Gartner announces the top ten strategic technology trends in 2019, with automation technology topping the list
From October 14th to 18th, analysts at Gartner Symposium/ITxpo 2018 discussed the top 10 strategic technology trends that companies and organizations need to explore in 2019 (Gartner Top 10 Strategic Technology Trends 2019).
Gartner defines strategic technology trends as strategic technology trends with enormous destructive potential, and the strategy has begun to evolve from emerging breakthroughs to applications with broader impacts – or a rapidly growing trend with high volatility The critical point will be reached in the next five years.
"The future will feature smart devices that provide increasingly insightful digital services everywhere, which we call smart digital grids," said David Cearley, vice president and researcher at Gartner. "The smart digital grid has been in the last two years. It has always been one of the focal points and has been the main driver for 2019. The trends under these three themes are a key factor driving the continuous innovation process as part of the ContinuousNEXT strategy."
- Intelligence: How artificial intelligence penetrates into almost all existing technologies and creates entirely new categories.
- Numbers: Combine the digital world with the real physical world to create an immersive world.
- Grid: Leverage the ever-expanding link between people, businesses, devices, content and services.
“For example, automation and enhanced intelligence in the form of artificial intelligence (AI) with IoT, edge computing and digital twins provides a highly integrated smart space. This combined effect of multiple trends will create new opportunities and drive The new wave of disruption is a sign of Gartner's top ten strategic technology trends in 2019."
Although science fiction may portray artificial intelligence robots as bad guys, some tech giants are now using them for security management. Companies such as Microsoft and Uber use the Knightscope K5 robotic patrol car park and large outdoor areas to predict and prevent crime. The robot can read the license plate, report suspicious activity and collect data to report to its owner.
These artificial intelligence-driven robots are just one example of "automation of things". It is one of Gartner's top ten strategic technologies in 2019, and it is likely to bring major disruptions and opportunities in the next five years.
Gartner points out that technologies such as blockchain, quantum computing, enhanced analysis, and artificial intelligence will drive disruptive new business models.
The top ten strategic technology trends announced by Gartner in 2019 are:
1. Automation of everything
Autonomous devices such as robots, drones, and self-driving cars will rely on the use of AI to automate functions previously performed by humans. Their automation goes beyond the automation provided by the rigid programming model, which uses AI to provide advanced behavior that interacts more naturally with the surrounding environment and people.
“With the proliferation of autonomous things, we expect to move from independent intelligence to a whole bunch of collaborative intelligence, with multiple devices working together, whether it is independent of people or human input,” Mr. Cearley said. “For example, if a drone checks a large field and finds it ready to be mined, it can dispatch an 'automatic oiler' to perform the task. In the logistics delivery market, the most effective solution might be to use automatic Driving the vehicle moves the parcel to the target area. Then the robots and drones on the vehicle ensure the final delivery of the parcel."
There are five main types of "automated things":
- Robot
- vehicle
- drone
- Home appliances
- Media
These five types occupy four environments: ocean, land, air, and numbers. They all have varying degrees of competence, coordination and intelligence. For example, they can span agricultural robots that operate completely autonomously in the field across drones that are manually assisted to fly in the air. This portrays a broad picture of potential applications—almost every application, service, and IoT object will use some form of AI to automate or enhance processes or human operations.
Explore the possibility of AI-driven autonomous functions in any physical object in an organization or customer environment, but it should also be remembered that these devices are best suited for narrowly defined purposes. They differ from the human brain's ability to make decisions, intelligence, or general learning.
2. Enhanced analysis
Enhanced analysis represents the third wave of data and analytics capabilities because data scientists can use automated algorithms to explore more hypotheses and possibilities.
Enhanced analysis focuses on specific areas of intelligence enhancement, using machine learning (ML) to transform the way in which analytics content is developed, consumed, and shared. Enhanced analytics will quickly advance to mainstream applications as a key feature of data preparation, data management, modern analytics, business process management, process mining and data science platforms.
