Trend No 1. Hyperautomation
Automation uses technology to automate tasks that once
required humans.
Hyperautomation deals with the application of advanced
technologies, including artificial intelligence (AI) and machine learning (ML),
to increasingly automate processes and augment humans. Hyperautomation extends across
a range of tools that can be automated, but also refers to the sophistication
of the automation (i.e., discover, analyze, design, automate, measure, monitor,
reassess.)
Hyperautomation often results in the creation of a digital
twin of the organization
As no single tool can replace humans, hyper-automation today
involves a combination of tools, including robotic process automation (RPA),
intelligent business management software (iBPMS) and AI, with a goal of
increasingly AI-driven decision making.
Although not the main goal, hyper-automation often results in
the creation of a digital twin of the organization (DTO), allowing
organizations to visualize how functions, processes and key performance
indicators interact to drive value. The DTO then becomes an integral part of
the hyper-automation process, providing real-time, continuous intelligence about
the organization and driving significant business opportunities.
Trend No. 2: Multiexperience
Multi experience replaces technology-literate people with people-literate
technology. In this trend, the traditional idea of a computer evolves from a
single point of interaction to include multisensory and multi-touchpoint
interfaces like wearables and advanced computer sensors.
For example, Domino’s Pizza created an experience beyond
app-based ordering that includes autonomous vehicles, a pizza tracker and smart
speaker communications.
In the future, this trend will become what’s called an
ambient experience, but currently multi-experience focuses on immersive experiences
that use augmented reality (AR), virtual (VR), mixed reality, multichannel
human-machine interfaces and sensing technologies. The combination of these
technologies can be used for a simple AR overlay or a fully immersive VR
experience.
Brian Burke, Gartner Research VP breaks down the Gartner Top
10 Strategic Technology Trends for 2020 at Gartner 2019 IT Symposium/Xpo™ in
Orlando, Florida.
Brian Burke, Gartner Research VP, breaks down the Gartner
Top 10 Strategic Technology Trends for 2020 during Gartner 2019 IT
Symposium/Xpo™ in Orlando, Florida.
Trend No. 3: Democratization
The democratization of technology means providing people with
easy access to technical or business expertise without extensive (and costly)
training. It focuses on four key areas — application development, data and
analytics, design and knowledge — and is often referred to as “citizen access,”
which has led to the rise of citizen data scientists, citizen programmers and
more.
For example, democratization would enable developers to
generate data models without having the skills of a data scientist. They would
instead rely on AI-driven development to generate code and automate testing.
Trend No. 4: Human augmentation
Human augmentation is the use of technology to enhance a
person’s cognitive and physical experiences.
Physical augmentation changes an inherent physical
capability by implanting or hosting a technology within or on the body. For
example, the automotive or mining industries use wearables to improve worker
safety. In other industries, such as retail and travel, wearables are used to
increase worker productivity.
Physical augmentation falls into four main categories:
Sensory augmentation (hearing, vision, perception), appendage and biological
function augmentation (exoskeletons, prosthetics), brain augmentation (implants
to treat seizures) and genetic augmentation (somatic gene and cell therapy).
AI and ML are increasingly used to make decisions in place of
humans
Cognitive augmentation enhances a human’s ability to think
and make better decisions, for example, exploiting information and applications
to enhance learning or new experiences. Cognitive augmentation also includes
some technology in the brain augmentation category as they are physical
implants that deal with cognitive reasoning.
Human augmentation carries a range of cultural and ethical
implications. For example, using CRISPR technologies to augment genes has
significant ethical implications.
Trend No. 5: Transparency and traceability
The evolution of technology is creating a trust crisis. As
consumers become more aware of how their data is being collected and used,
organizations are also recognizing the increasing liability of storing and gathering
the data.
Additionally, AI and ML are increasingly used to make
decisions in place of humans, evolving the trust crisis and driving the need
for ideas like explainable AI and AI governance.
This trend requires a focus on six key elements of trust:
Ethics, integrity, openness, accountability, competence, and consistency.
Legislation, like the European Union’s General Data
Protection Regulation (GDPR), is being enacted around the world, driving
evolution and laying the ground rules for organizations.
