Gartner: Top strategic technology trends for 2020 (1st part)

Barcelona, January 8, 2019.- Gartner Technology Consultant is a source of information, recommendations, trends and resources that should always be taken into account by an information technology professional. AndSoft traditionally uses Gartner to learn: “Top strategic technology trends for 2020”. This is a 52 page document that we have summarized in 8 pages for two articles. In any case, we provide the web link to be able to print the entire document. In this first part, Gartner tells us about: Hyperautomation, Multiexperience, Democratization, Human Augmentation, Transparency and Traceability.

Trend No. 1: Hyperautomation 

Automation refers to the use of technology to facilitate or perform tasks that originally required some form of human judgment or action. The term “tasks” refers not only to tasks and activities in the execution, working or operational environment, but it also encompasses tasks in thinking, discovering and designing these automations themselves. 

Hyperautomation refers to the combination of multiple machine learning, packaged software and automation tools to deliver work. The propensity to use particular types of automation will be highly dependent on the organization’s existing IT architecture and business practices. 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, reassess). 

Hyperautomation is an unavoidable market state in which organizations must rapidly identify and automate all possible business processes with several implications: 

The scope of automation changes. The automation focus now spans automating individual, discrete tasks and transactions based on static and rigid rules, to automating more and more knowledge work. In turn, those levels of automation enable enhanced and more dynamic experiences and better business outcomes. 

A range of tools will be used to manage work and coordinate resources. Increasingly, organizations will use an evolving set of technologies to support an ever-expanding business scope. The tools include task and process automation, decision management, and packaged software — all of which will incorporate more and more machine learning technologies. 

Architecting for agility is required. This means organizations need the ability to reconfigure operations and supporting processes in response to evolving needs and competitive threats in the market. A hyperautomated future state can only be achieved through hyperagile working practices and tools. 

Workforce engagement is needed to reinvent how employees deliver value. Without engaging employees to digitally transform their operations, the organization is destined to gain only incremental benefits. This means overcoming the challenges associated with silos and the way the organization allocates resources and integrates the capabilities of its partners and suppliers. 

Trend No. 2: Multiexperience 

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. Virtual reality (VR), augmented reality (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 the future multisensory and multitouchpoint experience. The ability to communicate with users across many human senses will provide a richer environment for delivering nuanced information. 

The “computer” in a multiexperience world is the environment around the user, including many touchpoints and sensory inputs. The multitouchpoint aspect of the experience will connect peopleacross edge devices, including traditional computing devices, wearables, automobiles, environmental sensors and consumer appliances. The multisensory aspect of the experience will use all human senses as well as advanced computer senses (such as heat, humidity and radar) as appropriate across this rich sea of devices. In the future, the very notion of “computer” will seem like a quaint and antiquated idea as the spaces that we inhabit become multisensory and multitouchpoint interfaces. 

The long-term manifestation of multiexperience is also called the ambient experience. However, this will happen only slowly through 2029 and beyond. Privacy concerns in particular may dampen the enthusiasm and impact of adoption. On the technical front, long life cycles of many consumer devices, and the complexity of having many creators developing elements independently, will be an enormous barrier to seamless integration. Don’t expect automatic plug and play of devices, applications and services. Instead, there will be proprietary ecosystems of devices in the near term. 

Focus on targeted use of immersive experiences and conversational platforms for highly specific scenarios as they evolve through 2024. These experiences and platforms will overlap with one another, incorporating a full array of sensory input/output channels delivered in various device scenarios. These may be targeted experiences on specific devices, but opportunities will grow for more robust scenarios across multiple devices and sensory channels to support specific environments (e.g., an ambient experience in a manufacturing plant). Complement these targeted solutions with an evolving multiexperience development platform that incorporates more sensory channels and more device targets well beyond the web and mobile targets of more traditional development platforms. 

Trend No. 3: Democratization 

Democratization is focused on providing people with access to technical expertise (e.g., ML, application development) or business domain expertise (e.g., sales process, economic analysis) via a radically simplified experience and without requiring extensive and costly training. The notion of “citizen access” (e.g., citizen data scientists, citizen integrators) as well as the evolution of citizen development and no-code models are examples of democratization. Development of expert systems or virtual assistants based on AI and decision models is another important aspect of offer a continuous experience. These systems provide advice or take actions on behalf of people to extend their democratization. knowledge or expertise beyond their experience or training. It is important to note that the target for the democratization trend could be any person inside or outside the enterprise including customers, business partners, corporate executives, salespeople, assembly line workers, professional application developers, and IT operations professionals. There are four key aspects to the democratization trend that are accelerating in 2020 through 2023: 

Democratization of Application Development. AI PaaS provides access to sophisticated AI tools to leverage custom-developed applications. These solutions provide AI-model-building tools, APIs and associated middleware that enable the building/training, deployment and consumption of machine learning models running on prebuilt infrastructure-as-cloud services. These cover vision, voice, and general data classification and prediction models of any type. 