Automated insights from enhanced analytics will also be embedded in enterprise applications, changing the way companies generate analytics insights. For example, human resources, finance, sales, marketing, customer service, procurement, and asset management. These synergies and collocations will optimize the decisions and actions of all employees in their environment, not just for analysts and data scientists. Enhanced analysis automates data preparation, insight generation, and insight visualization, in many cases without the involvement of professional data scientists.
“This will lead to the further ubiquity of data science, a set of emerging functions and practices that enable users who are primarily working outside the statistical and analytical realm to extract predictive and normative insights from the data,” Cearley Said the gentleman.
“By 2020, the number of ordinary citizen data scientists will grow five times faster than the number of expert data scientists. Organizations can use citizen data scientists to fill gaps in data science and machine learning talents due to shortages and high costs of data scientists. ."
“By 2020, more than 40% of data science tasks will be automated.” Enhanced analysis identifies hidden patterns while eliminating personal bias. Between citizen data scientists and enhanced analytics, data insights will be more widely used across the enterprise, including analysts, decision makers, and operations workers.
3. AI driver development
The market is rapidly shifting from a model where professional data scientists must work with application developers to create most artificial intelligence-enhanced solutions, transforming into a model that professional developers can use as a separate model of the predefined models provided by the service. This provides developers with an ecosystem of artificial intelligence algorithms and models, as well as development tools tailored to integrate AI functionality and models into the solution.
As AI is applied to the development process itself to automate various data science, application development and testing functions, another opportunity for professional application development "peak" has emerged. By 2022, at least 40% of new application development projects will have AI co-developers in their teams.
“Ultimately, the highly advanced artificial intelligence-based development environment automation application will usher in a new era of 'civilian application developers' in both functional and non-functional aspects, and non-professionals will be able to automatically generate new ones using AI-driven tools. The solution. It's nothing new for non-professionals to generate applications without coding, but we want AI-driven systems to increase flexibility,” Mr. Cearley said.
AI-driven development focuses on tools, techniques, and best practices for embedding AI into applications and using AI to create AI-driven tools for the development process. This trend is developing in three ways:
- Tools for building AI-based solutions are expanding from tools for data scientists (AI infrastructure, AI frameworks and AI platforms) to tools for professional developer communities (AI platforms, AI services).
- Tools for building AI-based solutions are being empowered with AI-driven capabilities that help professional developers automate tasks related to AI-enhanced solution development.
- AI-enabled tools are evolving from assisting and automating application development (AD)-related functions to higher-level activities that use business domain expertise and automate the AD process stack (from general development to business solution design).
The market will move from a data scientist focused on working with developers to a developer working independently using a predefined model provided as a service. This allows more developers to take advantage of these services and increase efficiency.
4. Digital twins
Digital twins refer to the digital representation of real-world entities or systems. By 2020, Gartner estimates that there will be more than 20 billion connected sensors and endpoints, and digital twins will connect billions of physical devices. Corporate organizations will implement digital twins from the start. They will evolve over time, improving their ability to collect and visualize the right data, applying the right analytics and rules, and responding effectively to business goals.
“One aspect of the development of digital twins that transcends the Internet of Things is that companies implement their organization's Digital Twins (DTO). DTO is a dynamic software model that relies on operations or other data to understand how an organization implements its business model, connecting its current State, deploy resources and respond to changes to meet expected customer value,” Mr. Cearley said. “DTO helps increase the efficiency of business processes and create more flexible, dynamic, and responsive processes that automatically react to changing conditions.”
Digital twins can also be connected to create twins in large systems, such as power plants or cities. The idea of digital twins is not new. It can be traced back to computer-aided design representations of things or customers' online materials, but today's digital twins differ in four ways:
- the robustness of the model, focusing on how they support specific business outcomes;
- links to the real world, possibly for real-time monitoring and control;
- Apply advanced big data analytics and artificial intelligence to drive new business opportunities;
- Ability to interact with them and evaluate "what if" scenarios.
