data ai digital trend quantum technology augmented
Gartner Top 10 Strategic Technology Trends for 2019Blockchain, quantum computing, augmented analytics and artificial intelligencewill drive disruption and new business models.Although science fiction may depict AI robots as the bad guys, some techgiants now employ them for security. Companies like Microsoft and Uber useKnightscope K5 robots to patrol parking lots and large outdoor areas topredict and prevent crime. The robots can read license plates, reportsuspicious activity and collect data to report to their owners.These AI-driven robots are just one example of “autonomous things,” one of theGartner Top 10 strategic technologies for 2019 with the potential to drivesignificant disruption and deliver opportunity over the next five years.“The future will be characterized by smart devices delivering increasinglyinsightful digital services everywhere,” said David Cearley, GartnerDistinguished Vice President Analyst, at Gartner 2018 Symposium/ITxpo inOrlando, Florida. “We call this the intelligent digital mesh.” * Intelligent: How AI is in virtually every existing technology, and creating entirely new categories. * Digital: Blending the digital and physical worlds to create an immersive world. * Mesh: Exploiting connections between expanding sets of people, businesses, devices, content and services.“Trends under each of these three themes are a key ingredient in driving acontinuous innovation process as part of the continuous next strategy,”Cearley said.The Gartner Top 10 Strategic Technology trends highlight changing or not yetwidely recognized trends that will impact and transform industries through2023.## Trend No. 1: Autonomous thingsWhether it’s cars, robots or agriculture, autonomous things use AI to performtasks traditionally done by humans. The sophistication of the intelligencevaries, but all autonomous things use AI to interact more naturally with theirenvironments.Autonomous things exist across five types: * Robotics * Vehicles * Drones * Appliances * AgentsThose five types occupy four environments: Sea, land, air and digital. Theyall operate with varying degrees of capability, coordination and intelligence.For example, they can span a drone operated in the air with human-assistanceto a farming robot operating completely autonomously in a field.This paints a broad picture of potential applications, and virtually everyapplication, service and IoT object will incorporate some form of AI toautomate or augment processes or human actions. Collaborative autonomousthings such as drone swarms will increasingly drive the future of AI systemsExplore the possibilities of AI-driven autonomous capabilities in any physicalobject in your organization or customer environment, but keep in mind thesedevices are best used for narrowly defined purposes. They do not have the samecapability as a human brain for decision making, intelligence or general-purpose learning.## Trend No. 2: Augmented analyticsData scientists now have increasing amounts of data to prepare, analyze andgroup — and from which to draw conclusions. Given the amount of data,exploring all possibilities becomes impossible. This means businesses can misskey insights from hypotheses the data scientists don’t have the capacity toexplore.Augmented analytics represents a third major wave for data and analyticscapabilities as data scientists use automated algorithms to explore morehypotheses. Data science and machine learning platforms have transformed howbusinesses generate analytics insight.> By 2020, more than 40% of data science tasks will be automatedAugmented analytics identify hidden patterns while removing the personal bias.Although businesses run the risk of unintentionally inserting bias into thealgorithms, augmented analytics and automated insights will eventually beembedded into enterprise applications.Through 2020, the number of citizen data scientists will grow five timesfaster than professional data scientists. Citizen data scientists use AIpowered augmented analytics tools that automate the data science functionautomatically identifying data sets, developing hypothesis and identifyingpatterns in the data. Businesses will look to citizen data scientists as a wayto enable and scale data science capabilities.Gartner predicts by 2020, more than 40% of data science tasks will beautomated, resulting in increased productivity and broader use by citizen datascientists. Between citizen data scientists and augmented analytics, datainsights will be more broadly available across the business, includinganalysts, decision makers and operational workers.## Trend No. 3: AI-driven developmentAI-driven development looks at tools, technologies and best practices forembedding AI into applications and using AI to create AI-powered tools for thedevelopment process. This trend is evolving along three dimensions: 1. 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, AI services). With these tools the professional developer can infuse AI powered capabilities and models into an application without involvement of a professional data scientist. 2. The tools used to build AI-powered solutions are being empowered with AI-driven capabilities that assist professional developers and automate tasks related to the development of AI-enhanced solutions. Augmented analytics, automated testing, automated code generation and automated solution development will speed the development process and empower a wider range of users to develop applications. 3. 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).The market will shift from a focus on data scientists partnered withdevelopers to developers operating independently using predefined modelsdelivered as a service. This enables more developers to utilize the services,and increases efficiency. These trends are also leading to more mainstreamusage of virtual software developers and nonprofessional “citizen applicationdevelopers.”~~Read more: How to Build a Business Case for Artificial Intelligence~~## Trend No. 4: Digital twinsA digital twin is a digital representation that mirrors a real-life object,process or system. Digital twins can also be linked to create twins of largersystems, such as a power plant or city. The idea of a digital twin is not new.It goes back to computer-aided design representations of things or onlineprofiles of customers, but today’s digital twins are different in four ways: 1. The robustness of the models, with a focus on how they support specific business outcomes 2. The link to the real world, potentially in real time for monitoring and control 3. The application of advanced big data analytics and AI to drive new business opportunities 4. The ability to interact with them and evaluate “what if” scenariosThe focus today is on digital twins in the IoT, which could improve enterprisedecision making by providing information on maintenance and reliability,insight into how a product could perform more effectively, data about newproducts and increased efficiency. Digital twins of an organization areemerging to create models of organizational process to enable real timemonitoring and drive improved process efficiencies.