Analysts Explore Top Industry Trends at
Gartner Symposium/ITxpo 2018, October 14-18 in Orlando
Gartner, Inc. today highlighted the top strategic technology
trends that organizations need to explore in 2019. Analysts
presented their findings during Gartner Symposium/ITxpo, which is
taking place here through Thursday.
Gartner defines a strategic technology trend as one with
substantial disruptive potential that is beginning to break out of
an emerging state into broader impact and use, or which are rapidly
growing trends with a high degree of volatility reaching tipping
points over the next five years.
“The Intelligent Digital Mesh has been a consistent theme for
the past two years and continues as a major driver through 2019.
Trends under each of these three themes are a key ingredient in
driving a continuous innovation process as part of a ContinuousNEXT
strategy,” said David Cearley, vice president and Gartner Fellow.
“For example, 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. This 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.”
The top 10 strategic technology trends for 2019 are:
Autonomous Things
Autonomous things, such as robots, drones and autonomous
vehicles, use AI to automate functions previously performed by
humans. Their automation goes beyond the automation provided by
rigid programing models and they exploit AI to deliver advanced
behaviors that interact more naturally with their surroundings and
with people.
“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,” said Mr. Cearley.
“For example, if a drone examined a large field and found that it
was ready for harvesting, it could dispatch an “autonomous
harvester.” Or in the delivery market, the most effective solution
may be to use an autonomous vehicle to move packages to the target
area. Robots and drones on board the vehicle could then ensure
final delivery of the package.”
Augmented Analytics
Augmented analytics focuses on a specific area of augmented
intelligence, using machine learning (ML) to transform how
analytics content is developed, consumed and shared. Augmented
analytics capabilities will advance rapidly to mainstream adoption,
as a key feature of data preparation, data management, modern
analytics, business process management, process mining and data
science platforms. Automated insights from augmented analytics will
also be embedded in enterprise applications — for example, those of
the HR, finance, sales, marketing, customer service, procurement
and asset management departments — to optimize the decisions and
actions of all employees within their context, not just those of
analysts and data scientists. Augmented analytics automates the
process of data preparation, insight generation and insight
visualization, eliminating the need for professional data
scientists in many situations.
“This will lead to citizen data science, an emerging set of
capabilities and practices that enables users whose main job is
outside the field of statistics and analytics to extract predictive
and prescriptive insights from data,” said Mr. Cearley. “Through
2020, the number of citizen data scientists will grow five times
faster than the number of expert data scientists. Organizations can
use citizen data scientists to fill the data science and machine
learning talent gap caused by the shortage and high cost of data
scientists.”
AI-Driven Development
The market is rapidly shifting from an approach in which
professional data scientists must partner with application
developers to create most AI-enhanced solutions to a model in which
the professional developer can operate alone using predefined
models delivered as a service. This provides the developer with an
ecosystem of AI algorithms and models, as well as development tools
tailored to integrating AI capabilities and models into a solution.
Another level of opportunity for professional application
development arises as AI is applied to the development process
itself to automate various data science, application development
and testing functions. By 2022, at least 40 percent of new
application development projects will have AI co-developers on
their team.
“Ultimately, highly advanced AI-powered development environments
automating both functional and nonfunctional aspects of
applications will give rise to a new age of the ‘citizen
application developer’ where nonprofessionals will be able to use
AI-driven tools to automatically generate new solutions. Tools that
enable nonprofessionals to generate applications without coding are
not new, but we expect that AI-powered systems will drive a new
level of flexibility,” said Mr. Cearley.
Digital Twins
A digital twin refers to the digital representation of a
real-world entity or system. By 2020, Gartner estimates there will
be more than 20 billion connected sensors and endpoints and digital
twins will exist for potentially billions of things. Organizations
will implement digital twins simply at first. They will evolve them
over time, improving their ability to collect and visualize the
right data, apply the right analytics and rules, and respond
effectively to business objectives.
“One aspect of the digital twin evolution that moves beyond IoT
will be enterprises implementing digital twins of their
organizations (DTOs). A DTO is a dynamic software model that relies
on operational or other data to understand how an organization
operationalizes its business model, connects with its current
state, deploys resources and responds to changes to deliver
expected customer value,” said Mr. Cearley. “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.”
Empowered Edge
The edge refers to endpoint devices used by people or embedded
in the world around us. 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 near term, edge is being driven by IoT and the need keep
the processing close to the end rather than on a centralized cloud
server. However, rather than create a new architecture, cloud
computing and edge computing will evolve as complementary models
with cloud services being managed as a centralized service
executing, not only on centralized servers, but in distributed
servers on-premises and on the edge devices themselves.
