Gartner, a trusted advisor and an objective resource for more than 15,000 organisations in 100+ countries, helps organisations gain the insights, advice and tools to achieve mission-critical priorities. This October, analysts explored top industry trends at the Gartner Symposium/ ITxpo 2018, in Orlando. Considered the world's most important gathering of CIOs and senior IT leaders, it unites a global community of CIOs with the tools and strategies to help them lead the next generation of IT and achieve business outcomes. The top strategic technology trends that organisations need to explore in the coming year were highlighted by Gartner, Inc. with analysts presenting their findings at the symposium.
WHAT IS A STRATEGIC TECHNOLOGY TREND?
As defined by Gartner, a strategic technology trend is one with substantial disruptive potential, which is starting to break out of an emerging state into broader impact and use. Also falling in this category are swiftly growing trends with a high degree of volatility reaching tipping points over the next five years.David Cearley, Vice President and Gartner Fellow had stated that the Intelligent Digital Mesh has been a consistent theme for the past two years and continues to be a major driver through 2019. He illustrated the same by explaining how Artificial Intelligence (AI) in the form of automated things and augmented intelligence is being used together with IoT, edge computing and digital twins to deliver highly integrated smart spaces. Cearley pointed out that combinatorial effect of multiple trends coalescing to produce new opportunities and drive new disruption is a hallmark of the Gartner top 10 strategic technology trends for 2019.For 2019, the following are the top 10 strategic technology trends as announced by Gartner…
The scope of automation has surged tremendously to grow beyond the automation provided by limited programming models. Now autonomous things, such as robots, drones and autonomous vehicles, use and exploit AI to automate functions previously performed by humans. They deliver advanced behaviours that interact more naturally with their surroundings and with people. As Cearley maintained, as autonomous things proliferate, a shift can be expected from standalone intelligent things to a swarm of collaborative intelligent things, with multiple devices working together, either independently of people or with human input. For instance, if a drone examined a large field and found that it was ready for harvesting, it could dispatch an “autonomous harvester.” Another example, in the delivery market, would be the use of an autonomous vehicle to move packages to the target area. Robots and drones on board the vehicle could ensure final delivery of the package.
This trend focuses on a specific area of augmented intelligence, whereby machine learning (ML) is used to transform how analytics content is developed, consumed and shared. It will not be long before Augmented Analytics capabilities will be adopted in the mainstream, as a key feature of data preparation, data management, modern analytics, business process management, process mining and data science platforms. The automated insights gleaned from augmented analytics will also be embedded in enterprise applications, in the departments of HR, finance, sales, marketing, customer service, procurement and asset management departments. This will help optimise the decisions and actions of all employees within their context. Augmented analytics automates the process of data preparation, insight generation and insight visualisation, even as it eliminates the need for professional data scientists in many situations.It is estimated that through 2020, there will be the emergence of citizen data science which will enable users, whose main job is outside the field of statistics and analytics, to extract predictive and prescriptive insights from data. Citizen data scientists will be used in organisations to fill the data science and machine learning talent gap caused by the shortage and high cost of data scientists.
DevelopmentIn the current times, a scenario is emerging wherein the professional developer operates alone to create AI-enhanced solutions using predefined models delivered as a service, as opposed to professional data scientists partnering with application developers. The developer is provided with an ecosystem of AI algorithms and models, including development tools which are meant to integrate AI capabilities and models into a solution. As AI is applied to the development process to automate different data science, application development and testing functions, a new level of opportunity for professional application development emerges. It is estimated that by the year 2022, no less than 40 percent of new application development projects will have AI co-developers on their team. Eventually, AI-powered development environments will see the emergence of citizen application development where non-professionals will use AI-driven tools to automatically generate new solutions minus coding and with greater flexibility.
Defined as a digital representation of a real-world entity or system, it is estimated that by 2020, there will be more than 20 billion connected sensors and endpoints. Digital twins will potentially exist for billions of things. While organisations will implement digital twins simply at first, they will evolve, improving their ability to collect and visualise the right data, apply the right analytics and rules, and respond effectively to business objectives. Enterprises will implement digital twins of their organisations, DTOs which are dynamic software models which rely on operational or other data to understand how an organisation operationalises its business model, connects with its current state, deploys resources and responds to changes to deliver expected customer value. Cearley pointed out that DTOs help drive efficiencies in business processes, as well as create more flexible, dynamic and responsive processes that can potentially react to changing conditions automatically.
