Gartner Eyes Top Strategic Technology Trends for 2022
October 19, 2021
noted the top strategic technology trends that organizations need to
explore in 2022. Analysts presented their findings during Gartner IT
Symposium/Xpo Americas, which is taking place virtually through
“With CEOs and Boards striving to find growth through direct digital
connections with customers, CIOs’ priorities must reflect the same
business imperatives, which run through each of Gartner’s top strategic
tech trends for 2022,” said
David Groombridge, research vice president at Gartner.
“CIOs must find the IT force multipliers to enable growth and
innovation, and create scalable, resilient technical foundations whose
scalability will free cash for digital investments. These imperatives
form the three themes of this year’s trends: engineering trust,
sculpting change and accelerating growth.”
The top strategic technology trends for 2022 are:
Generative Artificial Intelligence (AI)
One of the most visible and powerful AI techniques coming to market is
generative AI – machine learning methods that learn about content or
objects from their data, and use it to generate brand-new, completely
original, realistic artifacts.
Generative AI can be used for a range of activities such as creating
software code, facilitating drug development and targeted marketing, but
also misused for scams, fraud, political disinformation, forged
identities and more. By 2025, Gartner expects generative AI to account
for 10% of all data produced, up from less than 1% today.
The number of data and application silos has surged in the last decade,
while the number of skilled personnel in data and analytics (D&A) teams
has either stayed constant or even dropped. Data fabrics – a flexible,
resilient integration of data across platforms and business users – have
emerged to simplify an organization’s data integration infrastructure
and create a scalable architecture that reduces the technical debt seen
in most D&A teams due to the rising integration challenges.
A data fabric’s real value is its ability to dynamically improve data
usage with its inbuilt analytics, cutting data management efforts by up
to 70% and accelerating time to value.
With the rise in remote and hybrid working patterns, traditional
office-centric organizations are evolving into distributed enterprises
comprised of geographically dispersed workers.
“This requires CIOs to make major technical and service changes to
deliver frictionless work experiences, but there is another side to this
coin: the impact on business models,” said Groombridge. “For every
organization, from retail to education, their delivery model has to be
reconfigured to embrace distributed services. The world didn’t think
they’d be trying on clothes in a digital dressing room two years ago.”
Gartner expects that by 2023, 75% of organizations that exploit
distributed enterprise benefits will realize revenue growth 25% faster
Cloud-Native Platforms (CNPs)
To truly deliver digital capabilities anywhere and everywhere,
enterprises must turn away from the familiar “lift and shift” migrations
and toward CNPs. CNPs use the core capabilities of cloud computing to
provide scalable and elastic IT-related capabilities “as a service” to
technology creators using internet technologies, delivering faster time
to value and reduced costs.
For this reason, Gartner predicts that cloud-native platforms will serve
as the foundation for more than 95% of new digital initiatives by 2025 —
up from less than 40% in 2021.
As enterprises grow, traditional programming or simple automation will
not scale. Autonomic systems are self-managing physical or software
systems that learn from their environments. Unlike automated or even
autonomous systems, autonomic systems can dynamically modify their own
algorithms without an external software update, enabling them to rapidly
adapt to new conditions in the field, much like humans can.
“Autonomic behavior has already made itself known through recent
deployments in complex security environments, but in the longer term,
will become common in physical systems such as robots, drones,
manufacturing machines and smart spaces,” said Groombridge.
Decision Intelligence (DI)
An organization’s decision-making competency can be a significant source
of competitive advantage, but it’s becoming more demanding.
Decision intelligence is a practical discipline used to improve decision
making by explicitly understanding and engineering how decisions are
made, and outcomes evaluated, managed and improved by feedback. Gartner
predicts that in the next two years, a third of large organizations will
be using decision intelligence for structured decision-making, to
improve competitive advantage.
In the continuously changing business context, demand for business
adaptability directs organizations toward technology architecture that
supports fast, safe and efficient application change. Composable
application architecture empowers such adaptability, and those that have
adopted a composable approach will outpace competition by 80% in the
speed of new feature implementation.
“In turbulent times, composable business principles help organizations
master the accelerated change that is essential for business resilience
and growth. Without it, modern organizations risk losing their market
momentum and customer loyalty,” said Groombridge.
Hyperautomation enables accelerated growth and business resilience by
rapidly identifying, vetting and automating as many processes as
“Gartner research shows that the top-performing hyperautomation teams
focus on three key priorities: improving the quality of work, speeding
up business processes, and enhancing the agility of decision-making,”
said Groombridge. “Business technologists supported an average of 4.2
automation initiatives in the past year, too.”
Privacy-Enhancing Computation (PEC)
As well as dealing with maturing international privacy and data
protection legislation, CIOs must avoid any loss of customer trust
resulting from privacy incidents. Therefore, Gartner expects 60% of
large organizations to use one or more privacy-enhancing computation
techniques by 2025.
PEC techniques – which protect personal and sensitive information at a
data, software or hardware level – securely share, pool and analyze data
without compromising confidentiality or privacy. Current use cases exist
in many verticals as well as with public cloud infrastructures (e.g.,
trusted execution environments).
“Data is strung throughout many of this year’s trends, but it is only
useful if enterprises can trust it,” said Groombridge. “Today, assets
and users can be anywhere, meaning the traditional security perimeter is
gone. This requires a cybersecurity mesh architecture (CSMA).”
CSMA helps provide an integrated security structure and posture to
secure all assets, regardless of location. By 2024, organizations
adopting a CSMA to integrate security tools to work as a cooperative
ecosystem will reduce the financial impact of individual security
incidents by an average of 90%.
leaders struggle to integrate AI within applications, wasting time and
money on AI projects that are never put in production, or struggling to
retain value from AI solutions once released. AI engineering is an
integrated approach for operationalizing AI models.
“For fusion teams working on AI, the real differentiator for their
organizations will lie in their ability to continually enhance value
through rapid AI change,” said Groombridge. “By 2025, the 10% of
enterprises that establish AI engineering best practices will generate
at least three times more value from their AI efforts than the 90% of
enterprises that do not.”
Total Experience (TX)
TX is a business strategy that combines the disciplines of customer
experience (CX), employee experience (EX), user experience (UX) and
multiexperience (MX). The goal of TX is to drive greater customer and
employee confidence, satisfaction, loyalty and advocacy. Organizations
will increase revenue and profit by achieving adaptive and resilient TX