Although science
fiction may depict AI robots as the bad guys, some tech giants now employ them
for security. Companies like Microsoft and Uber use Knightscope K5 robots to
patrol parking lots and large outdoor areas to predict and prevent crime. The robots can read license plates, report
suspicious activity and collect data to report to their owners.
These AI-driven robots
are just one example of “autonomous things,” one of the Gartner Top 10
strategic technologies for 2019 with the potential to drive significant
disruption and deliver opportunity over the next five years.
“The future will be
characterized by smart devices delivering increasingly insightful digital
services everywhere,” said David Cearley, Gartner Distinguished Vice
President Analyst, at Gartner 2018 Symposium/ITxpo in Orlando,
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.
- Robotics
- Vehicles
- Drones
- Appliances
- Agents
- 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.
- 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.
- 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 robustness of the models, with a focus on how they support specific business outcomes
- The link to the real world, potentially in real time for monitoring and control
- The application of advanced big data analytics and AI to drive new business opportunities
- The ability to interact with them and evaluate “what if” scenarios
“Trends under each of
these three themes are a key ingredient in driving a continuous innovation
process as part of the continuous next strategy,” Cearley said.
The Gartner Top 10
Strategic Technology trends highlight changing or not yet widely recognized
trends that will impact and transform industries through 2023.
Trend No. 1: Autonomous things
Whether it’s cars, robots or
agriculture, autonomous things use AI to perform tasks traditionally done by
humans. The sophistication of the intelligence varies, but all autonomous
things use AI to interact more naturally with their environments.
Autonomous things
exist across five types:
Those five types
occupy four environments: Sea, land, air and digital. They all operate with
varying degrees of capability, coordination and intelligence. For example, they
can span a drone operated in the air with human-assistance to a farming robot
operating completely autonomously in a field. This paints a broad picture of
potential applications, and virtually every application, service and IoT object
will incorporate some form of AI to automate or augment processes or human
actions. Collaborative autonomous things such as drone swarms will
increasingly drive the future of AI systems
Explore the
possibilities of AI-driven autonomous capabilities in any physical object in
your organization or customer environment, but keep in mind these devices are
best used for narrowly defined purposes. They do not have the same capability
as a human brain for decision making, intelligence or general-purpose learning.
Trend No. 2: Augmented analytics
Data scientists now
have increasing amounts of data to prepare, analyze and group — and from which
to draw conclusions. Given the amount of data, exploring all possibilities
becomes impossible. This means businesses can miss key insights from hypotheses
the data scientists don’t have the capacity to explore.
Augmented analytics
represents a third major wave for data and analytics capabilities as data
scientists use automated algorithms to explore more hypotheses. Data science
and machine learning platforms have transformed how businesses generate
analytics insight.
“By 2020, more than
40% of data science tasks will be automated”
Augmented analytics
identify hidden patterns while removing the personal bias. Although businesses
run the risk of unintentionally inserting bias into the algorithms, augmented
analytics and automated insights will eventually be embedded into enterprise
applications.
Through 2020, the
number of citizen data scientists will grow five times faster than professional
data scientists. Citizen data scientists use AI powered augmented analytics
tools that automate the data science function automatically identifying data
sets, developing hypothesis and identifying patterns in the data. Businesses
will look to citizen data scientists as a way to enable and scale data science
capabilities. Gartner predicts by 2020, more than 40% of data science tasks
will be automated, resulting in increased productivity and broader use by
citizen data scientists. Between citizen data scientists and augmented analytics,
data insights will be more broadly available across the business, including
analysts, decision makers and operational workers.
Trend No. 3: AI-driven development
AI-driven development
looks at tools, technologies and best practices for embedding AI into
applications development and using AI to create AI-powered tools for the development process.
This trend is evolving along three dimensions:
The market will shift
from a focus on data scientists partnered with developers to developers
operating independently using predefined models delivered as a service. This
enables more developers to utilize the services, and increases efficiency.
These trends are also leading to more mainstream usage of virtual software developers and nonprofessional “citizen application developers.”
Trend No. 4: Digital
twins
A 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 larger systems, 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 online profiles of
customers, but today’s digital twins are different in four ways:
The focus today is
on digital twins in the IoT,
which could improve enterprise decision making by providing information on
maintenance and reliability, insight into how a product could perform more
effectively, data about new products and increased efficiency. Digital
twins of an organization are emerging to create models of organizational
process to enable real time monitoring and drive improved process efficiencies.