Over the next five years, specialized AI chips, along with
greater processing power, storage and other advanced capabilities,
will be added to a wider array of edge devices. The extreme
heterogeneity of this embedded IoT world and the long life cycles
of assets such as industrial systems will create significant
management challenges. Longer term, as 5G matures, the expanding
edge computing environment will have more robust communication back
to centralized services. 5G provides lower latency, higher
bandwidth, and (very importantly for edge) a dramatic increase in
the number of nodes (edge endoints) per square km.
Immersive Experience
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
perception and interaction models leads to the future immersive
user experience.
“Over time, we will shift from thinking about individual devices
and fragmented user interface (UI) technologies to a multichannel
and multimodal experience. 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,” said
Mr. Cearley. “The multichannel experience will use all human senses
as well as advanced computer senses (such as heat, humidity and
radar) across these multimodal devices. This multiexperience
environment will create an ambient experience in which the spaces
that surround us define “the computer” rather than the individual
devices. In effect, the environment is the computer.”
Blockchain
Blockchain, a type of distributed ledger, promises to reshape
industries by enabling trust, providing transparency and reducing
friction across business ecosystems potentially lowering costs,
reducing transaction settlement times and improving 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. The
centralized trust model adds delays and friction costs
(commissions, fees and the time value of money) to transactions.
Blockchain provides an alternative trust mode and removes the need
for central authorities in arbitrating transactions.
”Current blockchain technologies and concepts are immature,
poorly understood and unproven in mission-critical, at-scale
business operations. This is particularly so with the complex
elements that support more sophisticated scenarios,” said Mr.
Cearley. “Despite the challenges, the significant potential for
disruption means CIOs and IT leaders should begin evaluating
blockchain, even if they don’t aggressively adopt the technologies
in the next few years.”
Many blockchain initiatives today do not implement all of the
attributes of blockchain — for example, a highly distributed
database. These blockchain-inspired solutions are positioned as a
means to achieve operational efficiency by automating business
processes, or by digitizing records. They have the potential to
enhance sharing of information among known entities, as well as
improving opportunities for tracking and tracing physical and
digital assets. However, these approaches miss the value of true
blockchain disruption and may increase vendor lock-in.
Organizations choosing this option should understand the
limitations and be prepared to move to complete blockchain
solutions over time and that the same outcomes may be achieved with
more efficient and tuned use of existing nonblockchain
technologies.
Smart Spaces
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. Multiple
elements — including people, processes, services and things — come
together in a smart space to create a more immersive, interactive
and automated experience for a target set of people and industry
scenarios.
“This trend has been coalescing for some time around elements
such as smart cities, digital workplaces, smart homes and connected
factories. We believe the market is entering a period of
accelerated delivery of robust smart spaces with technology
becoming an integral part of our daily lives, whether as employees,
customers, consumers, community members or citizens,” said Mr.
Cearley.
Digital Ethics and Privacy
Digital ethics and privacy is a growing concern for individuals,
organizations and governments. People are increasingly concerned
about how their personal information is being used by organizations
in both the public and private sector, and the backlash will only
increase for organizations that are not proactively addressing
these concerns.
“Any discussion on privacy must be grounded in the broader topic
of digital ethics and the trust of your customers, constituents and
employees. While privacy and security are foundational components
in building trust, trust is actually about more than just these
components,” said Mr. Cearley. “Trust is the acceptance of the
truth of a statement without evidence or investigation. Ultimately
an organization’s position on privacy must be driven by its broader
position on ethics and trust. Shifting from privacy to ethics moves
the conversation beyond ‘are we compliant’ toward ‘are we doing the
right thing.’”
Quantum Computing
Quantum computing (QC) is a type of nonclassical computing that
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
algorithms would take too long to find a solution. Industries such
as automotive, financial, insurance, pharmaceuticals, military and
research organizations have the most to gain from the advancements
in QC. In the pharmaceutical industry, for example, QC could be
used to model molecular interactions at atomic levels to accelerate
time to market for new cancer-treating drugs or QC could accelerate
and more accurately predict the interaction of proteins leading to
new pharmaceutical methodologies.
“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. Identify
real-world problems where QC has potential and consider the
possible impact on security,” said Mr. Cearley. “But don’t believe
the hype that it will revolutionize things in the next few years.
Most organizations should learn about and monitor QC through 2022
and perhaps exploit it from 2023 or 2025.”
Gartner clients can learn more in the Gartner Special Report
“Top 10 Strategic Technology Trends for 2019.” Additional detailed
analysis on each tech trend can be found in the Gartner YouTube
video “Gartner Top 10 Strategic Technology Trends 2019.”
About Gartner Symposium/ITxpo
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