Postquantum Cryptography
Postquantum cryptography provides data protection that is resistant to quantum computing decryption risks. As quantum computing developments have progressed over the last several years, it is expected there will be an end to several types of conventional cryptography that is widely used. It is not easy to switch cryptography methods so organizations must have a longer lead time to ready themselves for robust protection of anything sensitive or confidential.
Gartner predicts that by 2029, advances in quantum computing will make most conventional asymmetric cryptography unsafe to use.
Ambient Invisible Intelligence
Ambient invisible intelligence is enabled by ultra-low cost, small smart tags and sensors which will deliver large-scale affordable tracking and sensing. In the long term, ambient invisible intelligence will enable a deeper integration of sensing and intelligence into everyday life.
Through 2027, early examples of ambient invisible intelligence will focus on solving immediate problems, such as retail stock checking or perishable goods logistics, by enabling low-cost, real-time tracking and sensing of items to improve visibility and efficiency.
Energy-Efficient Computing
IT impacts sustainability in many ways and in 2024 the leading consideration for most IT organizations is their carbon footprint. Compute-intensive applications such as AI training, simulation, optimization and media rendering, are likely to be the biggest contributors to organizations’ carbon footprint as they consume the most energy.
It is expected that starting in the late 2020s, several new compute technologies, such as optical, neuromorphic and novel accelerators, will emerge for special purpose tasks, such as AI and optimization, which will use significantly less energy.
Hybrid Computing
New computing paradigms keep popping up including central processing units, graphic processing units, edge, application-specific integrated circuits, neuromorphic, and classical quantum, optical computing paradigms. Hybrid computing combines different compute, storage and network mechanisms to solve computational problems.This form of computing helps organizations explore and solve problems which helps technologies, such as AI, perform beyond current technological limits. Hybrid computing will be used to create highly efficient transformative innovation environments that perform more effectively than conventional environments.
Spatial Computing
Spatial computing digitally enhances the physical world with technologies such as augmented reality and virtual reality. This is the next level of interaction between physical and virtual experiences.The use of spatial computing will increase organizations’ 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.
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. The functionality of these new robots improve efficiency and provide a faster ROI. Polyfunctional robots are designed to operate in a world with humans which will make for fast deployment and easy scalability.
Gartner predicts that by 2030, 80% of humans will engage with smart robots on a daily basis, up from less than 10% today.
Neurological Enhancement
Neurological enhancement improves human cognitive abilities using technologies that read and decode brain activity. This technology reads a person’s brain by using unidirectional brain-machine interfaces or bidirectional brain-machine interfaces (BBMIs). This has huge potential in three main areas: human upskilling, next-generation marketing and performance. Neurological enhancement will enhance cognitive abilities, enable brands to know what consumers are thinking and feeling, and enhance human neural capabilities to optimize outcomes.
By 2030, Gartner predicts 30% of knowledge workers will be enhanced by, and dependent on, technologies such as BBMIs (both employer-and-self-funded) to stay relevant with the rise of AI in the workplace, up from less than 1% in 2024.
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