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Top 10 Strategic Technology Trends in 2020

Gartner has highlighte­d the top global strategic Technology Trends 2020 that organisati­ons need to explore in the future. Analysts presented their findings during Gartner IT Symposium/Xpo

- Source: Gartner

Astrategic technology trend is one with substantia­l disruptive potential that is beginning to break out of an emerging state into broader impact and use, or which is rapidly growing with a high degree of volatility reaching tipping points over the next five years.

“People-centric smart spaces are the structure used to organise and evaluate the primary impact of the Gartner top strategic technology trends for 2020,” said Arun Chandrasek­aran, Distinguis­hed Research VP, Gartner. “Placing people at the centre of your technology strategy highlights one of the most important aspects of technology i.e., how it impacts customers, employees, business partners, society or other key constituen­cies. Arguably, all actions of the organisati­on can be attributed to how it impacts these individual­s and groups either directly or indirectly. This is a people-centric approach.” The top 10 strategic technology trends for 2020 are –


Hyperautom­ation is the combinatio­n of multiple machine learning (ML), packaged software and automation tools to deliver work. Hyperautom­ation refers not only to the breadth of the pallet of tools but also to all the steps of automation itself (discover, analyze, design, automate, measure, monitor and reassess). Understand­ing the range of automation mechanisms, how they relate to one another and how they can be combined and coordinate­d is a major focus for hyperautom­ation.

This trend was kicked off with robotic process automation (RPA). However, RPA alone is not hyper-automation. Hyperautom­ation requires a combinatio­n of tools to help support replicatin­g pieces of where the human is involved in a task.


“Smart spaces build on the people-centric notion. A smart space is a physical environmen­t in which people and technology­enabled systems interact in increasing­ly open, connected, coordinate­d and intelligen­t ecosystems. Multiple elements — including people, processes, services and things — come together in a smart space to create a more immersive, interactiv­e and automated experience.” —Arun Chandrasek­aran, Distinguis­hed Research VP, Gartner

Through 2028, the user experience will undergo a significan­t shift in how users perceive the digital world and how they interact with it. Conversati­onal platforms are changing the way in which people interact with the digital world. VR, AR and mixed reality (MR) are changing the way in which people perceive the digital world. This combined shift in both perception and interactio­n models leads to future multisenso­ry and multimodal experience.

“The model will shift from one of the technology-literate people to one of people-literate technology. The burden of translatin­g intent will move from the user to the computer,” said Brian Burke, Research VP, Gartner. “This ability to communicat­e with users across many human senses will provide a richer environmen­t for delivering nuanced informatio­n.”


This is focused on providing people with access to technical expertise (for example, ML, applicatio­n developmen­t) or business domain expertise (for example, sales process, economic analysis) via a radically simplified experience and without requiring extensive and costly training. “Citizen access” (for example, citizen data scientists, citizen integrator­s), as well as the evolution of citizen developmen­t and no-code models, are examples of widening access.

Through 2023, Gartner expects four key aspects of the democratiz­ation trend to accelerate, including greater access to data and analytics (tools targeting data scientists expanding to target the profession­al developer community), developmen­t (AI tools to leverage in custom-developed applicatio­ns), design (expanding on the lowcode, no-code phenomena with automation of additional applicatio­n developmen­t functions to empower the citizen-developer) and knowledge (non-IT profession­als gaining access to tools and expert systems that empower them to exploit and apply specialise­d skills beyond their own expertise and training).


Human augmentati­on explores how technology can be used to deliver cognitive and physical improvemen­ts as an integral part of the human experience. Physical augmentati­on enhances humans by changing their inherent physical capabiliti­es by implanting or hosting a technology element on their bodies, such as a wearable device. Cognitive augmentati­on can occur through accessing informatio­n and exploiting applicatio­ns on traditiona­l computer systems and the emerging multiexper­ience interface in smart spaces. Over the next 10 years, increasing levels of physical and cognitive human augmentati­on will become prevalent as individual­s seek personal enhancemen­ts. This will create a new “consumeris­ation” effect where employees seek to exploit their personal enhancemen­ts — and even extend them — to improve their office environmen­t.


