The analysts define strategic technology trends as those that have substantial disruptive potential along with the kind of attention that’s encouraging widespread adoption. Underlying the eight elements that weave the smart mesh are emerging calls for digital ethics and privacy guarantees and the prospect of quantum computing that will kick machine intelligence into hyperdrive.
Gartner executive vice president and global head of research Mike Harris points out, “Nearly two-thirds of CEOs and CFOs anticipate business model change, frequently due to digital transformation, and investors are encouraging that change. They reward organizations that wrap every product and service with digital capabilities.”
And the technology trends affect business processes as well as company products. Harris explains, company executives “are not just interested in data—which is now old news—they are interested in what you do with data through advanced analytics and artificial intelligence (AI). Leaders apply technology and information in unique and creative ways to outperform their peers. It’s what distinguishes them from the rest, and that’s where ContinuousNEXT comes in.” ContinuousNEXT is a difficult, but reasonable strategic answer to continuous, accelerating change.
THE TOP 10 TECHNOLOGY TRENDS
- Autonomous things. These are things that use AI to perform human tasks. The group includes vehicles, robotics, drones, appliances, and agents (Google Home, Amazon Alexa, etc.). They are getting smarter and are now ubiquitous, occupying four environments: sea, land, air, and digital. David Cearley, vice president and Gartner Fellow, predicts, “As autonomous things proliferate, we expect a shift from stand-alone intelligent things to a swarm of collaborative intelligent things, with multiple devices working together, either independently of people or with human input.”
- Augmented analytics. With the emergence of Big Data, the task of managing business information has moved beyond human possibility. “Augmented analytics represents a third major wave for data and analytics capabilities as data scientists use automated algorithms to explore more hypotheses.” Gartner predicts that by 2020, more than 40% of data science tasks will be automated, and the number of “citizen data scientists” will grow five times faster than professional data scientists. Helping them will be natural language queries, algorithms that find relevant patterns, features and models that can be autoselected, and autogenerated code.
- AI-driven development. Likewise, there will be a similar movement toward embedding AI-enabled tools to assist professional developers create AI-powered solutions without the involvement of a professional data scientist. An important dimension of the evolution of this trend is under way. “AI-enabled tools are evolving from assisting and automating functions related to application development (AD) to being enhanced with business domain expertise and automating activities higher on the AD process stack (from general development to business solution design).” These tools are encouraging the use of virtual software developers and nonprofessional “citizen application developers.”
- Digital twins. A digital twin (computer model) of a real-world object, like a power plant, can be invaluable as a way to monitor and even remotely initiate maintenance for the actual plant. The current use of twinning usually involves computer models of IoT (Internet of things) devices. Gartner expects “digital twins of an organization [to emerge] to create models of organizational process to enable real-time monitoring and drive improved process efficiencies.”
- Empowered edge. Edge computing is a way to move the information processing and content collection away from the center of the cloud out closer to the data sources (the edges) where IoT devices reside. Removing the extra travel points reduces latency. “Through 2028, Gartner expects a steady increase in the embedding of sensor, storage, compute and advanced AI capabilities in edge devices.”
- Immersive experience. VR (virtual reality), AR (augmented reality), and MR (mixed reality) will continue to change how users interact with the world, and “by 2022, 70% of enterprises will be experimenting with immersive technologies for consumer and enterprise use, and 25% will have deployed to production.”
- Blockchain. Gartner’s concise definition of blockchain reads: “Blockchain is a type of distributed ledger, an expanding chronologically ordered list of cryptographically signed, irrevocable transactional records shared by all participants in a network.” Despite its erratic history with the bitcoin experiment, Gartner recommends a serious look. “Businesses should begin evaluating the technology, as blockchain will create $3.1T in business value by 2030.”
- Smart spaces. What Gartner sees as “smart spaces” are the places where human and computer intelligence mesh in an environment that isn’t shared but rather enjoined by both. Here’s the company’s description: “A smart space is a physical or digital environment in which humans and technology-enabled systems interact in increasingly open, connected, coordinated and intelligent ecosystems.” Sounds almost like a lake where all the fish will soon be soluble, or at least indistinguishable.
- Digital ethics and privacy. Gartner analysts predict a growing public awareness of how our information is being used and is sometimes exposed to great risk by corporations. They warn, “Enterprises that don’t pay attention are at risk of consumer backlash. Conversations regarding privacy must be grounded in ethics and trust. The conversation should move from ‘Are we compliant?’ toward ‘Are we doing the right thing?’”
- Quantum computing. Now is a good time for businesses to increase their understanding of potential applications for quantum computing as well as the threat it poses to standard security measures like encryption. Presently, in a very early stage of development, this class of computers doesn’t use transistors and digital bits to flip switches to on or off positions (0 or 1). They use quantum bits (qubits), which have the very confusing ability to be either on or off, 0 or 1, or on and off (0 and 1) at precisely the same time. The systems also use something called quantum entanglement, which is the physical state created when pairs or groups of particles can’t be described independently of the state of the others in its pair or group, even if they’re a distance apart.
The quantum state of the computer is the system in its entirety. Gartner offers this example to illustrate the difference. Imagine a very large library of books. A classic computer could read every book in the building in a linear fashion. A quantum computer would read all the books simultaneously. “Quantum computing in the form of a commercially available, affordable and reliable service would transform some industries.” In truth, if you factor in the far-reaching influence of these machines, it would be more like “most industries.” The time to start looking at potential future impacts for these computers is now.
The ContinuousNEXT strategy that Gartner proposes for meeting this panoply of accelerating changes almost sounds like a peddle-as-fast-as-you-can measure. Certainly, there’s a need to keep up on the changes. To get an idea of what sort of timetable you have, consider the historical timeline for the birth and growth of the Industrial Revolution, and then lay that alongside the timeline for the Digital Revolution.
NOTE: For an interesting comparison of Gartner’s 2017, 2018, and 2019 Top-10 Technology Trends you can see the previous lists here https://www.gartner.com/smarterwithgartner/gartner-top-10-strategic-technology-trends-for-2019/. Just check the navigation bar on the right side of the page titled “Most Read” and click on the year.