Today's focus is on digital twins in the Internet of Things – it can improve business decisions by providing information about maintenance and reliability, insight into how products are executed more efficiently, new product data and increased efficiency.
5. Empowering the edge
Edge refers to the endpoint device that people use or embed in the world around us. Edge computing describes a computational topology in which information processing, content collection, and delivery are closer to these endpoints. It attempts to keep traffic and processing closer to 'localization' with the goal of reducing traffic loss and latency.
In the short term, the edge is driven by the Internet of Things and needs to be handled close to the endpoint rather than a centralized cloud server. However, cloud computing and edge computing are not creating new architectures, but as complementary models, cloud services are managed as centralized services—not only on centralized servers, but also on local distributed servers and edge devices themselves. .
Gartner expects that in the next five years (2028), dedicated AI chips and more powerful processing power, storage and other advanced features will be added to a wider range of edge devices. The extreme heterogeneity of the embedded IoT world and the long life cycle of assets such as industrial systems will present significant management challenges. In the long run, as the 5G matures, the ever-expanding edge computing environment will return more powerful communications back to centralized services. 5G offers lower latency, higher bandwidth, and (very importantly edge) the number of nodes per square kilometer (edge endpoints) increases dramatically.
Currently, much of the focus of this technology is on the need for IoT systems to provide disconnected or distributed functionality in the embedded IoT world. This type of topology will address challenges such as high WAN costs and unacceptable levels of latency. In addition, it will implement the details of digital business and IT solutions.
6. An immersive experience (immersion technology)
The conversational platform is changing the way people interact with the digital world. Virtual reality (VR), augmented reality (AR), and mixed reality (MR) are changing the way people perceive the digital world. This combined shift in perception and interaction models will lead to an immersive user experience in the future.
“Over time, we will transform from considering personal devices and decentralized user interface (UI) technologies to multi-channel and multi-modal experiences. Multi-mode experiences connect people to the digital world, including traditional computing devices, wearable devices Hundreds of edge devices, such as cars, environmental sensors and consumer electronics," said Mr. Cearley.
“The multi-channel experience will use all human senses and advanced computer senses (such as heat, humidity and radar) in these multi-mode devices. This multi-experience environment will create an environmental experience in which the space around us defines “ "Computer", not a single device. In fact, the environment is a computer."
By 2022, 70% of companies will try to use immersive technology for consumer and enterprise use, and 25% will be deployed to production. The future of the conversational platform, from virtual personal assistants to chat bots, will incorporate an expanded sensory channel that enables the platform to detect emotions based on facial expressions and they will become more smoothly engaged in the interaction.
7. Blockchain
It is a distributed ledger that is expected to reshape the industry by enabling trust, providing transparency and reducing friction between business ecosystems, thereby reducing costs, reducing transaction settlement time and improving cash flow. Today, trust is placed in banks, stock exchanges, governments, and many other agencies as central authorities, safely maintaining a “single version of facts” in its database. Concentrated trust models increase transaction latency and friction costs (commissions, fees, and time value of money). The blockchain provides another form of trust that does not require a central authority to arbitrate transactions.
“Current blockchain technologies and concepts are not yet mature in mission-critical, large-scale business operations, and little is known and unconfirmed. This is especially true for complex elements that support more complex scenarios,” Mr. Cearley said. . “Despite the challenges, the enormous potential for disruption means that CIOs and IT leaders should start evaluating blockchains, even if they don’t actively adopt these technologies in the next few years.”
At present, many blockchain plans do not implement all the attributes of the blockchain, such as highly distributed databases.These blockchain-based solutions are positioned as a means of achieving operational efficiencies through automated business processes or through digital recording. They have the potential to enhance information sharing between known entities and improve opportunities to track and track physical and digital assets.
