Reflecting on Gartner’s Top Technology Trends For 2022
Like every year, Gartner, Inc has presented another list of the top strategic technology trends for 2022. The list consists of 12 trends, selected on basis of the technology demands that flow down to CIOs and IT leaders. Unlike 2021, where technology trends were solely focused on navigating the pandemic, this year’s list highlights digital innovations to help companies emerge stronger against modern business challenges.
David Groombridge, Research Vice President at Gartner classifies these trends into three specific themes – Engineering Trust, Sculpting Change, and Accelerating Growth. These three themes are closely aligned with what today’s business leaders want i.e looking to invest in digitalization to deliver better customer experience, operational efficiency, and accelerate top-line growth.
Though these trends show immense potential especially looking at the current events of the coronavirus pandemic, the bigger question is how to put them into action and design the next steps for your organization.
The very reason, iLink Digital brings you an in-depth reflection of these top technology trends and helps you determine whether these trends are a threat or an opportunity. We leverage our business and technical knowledge to help you understand the impact of these trends before you start implementing them.
How did Gartner select these top technology trends?
Gartner generally selects these trends based on CEOs’ priorities for their organizations. They consider several inputs such as quantitative data, inquiries, survey data of CIOs, CTOs, and the board of directors. They also consider data from published research such as Hype Cycles and technology riders.
Arun Chandrashekar, CTO/CIO Advisor, and Distinguished VP at Gartner admit that the company does not know everything. They are humble enough to take help from external ecosystems like academic institutions, research labs, large vendors, venture capitalists, and startups before settling down on the list.
More than 2000 analysts from their organization have the opportunity to nominate these trends, discuss them widely in the research group and then vote on them. To quote Arun, “Selecting top trends is a cumulative effort that triangulates all of these.”
Top Technology Trends of 2022
Forbes claims these trends are nothing but a creative modification of old trends, let’s take a closer look at each one of them.
- Data Fabric
Research shows that up to 68% of data is not analyzed in most organizations and up to 82% of enterprises are inhibited by data silos. Today’s businesses need to be data-ready to ensure strategic effectiveness and perform at their optimum. Accessing the right data at the right time across multiple platforms and applications has become a mission-critical priority for organizations.
However, data management and making it available everywhere is not quite as easy as it seems. Especially when the data environment is increasingly becoming diverse, distributed, and complex. Steps in, data fabric – an architecture and set of data services that bridge the gap between the disparate data sources. It can be explained as an integrated layer or fabric, stretched over a larger area that connects multiple data sources and processes the data within.
A data fabric utilizes continuous analytics, eliminating the inefficient, repetitive, and manual data integration process to support new applications and business innovations across hybrid and multi-cloud platforms. In simple terms, data fabric is the ability to dynamically improve data usage with its inbuilt analytics, giving your business a single compliant and accessible view of data.
Here’s how iLink helped a leading oil and gas company with real-time data visualizations enabling better and faster decision making.
- Cybersecurity Mesh
Protecting such a distributed data fabric is no easy feat. Most companies even fail to understand the nature of the cyber threats resulting in underspending in cybersecurity or spending in the wrong direction. Moreover, cyber threats keep increasing and there are no perfect solutions to cease these threats.
Thus implementing a cybersecurity mesh is a composable approach to improve your overall security. It can be defined as a cyber defense strategy that independently secures each device in its perimeter including firewalls and network protection tools. It widely integrates with disparate security services bringing integrated tools with common interfaces and APIs into the security process as needed.
In simple terms, Cyber Security Mesh Architecture (CSMA) provides centralized management, analytics, and intelligence about what is going on across the enterprise. By 2024, organizations adopting CSMA are expected to reduce the financial impact of individual security incidents by an average of 90%.
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- Privacy-enhancing Computation
Data is and will remain to be the most valuable asset a company can produce and keep safe. But as companies are looking for ways to prioritize data security, consumers are becoming more skeptical in sharing it. They are getting wary about which company will be accessing and managing their data and how much they should allow it.
As per the statistics from Pew Research Center, 52% of the adults opted not to use a product or service due to worries about how their personal information might be collected. With Privacy-enhancing computation (PEC), this problem is quite solved as it secures the processing of personal data in an untrusted environment.
Organizations can use consumer data without betraying its confidentiality. It is an umbrella term for privacy-protection technologies that allow value extraction from data while meeting compliance requirements. Organizations can draw actionable insights without sharing personal or sensitive data with different parties.
PEC concerns all spheres of an individual’s life, whether it’s social media or a bank account. It assures them that their personal data will not be announced to third parties. Simply put, it helps the security borders to expand their abilities and level of anonymity.
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- Cloud-native platforms
Cloud-native has real traction among companies looking to repurpose their existing application portfolios or build new ones. These platforms improve on the traditional lift and shifts approach to help companies take advantage of the benefits of the cloud and add complexity to maintenance. It uses the core capabilities of cloud computing to build application architecture that is resilient, elastic, and agile.
These architectures produce highly automated cloud services to help organizations deliver digital capabilities irrespective of the location. A reason why, 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.
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- Composable Applications
Gartner says the future of next-generation business applications is composable, ie. applications built from business-centric modular components. A primary reason is the changing needs of the business and its ability to deliver innovations at a quick pace. Customers and employees increasingly expect more contextualized and personalized application experiences.
To adapt applications dynamically and respond to the accelerating pace of business change, organizations must consider turning composable. It can be defined as decoupling the blocks or component parts of an application to more finely tune them and create a whole new application that is functionally better than the sum of its parts.
