficiency improvements and reduce the environmental impact of computing.
Hybrid Computing: The Best of All Worlds
In the future, organisations are expected to take a hybrid computing approach, integrating and orchestrating multiple different computing paradigms and technologies. This could include CPUs, GPUs, edge computing, quantum computing, optical computing, and storing information in DNA. By combining these technologies, organisations can optimise their computing capabilities and achieve better performance.
Spatial Computing: Blending the Physical and Digital
Spatial computing brings the physical and digital realms together into a single, unified 3D space through devices such as augmented reality headsets. This technology could support just-in-time contextualisation for decision-making in places like the manufacturing shop floor. For example, a worker could use an AR headset to see step-by-step instructions for a complex task, improving efficiency and accuracy.
Polyfunctional Robots: The Future of Automation
Polyfunctional robots that can perform multiple functions, rather than being limited to a single task, are expected to become part of everyday life within the next three to ten years. By 2030, 80% of humans could be engaging with smart polyfunctional robots on a daily basis. These robots could assist with tasks ranging from household chores to complex industrial processes. SoftBank's recent acquisition in robotics highlights this growing trend.
Neurological Enhancement Technologies: Unlocking the Brain's Potential
Developing technologies that can read and enhance brain functions could be used in settings including healthcare facilities to restore senses such as sight or hearing. These devices will range from simple wearables like earbuds or headbands to complex integrated brain-computer interfaces. While this technology is still at least a decade away, it has the potential to revolutionise healthcare and improve the quality of life for many people.
Staying Ahead of the Curve
IT leaders need to decide which technologies to act on now, which to monitor, and which to ignore. However, ignoring these trends could be detrimental. As Gene Alvarez, Gartner’s distinguished vice president analyst, warns, "if you turn your back on a wave, it could knock you down."
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Latest Comments (3)
i agree with this point on agentic AI, about it taking actions instead of just summarising. i've been playing around with some of the open source LLM agents, like autogen, and it's clear how quickly they're moving past just giving me answers to actually doing things in my dev environment. my coding workflow has changed so much already with these.
Right, agentic AI making decisions for us in two to three years. That timeframe felt a bit optimistic even back when this was written, didn't it? We're still seeing plenty of hurdles in getting models to reliably summarise information without hallucinating, let alone autonomously booking rides and rescheduling diaries. The complexity of real-world decision-making, with all its nuances and exceptions, is proving rather a tricky problem to crack at scale, especially where user trust and accountability are paramount. We've certainly made progress, but fully autonomous AI agents are still a fair bit further down the road, I reckon.
While the article mentions Agentic AI making decisions in 2-3 years, achieving truly robust, multi-modal decision-making agents still faces significant challenges in generalization and real-world ethical alignment, as seen in recent benchmarks.
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