Trend No. 6: The 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 and distributed will
reduce latency. This includes all the technology on the Internet of Things
(IoT). Empowered edge looks at how these devices are increasing and forming the
foundations for smart spaces, and moves key applications and services closer to
the people and devices that use them.
By 2023, there could be more than 20 times as many smart
devices at the edge of the network as in conventional IT roles.
Trend No. 7: The distributed cloud
The distributed cloud refers to the distribution of public cloud
services to locations outside the cloud provider’s physical data centers, but
which are still controlled by the provider. In a distributed cloud, the cloud
provider is responsible for all aspects of cloud service architecture,
delivery, operations, governance, and updates. The evolution from centralized
public cloud to distributed public cloud ushers in a new era of cloud
computing.
The distributed cloud allows data centers to be located
anywhere. This solves both technical issues like latency and also regulatory
challenges like data sovereignty. It also offers the benefits of a public cloud
service alongside the benefits of a private, local cloud.
Trend No. 8: Autonomous things
Autonomous things, which include drones, robots, ships and
appliances, exploit AI to perform tasks usually done by humans. This technology
operates on a spectrum of intelligence ranging from semiautonomous to fully
autonomous and across a variety of environments including air, sea, and land.
While currently autonomous things mainly exist in controlled
environments, like in a mine or warehouse, they will eventually evolve to
include open public spaces. Autonomous things will also move from stand-alone
to collaborative swarms, such as the drone swarms used during the Winter
Olympic Games in 2018.
However, autonomous things cannot replace the human brain
and operate most effectively with a narrowly defined, well-scoped purpose.
Read more: Human Beings, AI and Robotics Represent the New
Workforce in 2028
Trend No. 9: Practical blockchain
Blockchain is a type of distributed ledger, an expanding the chronologically ordered list of cryptographically signed, irrevocable
transactional records shared by all participants in a network.
Blockchain also allows parties to trace assets back to their
origin, which is beneficial for traditional assets, but also paves the way for
other uses such as tracing food-borne illnesses back to the original supplier.
It also allows two or more parties who don’t know each other to safely interact
in a digital environment and exchange value without the need for a centralized
authority.
The complete blockchain model includes five elements: A
shared and distributed ledger, immutable and traceable ledger, encryption,
tokenization and a distributed public consensus mechanism. However, blockchain
remains immature for enterprise deployments due to a range of technical issues
including poor scalability and interoperability.
Blockchain, which is already appearing in experimental and
small-scope projects will be fully scalable by 2023
Enterprise blockchains today take a practical approach and
implement only some of the elements of a complete blockchain by making the
ledger independent of individual applications and participants and replicating
the ledger across a distributed network to create an authoritative record of
significant events. Everyone with permission access sees the same
information and integration is simplified by having a single shared
blockchain. The consensus is handled through more traditional private models.
Read more: The 4 Phases of the Gartner Blockchain Spectrum
Digital Business
The Real Business of Blockchain
How leaders can create value in a new digital age.
In the future, true blockchain or “blockchain complete” will
have the potential to transform industries, and eventually, the economy, as
complementary technologies such as AI and the IoT begin to integrate alongside
blockchain. This expands the type of participants to include machines, which
will be able to exchange a variety of assets — from money to real estate. For
example, a car would be able to negotiate insurance prices directly with the
insurance company based on data gathered by its sensors.
Blockchain, which is already appearing in experimental and
small-scope projects will be fully scalable by 2023.
Trend No. 10: AI security
Evolving technologies such as hyper automation and autonomous
things offer transformational opportunities in the business world. However,
they also create security vulnerabilities in new potential points of attack.
Security teams must address these challenges and be aware of how AI will impact
the security space.
AI security has three key perspectives:
Protecting AI-powered systems: Securing AI training data,
training pipelines and ML models.
Leveraging AI to enhance security defense: Using ML to
understand patterns, uncover attacks and automate parts of the cybersecurity
processes.
Anticipating nefarious use of AI by attackers: Identifying
attacks and defending against them.
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