Endpoint devices used by people or embedded in the world around us are classified as the edge. Edge computing describes a computing topology in which information processing, and content collection and delivery, are placed closer to these endpoints. It tries to keep the traffic and processing local, with the goal being to reduce traffic and latency. In the short term, the edge is driven by IoT and the need to keep the processing close to the end rather than on a centralized cloud server. In time cloud computing and edge computing will evolve as complementary models with cloud services being managed as a centralised service executing, not only on centralized servers, but in distributed servers on-premises and on the edge devices themselves. As 5G matures, the expanding edge computing environment will have more robust communication back to centralised services, leading to a dramatic increase in the number of nodes (edge endpoints) per square km.
Virtual reality (VR), augmented reality (AR) and mixed reality (MR) are changing the way in which people perceive the digital world. The combined shift in perception and interaction models leads to the future immersive user experience. With time, the shift will occur from thinking about individual devices and fragmented user interface (UI) technologies to a multichannel and multimodal experience. According to Cearley, the multimodal experience will connect people with the digital world across hundreds of edge devices that surround them, including traditional computing devices, wearables, automobiles, environmental sensors and consumer appliances. The multichannel experience will use all human senses as well as advanced computer senses (such as heat, humidity and radar) across these multimodal devices. An ambient experience will be created in which the spaces that surround us define ‘the computer’ rather than the individual devices.
A type of distributed ledger, Blockchain has the potential to reshape industries by enabling trust, providing transparency and reducing friction across business ecosystems. Thus, it will potentially lower costs, reduce transaction settlement times and improve cash flow. Today, trust is placed in banks, clearinghouses, governments and many other institutions as central authorities with the ‘single version of the truth’ maintained securely in their databases. However, this centralised trust model adds delays and friction costs (commissions, fees and the time value of money) to transactions. Blockchain, on the other hand, provides an alternative trust mode and removes the need for central authorities in arbitrating transactions. Blockchain-inspired solutions can help achieve operational efficiency by automating business processes, or by digitising records. They have the potential to enhance sharing of information among known entities and improve opportunities for tracking and tracing physical and digital assets. SMART SPACES A physical or digital environment in which humans and technology-enabled systems interact in increasingly open, connected, coordinated and intelligent ecosystems is defined as a smart space. It sees multiple elements including people, processes, services and things coming together to create a more immersive, interactive and automated experience for a target set of people and industry scenarios. According to Cearley, the trend has been coalescing for some time around elements such as smart cities, digital workplaces, smart homes and connected factories. He maintained that the market is entering a period of accelerated delivery of robust smart spaces with technology becoming an integral part of daily life, whether as employees, customers, consumers, community members or citizens.
DIGITAL ETHICS AND PRIVACY
This is a matter of growing concern for individuals, organisations and governments. There are increasing fears about how people’s personal information is being used by organisations in both the public and private sector. It is highly crucial that organisations proactively address these concerns. Cearley maintained that any discussion on privacy must be grounded in the broader topic of digital ethics and the trust of customers, constituents and employees. He pointed out that while privacy and security are foundational components in building trust, trust is actually about more than just these components – it is the acceptance of the truth of a statement without evidence or investigation. Thus, it is important that an organisation’s position on privacy be driven by its broader position on ethics and trust.
A type of nonclassical computing, it operates on the quantum state of subatomic particles (for example, electrons and ions) that represent information as elements denoted as quantum bits (qubits). The parallel execution and exponential scalability of quantum computers means they excel with problems too complex for a traditional approach or where a traditional algorithm would take too long to find a solution. Industries such as automotive, financial, insurance, pharmaceuticals, military and research organisations have the most to gain from the advancements in QC. Cearley advises that CIOs and IT leaders should start planning for QC by increasing understanding and how it can apply to real-world business problems. Learn while the technology is still in the emerging state, he recommends, adding that real-world problems where QC has potential should be identified and the possible impact on security considered. However, he believes that the revolution is not around the corner – while most organisations should learn about and monitor QC through 2022, it would probably be exploited from 2023 or 2025.
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