When it comes to implementing and maintaining applications, business requires a whole new vision, approach, and strategy. With composable applications, they can use and reuse code, accelerating the time to market and releasing enterprise value.
You might also find important: 5 Signs It’s Time to Modernize Your Applications
- Decision Intelligence
One of the top priorities for businesses today is to become an analytics and AI-driven organization. Especially amidst the pandemic, when every company is looking to adopt digital transformation. These digital competitors are more resilient and responsive to the changing demands of the customer.
To emerge stronger in such competitive times, implementing Decision Intelligence is an advantage. It empowers organizations’ ability to make data-driven decisions in real-time, converting information into better actions. It’s a fusion of a whole set of technologies and algorithms machine learning, deep learning, predictive analytics, business intelligence, applied data science, and decision modeling.
Gartner forecasts that more than 33 percent of large organizations are going to have analysts who will practice decision intelligence by 2023. Soon it will be a vital science for the AI era, that will help business leaders lead their AI projects responsibly at scale.
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Coined by Gartner in 2020, the term Hyperautomation refers to the “end-to-end” automation of complex business processes beyond the confines of individual processes. Robotic Process Automation (RPA) combined with complementary technologies like machine learning (ML) and artificial intelligence (AI) augments business processes that once required the guidance of a subject matter expert.
With the help of these technologies, machines can identify processes and opportunities to automate as many business and IT processes as possible, enabling scalability, remote operation, and business model disruption. According to Gartner’s research, in 2022 the hyperautomation market is expected to exceed $596 billion, which is a 24% increase when compared to 2021.
Hyperautomation can be defined as a data-driven approach rather than the process-driven approach. It creates a digital workforce by integrating every process with one another to capture, analyze and make decisions using structured and unstructured data. This workforce can accomplish repetitive tasks, discover automation opportunities and execute complex processes that usually rely on knowledge input from humans.
- AI Engineering
AI is the most transformative opportunity in business and IT today. However, the real challenge for a lot of organizations implementing AI projects is also characterized by very high failure rates. Though businesses are excited to unleash the potential of AI, they are looking for ways to mitigate these failures in their environment. AI engineering is the answer to all these problems.
AI engineering can be defined as a discipline of operationalizing AI models using better-integrated data pipelines, in a more automated model development with very strong governance built into it. It automates the deployment of these models into production environments to streamline AI delivery and ensure its ongoing business value.
David Groombridge, Research Vice President at Gartner notes that AI engineering adoption will lead to three times more value for AI efforts by 2025. The real differentiator will lie in the organization’s ability to continually enhance through rapid AI change.
- Distributed Enterprises
Gartner believes, distributed enterprises reflect a digital-first approach. Driven by the massive growth in remote and hybrid working, the distributed enterprises will help businesses improve their employee experience, digitalize consumer and partner touchpoints and build out product experiences.
Industries from retail to education are looking to reconfigure their delivery model to embrace distributed fashion, opening up new pathways for talent acquisition. Gartner expects that by 2023, 75% of organizations that exploit the benefits of distributed enterprises will realize revenue growth 25% faster than competitors.
- Total Experience (TX)
The Gartner 2021 Digital Business Acceleration Survey found that the top two reasons for pursuing digital initiatives are – enhancing customer experiences and improving employee productivity. Implementing a total experience strategy can help IT leaders achieve both of these outcomes.
Total-experience is a business strategy that integrates the customer experience (CX), employee experience (EX), user experience (UX), and multi-experience (MX) across multiple touchpoints to accelerate growth. It helps businesses create a superior interconnected experience for customers and employees enhancing their satisfaction, loyalty, and advocacy.
By managing each experience effectively, businesses will drive better outcomes, increase revenue and profit and create a more holistic, adaptive, and resilient approach.
- Autonomic Systems
As the name suggests, Autonomic systems can modify their own algorithms to help businesses adapt to new conditions without any external software updates. These systems are self-managed, can learn new tasks, and provide quick responses, optimizing their behavior in complex ecosystems.
These systems use a set of technology capabilities to support new business requirements and situations. It’s currently deployed in complex security environments and is expected to become common in physical systems such as robots, drones, manufacturing machines, and smart spaces in the longer term.
- Generative AI
The MIT Technology review described generative AI as one of the most promising advances in the world of AI in the past decade. It refers to the program that uses existing content like text, audio files, or images to generate new content that is similar to the original content.
Generative AI uses machine learning methods, enabling computers to learn underlying patterns of the content or object from their data. Then it uses these patterns to generate brand-new content, though which is similar but completely original.
Generative AI offers limitless possibilities coupled with convenience to create new forms of creative content ranging from the medical field to product creation. Creating software code, facilitating drug development and target marketing are some of its applications.
The technology is also used through fraud prevention, personalized customer support, and intelligent decision-making. By 2025, Gartner expects generative AI to account for 10% of all data produced, up from less than 1% today.
That’s all for 2022! Now wrapping up…
The past 18 months have triggered faster change than ever before and these trends are proof of the fast-changing priorities of CIOs. While some of these trends have foundational technological capabilities to compete in a digital environment, others possess business-oriented capabilities to help companies stay ahead of the competition.
Looking ahead, these Gartner’s technology trends will help organizations analyze their needs, evolve and implement accordingly. Companies embracing and planning for these trends will develop strategies for reliant and sustainable business success. To simply put, these trends are long-term technology bets that organizations need to make.
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