Democratization of Data and Analytics. The tools used to build AI-powered solutions are expanding from tools targeting data scientists (AI infrastructure, AI frameworks and AI platforms) to tools targeting the professional developer community (AI platforms and AI services) and the citizen data scientist. This includes tools to generate synthetic training data, 

Democratization of Design. In addition, low-code application development platform tools used to build AI-powered solutions are themselves being empowered with AI-driven capabilities that assist professional developers and automate tasks related to the development of AI- enhanced solutions. This expands on the low-code, no-code phenomenon with automation of additional application development functions to empower the citizen developer. 

Democratization of Knowledge. Non-IT professionals increasingly have access to powerful tools and expert systems that empower them to exploit and apply specialized skills beyond their own expertise and training. Dealing with the issues around “shadow AI” in this user-led environment will be a challenge.

Trend No. 4: Human Augmentation 

Human augmentation refers to the enhancement of human capabilities and capacity through the use of technology and science. Humans have always used technology and science in this fashion. Even before the introduction of the computer, technologies such as the typewriter, copy machine and printing press augmented the human ability to create, copy and publish text. Glasses, hearing aids and false teeth are all historical examples of human augmentation. 

The computer era has added new dimensions to human augmentation. Word processing, desktop publishing, webpages, blogs and social media greatly extend our ability to create and publish text. With the rise of new technologies such as IoT, AI, smart speakers and VR emerging from computer science, and technologies such as CRISPR18 emerging from biological science, entirely new opportunities for human augmentation are emerging. 

Human augmentation explores how technology can be used to deliver cognitive and physical improvements as an integral part of the human experience. Instead of computers and applications being something outside the normal human experience, they become a natural — and sometimes necessary — part of the day-to-day human experience. Moreover, human augmentation also includes bioengineering factors that go beyond exploitation of computers and applications. We are already on this path to a certain extent. For many people, smartphones are an essential tool and constant companion. Social networks and electronic connections like email have become a primary link between people. Pharmaceuticals have augmented humans since well before the advent of computers. Human augmentation is a prime example of combinatorial innovation which brings together many trends including: 

Hyperautomation and the development of expert systems to democratize access to skills beyond current experience and training. Empowered edge devices and autonomous things, which exist in spaces around humans and augment their capabilities. 

Trend No. 5: Transparency and Traceability 

Digital ethics and privacy are growing concerns for individuals, organizations and governments. Consumers are increasingly aware their personal information is valuable and are demanding control. Organizations recognize the increasing risk of securing and managing personal data, and governments are implementing strict legislation to ensure they do. 

Artificial Intelligence and the use of ML models to make autonomous decisions raises a new level of concern, with digital ethics driving the need for explainable AI and the assurance that the AI system is operating in an ethical and fair manner. Transparency and traceability are critical elements to support these digital ethics and privacy needs. 

Transparency and traceability are not a single product or a single action. It refers to a range of attitudes, actions, and supporting technologies and practices designed to address regulatory requirements, enshrine an ethical approach to use of AI and other advanced technologies, and repair the growing lack of trust in companies. 

Transparency and traceability require a focus on six key elements of trust: 

Ethics — Does the organization have strong moral principles on the use of personal data, algorithms and the design of systems that go beyond regulations and are transparent to all interested parties? 

Integrity — Does the organization have a proven track record of designing systems that reduce or eliminate bias and inappropriate use of personal data? 

Openness — Are the ethical principles and privacy commitments clear and easily accessible — and do changes to such policies bring the appropriate constituencies into the decision-making process? 

Accountability — Are there mechanisms for testing, assurance and auditability such that privacy or ethical concerns can be identified and addressed? This applies not only to adherence to regulatory requirements, but also to new ethical or privacy concerns that arise from future technologies. 

Competence — Has the organization implemented design principles, processes, testing and training so that concerned constituencies can feel comfortable that the organization can execute on its promises? 

Consistency — Are policies and processes handled consistently? 

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