Gartner: top 10 2020 strategic technology trends
Business Chief North America, takes a look at Garnter’s top 10 2020 strategic technology trends.
In a recent report from Gartner, the company highlights the top 10 strategic technology trends that it predicts will drive significant disruption and opportunity in the next five to 10 years.
“For several years, the top trends focused on the intelligent digital mesh, which is a future in which smart devices deliver insightful digital services everywhere. Although intelligent digital mesh is still important, the 2020 trends are structured around the idea of “people-centric smart spaces” — which means considering how technologies will affect people (i.e., customers, employees) and the places where they live (i.e., home, office, car),” commented Gartner.
Hyperautomation
Defined as a state in which organisations use a combination of artificial intelligence (AI) and machine learning (ML) to rapidly identify and automate possible business processes, “Hyperautomation extends across a range of tools that can be automated, but also refers to the sophistication of the automation (i.e., discover, analyse, design, automate, measure, monitor, reassess).”
Gartner identifies four key implications of hyperautomation: shifting scope, evolving technology, increasing agility and engaging the workforce.
Multi experience
“Multiexperience replaces technology-literate people with people literate technology,” explains Gartner. The traditional idea of a computer from one single point of interaction into a multi-sensory and multi-touchpoint interface creating a richer and more immersive experience.
Democratization
“Democratization provides people with easy, low or no-cost access to technical or business domain expertise,” adds Gartner.
It focuses on four key areas: application development, data and analytics, design and knowledge. This trend is often referred to as ‘citizen access’, providing advice, taking action and extending the expertise of the user, in addition to reducing the timeline and resource lift for projects.
Human augmentation
Human augmentation — the use of technology and science to improve cognitive and physical experiences. “Human augmentation is not a new concept — humans have been augmenting themselves with glasses and prosthetics for hundreds of years — but the introduction of computers added a new dimension to the possibilities,” commented Gartner.
Transparency and traceability
“As consumers become more aware and savvy about how organisations are using their data — and organisations are using increasing amounts of AI and ML to drive business decisions — a trust crisis has emerged,” highlights Gartner. Who explains that enterprises must embrace concepts such as explainable AI and transparent data policies for both ethical and business reasons.
Empowered edge
“Edge computing is a topology where information processing and content collection and delivery are placed closer to the sources of the information, with the idea that keeping traffic local and distributed will reduce latency,” highlights Gartner.
Distributed cloud
Referring to “the distribution of public cloud services to locations outside the cloud provider’s physical data centers, but which are still controlled by the provider,” distributed cloud providers are responsible for all aspects of cloud service architecture, delivery, operations, governance and updates.
Autonomous things
“Autonomous things are physical devices that use AI to automate functions previously performed by humans,” comments Garnter, who explains that autonomous things can vary from semi to fully autonomous devices and machines
Blockchain
A type of distributed ledger, “an expanding chronologically ordered list of cryptographically signed, irrevocable transactional records shared by all participants in a network,” comments Garnter. This technology enables two or more parties to exchange value without needing a centralised authority.
AI security
WIth the increased number of AI solutions and potential points of attack, there will also be a rise in AI security. Gartner details that AI security includes three key perspectives: protecting AI-powered systems, using ML to understand patterns and identifying attacks and defending against them.
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