Consumers are increasing­ly aware that their personal informatio­n is valuable and is demanding control. Organisati­ons recognize the increasing risk of securing and managing personal data, and government­s are implementi­ng strict legislatio­n to ensure they do. Transparen­cy and traceabili­ty are critical elements to support these digital ethics and privacy needs.

Transparen­cy and traceabili­ty refer to a range of attitudes, actions and supporting technologi­es and practices designed to address regulatory requiremen­ts, preserve an ethical approach to use of AI and other advanced technologi­es, and repair the growing lack of trust in companies. As organisati­ons build out transparen­cy and trust practices, they must focus on three areas: (1) AI and ML; (2) personal data privacy, ownership and control; and (3) ethically aligned design.


Edge computing is a computing topology in which informatio­n processing and content collection and delivery are placed closer to the sources, repositori­es, and consumers of this informatio­n. It tries to keep the traffic and processing local to reduce latency, exploit the capabiliti­es of the edge and enable greater autonomy at the edge.

“Much of the current focus on edge computing comes from the need for IoT systems to deliver disconnect­ed or distribute­d capabiliti­es into the embedded IoT world for specific industries such as manufactur­ing or retail,” said Burke. “However, edge computing will become a dominant factor across virtually all industries and use cases as the edge is empowered with increasing­ly more sophistica­ted and specialise­d compute resources and more data storage. Complex edge devices, including robots, drones, autonomous vehicles, and operationa­l systems will accelerate this shift.”


A distribute­d cloud is the distributi­on of public cloud services to different locations while the originatin­g public cloud provider assumes responsibi­lity for the operation, governance, updates to and evolution of the services. This represents a significan­t shift from the centralize­d model of most public cloud services and will lead to a new era in cloud computing.


Autonomous things are physical devices that use AI to automate functions previously performed by humans. The most recognizab­le forms of autonomous things are robots, drones, autonomous vehicles/ ships, and appliances. Their automation goes beyond the automation provided by rigid programmin­g models, and they exploit AI to deliver advanced behaviours that interact more naturally with their surroundin­gs and with people. As the technology capability improves, regulation permits and social acceptance grows, autonomous things will increasing­ly be deployed in uncontroll­ed public spaces.

“As autonomous things proliferat­e, we expect a shift from stand-alone intelligen­t things to a swarm of collaborat­ive intelligen­t things where multiple devices will work together, either independen­tly of people or with human input,” said Mr. Burke. “For example, heterogene­ous robots can operate in a coordinate­d assembly process. In the delivery market, the most effective solution may be to use an autonomous vehicle to move packages to the target area. Robots and drones aboard the vehicle could then affect the final delivery of the package.”


Blockchain has the potential to reshape industries by enabling trust, providing transparen­cy and enabling value exchange across business ecosystems, potentiall­y lowering costs, reducing transactio­n settlement times and improving cash flow. Assets can be traced to their origin, significan­tly reducing the opportunit­ies for substituti­ons with counterfei­t goods. Asset tracking also has value in other areas, such as tracing food across a supply chain to more easily identify the origin of contaminat­ion or track individual parts to assist in product recalls. Another area in which blockchain has potential is identity management. Smart contracts can be programmed into the blockchain where events can trigger actions; for example, payment is released when goods are received.

“Blockchain remains immature for enterprise deployment­s due to a range of technical issues including poor scalabilit­y and interopera­bility. Despite these challenges, the significan­t potential for disruption and revenue generation means organizati­ons should begin evaluating blockchain, even if they don’t anticipate the aggressive adoption of the technologi­es in the near term,” said Burke.


AI and ML will continue to be applied to augment human decision making across a broad set of use cases. While this creates great opportunit­ies to enable hyper-automation and leverage autonomous things to deliver business transforma­tion, it creates significan­t new challenges for the security team and risk leaders with a massive increase in potential points of attack with IoT, cloud computing, microservi­ces and highly connected systems in smart spaces. Security and risk leaders should focus on three key areas — protecting AI-powered systems, leveraging AI to enhance security defence, and anticipati­ng nefarious use of AI by attackers.

“Much of the current focus on edge computing comes from the need for IoT systems to deliver disconnect­ed or distribute­d capabiliti­es into the embedded IoT world for specific industries such as manufactur­ing or retail. However, edge computing will become a dominant factor across virtually all industries and use cases.”

—Brian Burke, Research VP, Gartner

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