## Emerging Technology RoadmapBenchmark technology adoption patterns across your organization.Download Roadmap## Trend No. 5: Empowered edgeEdge computing is a topology where information processing and contentcollection and delivery are placed closer to the sources of the information,with the idea that keeping traffic local will reduce latency. Currently, muchof the focus of this technology is a result of the need for IoT systems todeliver disconnected or distributed capabilities into the embedded IoT world.This type of topology will address challenges ranging from high WAN costs andunacceptable levels of latency. Further, it will enable the specifics ofdigital business and IT solutions.> Technology and thinking will shift to a point where the experience will> connect people with hundreds of edge devicesThrough 2028, Gartner expects a steady increase in the embedding of sensor,storage, compute and advanced AI capabilities in edge devices. In general,intelligence will move toward the edge in a variety of endpoint devices, fromindustrial devices to screens to smartphones to automobile power generators.## Trend No. 6: Immersive technologiesThrough 2028, conversational platforms, which change how users interact withthe world, and technologies such as augmented reality (AR), mixed reality (MR)and virtual reality (VR), which change how users perceive the world, will leadto a new immersive experience. AR, MR and VR show potential for increasedproductivity, with the next generation of VR able to sense shapes and track auser’s position and MR enabling people to view and interact with their world.By 2022, 70% of enterprises will be experimenting with immersive technologiesfor consumer and enterprise use, and 25% will have deployed to production. Thefuture of conversational platforms, which range from virtual personalassistants to chatbots, will incorporate expanded sensory channels that willallow the platform to detect emotions based on facial expressions, and theywill become more conversational in interactions.Eventually, the technology and thinking will shift to a point where theexperience will connect people with hundreds of edge devices ranging fromcomputers to cars.## Trend No. 7: BlockchainBlockchain is a type of distributed ledger, an expanding chronologicallyordered list of cryptographically signed, irrevocable transactional recordsshared by all participants in a network. Blockchain allows companies to tracea transaction and work with untrusted parties without the need for acentralized party (i.e., a bank).This greatly reduces business friction and has applications that began infinance, but have expanded to government, healthcare, manufacturing, supplychain and others. Blockchain could potentially lower costs, reduce transactionsettlement times and improve cash flow. The technology has also given way to ahost of blockchain-inspired solutions that utilize some of the benefits andparts of blockchain.Pure blockchain models are immature and can bedifficult to scale. . However,businesses should begin evaluating the technology, as blockchain will create$3.1T in business value by 2030. Blockchain inspired approaches that do notimplement all the tenets of blockchain deliver near term value but do notprovide the promised highly distributed decentralized consensus models of apure blockchain.~~Read more: The CIO’s Guide to Blockchain~~## Trend No. 8: Smart spacesA smart space is a physical or digital environment in which humans andtechnology-enabled systems interact in increasingly open, connected,coordinated and intelligent ecosystems. As technology becomes a moreintegrated part of daily life, smart spaces will enter a period of accelerateddelivery. Further, other trends such as AI-driven technology, edge computing,blockchain and digital twins are driving toward this trend as individualsolutions become smart spaces.Smart spaces are evolving alone five key dimensions: Openness, connectedness,coordination, intelligence and scope. Essentially, smart spaces are developingas individual technologies emerge from silos to work together to create acollaborative and interaction environment.The most extensive example of smart spaces is smart cities, where areas thatcombine business, residential and industrial communities are being designedusing intelligent urban ecosystem frameworks, with all sectors linking tosocial and community collaboration.## Trend No. 9: Digital ethics and privacyConsumers have an growing awareness of the value of their personalinformation, and they are increasingly concerned with how it’s being used bypublic and private entities. Enterprises that don’t pay attention are at riskof consumer backlash.Conversations regarding privacy must be grounded in ethics and trust. Theconversation should move from “Are we compliant?” toward “Are we doing theright thing?”Governments are increasingly planning or passing regulations with whichcompanies must be compliant, and consumers are carefully guarding or removinginformation about themselves. Companies must gain and maintain trust with thecustomer to succeed, and they must also follow internal values to ensurecustomers view them as trustworthy.## Trend No. 10: Quantum computingQuantum computing is a type of nonclassical computing that is based on thequantum state of subatomic particles that represent information as elementsdenoted as quantum bits or “qubits.”Quantum computers are an exponentially scalable and highly parallel computingmodel. A way to imagine the difference between traditional and quantumcomputers is to imagine a giant library of books.While a classic computer would read every book in a library in a linearfashion, a quantum computer would read all the books simultaneously. Quantumcomputers are able to theoretically work on millions of computations at once.Quantum computing in the form of a commercially available, affordable andreliable service would transform some industries.~~Read more: The CIO’s Guide to Quantum Computing~~Real-world applications range from personalized medicine to optimization ofpattern recognition. This technology is still in an emerging state, whichmeans it is a good time for businesses to increase their understanding ofpotential applications and consider any security implications. Aside from aselect group of businesses where specific quantum algorithms would provide amajor advantage, most enterprises could remain in exploration phase through2022 and begin exploiting the technology later.