Trend No. 5: Empowered edge
Edge computing is a
topology where information processing and content collection and delivery are
placed closer to the sources of the information, with the idea that keeping
traffic local will reduce latency. Currently, much of the focus of this
technology is a result of the need for IoT systems to deliver disconnected or
distributed capabilities into the embedded IoT world. This type of topology
will address challenges ranging from high WAN costs and unacceptable levels of
latency. Further, it will enable the specifics of digital business and IT
solutions.
“Technology and
thinking will shift to a point where the experience will connect people with
hundreds of edge devices”
Through 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, from industrial devices to
screens to smartphones to automobile power generators.
Trend No. 6: Immersive technologies
Through 2028,
conversational platforms, which change how users interact with the world, and
technologies such as augmented reality (AR), mixed reality (MR) and virtual
reality (VR), which change how users perceive the world, will lead to a new
immersive experience. AR, MR and VR show potential for
increased productivity, with the next generation of VR able to sense shapes and
track a user’s position and MR enabling people to view and interact with their
world.
By 2022, 70% of
enterprises will be experimenting with immersive technologies for
consumer and enterprise use, and 25% will have deployed to production. The
future of conversational platforms, which range from virtual personal
assistants to chatbots, will incorporate expanded sensory channels that will
allow the platform to detect emotions based on facial expressions, and they
will become more conversational in interactions.
Eventually, the
technology and thinking will shift to a point where the experience will connect
people with hundreds of edge devices ranging from computers to cars.
Trend No. 7: Blockchain
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. Blockchain allows companies to trace a transaction
and work with untrusted parties without the need for a centralized party (i.e.,
a bank). This greatly reduces business friction and has applications that began
in finance, but have
expanded to government, healthcare,
manufacturing, supply chain and
others. Blockchain could potentially lower costs, reduce transaction settlement
times and improve cash flow. The technology has also given way to a host of
blockchain-inspired solutions that utilize some of the benefits and parts 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 not implement all
the tenets of blockchain deliver near term value but do not provide the
promised highly distributed decentralized consensus models of a pure
blockchain.
Trend No. 8: 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. As technology becomes a more integrated part of daily life, smart
spaces will enter a period of accelerated delivery. Further, other trends such
as AI-driven technology, edge computing, blockchain and digital twins are
driving toward this trend as individual solutions become smart spaces.
Smart spaces are
evolving alone five key dimensions: Openness, connectedness, coordination,
intelligence and scope. Essentially, smart spaces are developing as individual
technologies emerge from silos to work together to create a collaborative and
interaction environment. The most extensive example of smart spaces is smart cities, where
areas that combine business, residential and industrial communities are being
designed using intelligent urban ecosystem frameworks, with all sectors linking
to social and community collaboration.
Trend No. 9: Digital ethics and privacy
Consumers have an
growing awareness of the value of their personal information, and they are
increasingly concerned with how it’s being used by public and private entities.
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?”
Governments are
increasingly planning or passing regulations with which companies must be
compliant, and consumers are carefully guarding or removing information about
themselves. Companies must gain and maintain trust with the customer to
succeed, and they must also follow internal values to ensure customers view
them as trustworthy.
Trend No. 10: Quantum computing
Quantum computing is a
type of nonclassical computing that is based on the quantum state of subatomic
particles that represent information as elements denoted as quantum bits or
“qubits.”
Quantum computers are
an exponentially scalable and highly parallel computing model. A way to
imagine the difference between traditional and quantum computers is to imagine
a giant library of books.
While a classic
computer would read every book in a library in a linear fashion, a quantum
computer would read all the books simultaneously. Quantum computers are able to
theoretically work on millions of computations at once. Quantum computing in
the form of a commercially available, affordable and reliable service would
transform some industries.
Real-world
applications range from personalized medicine to optimization of pattern
recognition. This technology is still in an emerging state, which means it is a
good time for businesses to increase their understanding of potential
applications and consider any security implications. Aside from a select group
of businesses where specific quantum algorithms would provide a major
advantage, most enterprises could remain in exploration phase through 2022
and begin exploiting the technology later.
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