However, these methods miss the value of real blockchain disruptive effects and may increase vendor lock-in. Organizations that choose this type of approach should be aware of these limitations and be prepared to gradually complete the blockchain solution over time to ensure that the same results can be achieved by using existing non-blockchain techniques more efficiently and efficiently. .
Gartner expects the blockchain to create 3.1 trillion business value by 2030.
8. Smart space
Smart space refers to a physical or digital environment, human and technically supported systems that interact in an increasingly open, connected, coordinated, and intelligent ecosystem. Multiple elements—including people, processes, services, and things—will be brought together in a smart space to create a more immersive, interactive, and automated experience for the target audience and industry scenes.
“This trend has been integrated for some time, such as smart cities, digital workplaces, smart homes and connected factories. We believe that the market is entering a period of accelerating the provision of powerful smart spaces, and technology is an integral part of our daily lives. Whether as an employee, customer, consumer, community member or citizen," said Mr. Cearley.
The five key dimensions of the main expansion of smart space are: openness, connectivity, coordination, intelligence and application scope.
9. Digital Ethics and Privacy
Digital ethics and privacy are issues of increasing concern to individuals, organizations and governments. There is growing concern about how public and private organizations use their personal information, and only those organizations that do not actively address these issues will continue to raise objections.
“Any discussion about privacy must be based on a broader digital ethics theme and the trust of customers, voters, and employees. While privacy and security are fundamental components of trust building, trust is more than just these components. "Mr. Cearley said. “Trust refers to the truthfulness of accepting a statement without evidence or investigation. Ultimately, the organization’s position on privacy must be driven by its broader position on ethics and trust. From privacy to ethics, the conversation goes beyond” Whether we are compliant or not, we turn to the 'what we are doing is the right thing.'"
As governments increasingly plan or pass regulations that companies must comply with, consumers are carefully protecting or deleting information about themselves. Companies must acquire and maintain trust with their customers to succeed, and they must also follow internal values to ensure that they see them as trusted partners.
10. Quantum computing
Quantum Computation (QC) is a non-classical calculation based on the quantum states of subatomic particles (eg, electrons and ions) that represent information as elements of quantum bits (qubits).
For example, although a classic computer reads each book in the library in a linear fashion, the quantum computer reads all the books at the same time. Quantum computers can theoretically process millions of calculations simultaneously. Quantum computing, which is commercially available, affordable, and reliable, will change an industry.
The parallel execution and exponential scalability of quantum computers means that they are superior to traditional methods that are too complex, or traditional algorithms take a long time to find a solution. Industries such as automotive, finance, insurance, pharmaceuticals, military and research institutions have benefited the most from advances in quality control.
For example, in the pharmaceutical industry, quantum computing can be used to simulate molecular interactions at the atomic level to speed up the market for new cancer therapeutics, or quantum computing can accelerate and more accurately predict protein interactions, resulting in new pharmaceutical methods. .
The application range of quantum computing in the real world has gone from a wide range of phenomena, from personalized medicine to image recognition optimization. The technology is still in an emerging state, which means it is now a good time for companies to increase their understanding of potential applications and consider any security risks.
“CIOs and IT leaders should begin to plan quality control by increasing understanding and how to apply them to real business problems. When technology is still in an emerging state, it begins to engage in learning. Determine which quantum computing has the potential to go. Solve real-world problems and consider the possible impact on security,” Mr. Cearley said. "But at the same time, don't expect it to change something completely in the next few years. Most organizations should understand and monitor the application of quantum computing by 2022 and may need to start using it in 2023 or 2025."
About Gartner Symposium/ITxpo
Gartner Symposium/ITxpo is the world's most important gathering of CIOs and senior IT leaders, bringing together the global CIO community with tools and strategies to help them lead the next generation of IT and achieve business results. With more than 25,000 CIOs around the world, senior business and IT leaders will come together to gain the insight they need to ensure their IT initiatives will be key contributors and enablers for their business success.
