The top seven CIO trends for 2022
Every new year, the publications that CIOs consult to get a sense of the most important technology trends for the upcoming year promise that the items on their lists will be game changing. However, we’ve turned a corner over the past two years, and the pandemic has drastically sped up the digital transformation efforts that were already underway at most organizations. With no end in sight to the pandemic, and the need to effectively manage remote or hybrid experiences, the technology predictions for 2022 look no different.
We’ve selected the following top CIO trends for 2022 after consulting expert sources, including Gartner. Read further to discover the transformative technologies that you will likely encounter, or even adopt, this year and beyond.
What it is: Metaverse is envisioned to be the next evolution of the Internet and is seen as a shared virtual world. It brings immersive experience to life leveraging technologies such as virtual reality (VR), augmented reality (AR), and non-fungible tokens (NFTs).
The Catalyst POV: We see metaverse enterprise as the one which enables the next level of customer engagement, leveraging the metaverse ecosystem. Some examples include using virtual avatars of customer service agents rather than corporate employees for assisting over a voice or chat channel, or letting customers browse virtual retail stores to try on different merchandise in virtual rooms. These can create more immersive, interactive experiences for customers. It is still in an early stage, but mass adoption has begun to gain traction.
Acceleration of cloud technology
What it is: Cloud-native platforms enable customers to fully harness the power of the cloud by leveraging the latest and greatest in cloud offerings. They allow organizations to create “born in the cloud” applications that are secure, resilient, manageable, and observable. To align with evolving business needs, these systems can be changed frequently and predictably, with minimal effort. Cloud platforms can also be powered with technologies such as microservices-based APIs, containers, orchestration, serverless functions, and CI/CD.
In addition, distributed cloud, the latest trend in cloud technology, provides cloud capabilities to different physical locations. Cloud providers maintain, operate, and evolve capabilities, but physically execute at the point of interest (near to the origin). It has evolved from the convergence of 5G, Edge, and IoT. Common styles include Edge cloud and Metro-area community cloud.
The Catalyst POV: Cloud-native companies, like Spotify, Netflix, and Amazon, have disrupted their respective industries with game-changing cloud technologies. A major factor in their success has been microservice architecture, which allows for a modular approach to software development, freeing teams up to deliver new customer experiences faster.
All this to say—CIOs need to remain nimble. To thrive after years of uncertainty, they will need to invest in future-facing technology that will enable digital transformation at scale. Those who do will inject innovation, opportunity, and resiliency into their organizations. The ability to run application components in a mix of cloud locations and environments allows for greater flexibility to meet requirements across the enterprise.
Zero-trust security architecture
What it is: Digital transformation isn’t going away, and as organizations digitize more of their business, they must keep up with cybersecurity to ensure proprietary and customer data is secure. Zero-trust security architecture involves an integrated approach to securing all enterprise IT assets regardless of location. It also allows for needed flexibility and doesn’t hinder the company’s growth.
The Catalyst POV: These capabilities are particularly pertinent in the aftermath of the COVID-19 pandemic. An estimated 26% of the workforce was remote in 2021. Many will continue to work remotely into the future. Zero-trust security architecture enables the secure accessibility of any digital asset, no matter where it is located, while continuing to provide security. As workers and systems become more distributed, the architecture as a strategy allows for protection from varied threats.
What it is: With Apple recently implementing privacy protections on iPhones and iPads and Facebook adoption decreasing, privacy is at the top of most consumers’ minds nowadays. Likewise, businesses will need to strengthen their ability to share data while protecting confidentiality and sensitive information. The technologies that will allow this to happen include an environment for containing the data securely, a way to process sensitive data across the enterprise using ML, and data transformation methods that ensure privacy.
The Catalyst POV: Beyond the reputational damage of a data breach, the risk of lax data security practices extends to the very real issue of intellectual property theft. As data sharing further cements itself as a necessity for doing business in today’s world, privacy compliance provides an added layer of security by not only preventing cyberattacks, but also by enabling the tracking of actions taken with the data and ensuring confidentiality.
What it is: Contextual intelligence, or the ability to model decision-making in a repeatable way, can allow organizations to make better data-driven decisions. Contextual Intelligence includes Generative AI, or AI that generates synthetic data to train models, identify valuable products, or create something new from preexisting source data and content. The ability for AI to independently realize novel content and data based off its training represents the next stage in AI maturity. According to Gartner, in the next two years, one-third of large organizations will use contextual intelligence for structured decision-making.
The Catalyst POV: In addition to informing strategic decisions that affect the bottom line of their own organization, executives can leverage contextual intelligence for competitive analysis. The combination of artificial intelligence, business intelligence, and predictive analytics can help solve one of the most pressing challenges in business today: how to turn insights into outcomes.
What it is: Hyperautomation—the ability to rapidly identify, vet and automate as many processes as possible—will allow organizations to deliver solutions faster and more consistently. Hyperautomation can also solve the problem of dealing with “technical debt,” by optimizing and synergizing the technologies that need it, creating more consistency in the process.
The Catalyst POV: By being able to accelerate digital transformation through hyperautomation, organizations can ensure that their operational processes are streamlined and efficient, and that they are also resilient in the face of unexpected situations that might challenge the business (such as a global pandemic or climate crisis). After all the workplace upheavals of the past two years, it would benefit CIOs to invest in hyperautomation to improve their operations.
What it is: Many organizations will continue to make investments in AI, but those that don’t leverage AI engineering techniques will likely fail due to challenges in maintaining, scaling, and governing their projects.
This is where AI engineering comes into play. The discipline enables a framework and tools to design AI systems for complex, ever-changing environments. To do this, organizations should combine DevOps principles (for DataOps) and the machine learning model pipeline (for MLOps).
The Catalyst POV: AI engineering by its very definition is geared around finding practical applications for AI. For all its promise, AI has to be operationalized and scaled to have impact. Through continuous delivery and optimization of AI systems, enterprises can realize the results of their AI initiatives.
These seven CIO trends represent the bleeding edge of technology. On the cusp of significant advancements across cyber, intelligence, cloud, ML, AI, and automation, many of these solutions require proofs of concept as their real-world application will need to be proven out.