IT in 2022 – what to expect from the IT sector over the next 12 months

The whole world is talking about tech in 2022 – how the industry will revolutionise, diversify and integrate across borders, job sectors, lifestyles and cultures.

But what about IT as a whole? And how does our rapidly digitising economy and culture impact what could now be considered the “traditional” arm of tech: an enterprises’ IT department?

IT – the science and activity of using computers and other electronic equipment to store and send information – covers the whole gamut of digital devices, software, hardware and people.

Tech is a catch-all term that fits different contexts – it could mean specific tools, programs or processes, platforms, products, even whole companies. It’s allure lies in its generalist definition, and as such it has become a byword for anything to do with digital work, culture, lifestyles and innovation.

• For the purposes of this blog, we wanted to delineate Tech and IT – IT is the manifestation of tech-led ideas in people, processes and order. IT has a huge year ahead of it as physical networks, individuals and whole societies pivot to deal with a more digital, more cloud-based and less physical world.

Tech and IT trends for 2022

Gartner has released what they say are the 12 top tech trends for 2022.

We wanted to start our IT analysis here because of how ubiquitous and generationally defining these changes are and will be to IT and our wider world:

Trend 1: Data Fabric – making data available everywhere it’s needed regardless where the data lives.

Trend 2: Cybersecurity Mesh – a flexible, composable architecture that integrates widely distributed and disparate security services.

Trend 3: Privacy-Enhancing Computation – secures the processing of personal data in untrusted environments.

Trend 4: Cloud-Native Platforms – technologies that allow you to build new application architectures that are resilient, elastic and agile.

Trend 5: Composable Applications – makes it easier to use and reuse code.

Trend 6: Decision Intelligence – a practical approach to improve organizational decision making through AI and automation.

Trend 7: Hyperautomation – the ability to rapidly identify, vet and automate as many business and IT processes as possible.

Trend 8: AI Engineering – automates updates to data, models and applications to streamline AI delivery.

Trend 9: Distributed Enterprises – serving the needs of remote employees and consumers, who are fueling demand for virtual services and hybrid workplaces.

Trend 10: Total Experience – holistic management of stakeholder experiences.

Trend 11: Autonomic Systems – self-managed physical or software systems that learn from their environments.

Trend 12: Generative AI – learns about artifacts from data, and generates innovative new creations.

So what trends will impact IT teams and day-to-day IT operations in 2022?

While not every trend above will change the nature of IT management, some of them will have a huge impact:

• Security – Trends 1, 2, 3, 7, 8, and 11 all touch on the centrality of security to successful tech use in 2022. As malware and ransomware attacks rise and as corporate spending rises to meet the demand on providers to secure networks, IT teams site at the nexus of error management, and uniquely have a huge roll to play in not only the patching and physical maintenance of networks and systems, but the training and solidity of social and workplace knowledge to make sure every system is free from human error, as much as tech error.

• The leading edge – part and parcel of secure network analysis is the careful handling of data at the edge. Trends 2, 3, 9, 11 and 12 speak to this point. The more touch points there are, and the more data analysis happens at the end point rather than at nodes or servers, the more IT attention needs to be focused on end-point contact, safety and efficiency.

• AI and IT – while machines learn to write copy, market products and sell to real people, IT engineers have to make sure the systems continue to work (and learn) the right way. This means the continued application of human proofreading (for example in reducing AI bias in algorithmic code) on autonomous systems.