More for Gartner Top Strategic Technology Trends for 2022

At the end of each year, Gartner publishes what they think are the top strategic technology trends for the next year. This link contains the twelve strategic technology trends for year 2022, with their concepts and deep discussions:

  1. Data fabric
  2. Cybersecurity mesh
  3. Privacy-enhancing computation
  4. Cloud-native platforms
  5. Composable applications
  6. Decision intelligence
  7. Hyperautomation
  8. AI engineering
  9. Distributed enterprises
  10. Total experience
  11. Autonomic systems
  12. Generative AI

With this blog, I am not going to have deep dive for these trend items, instead, I will put all these twelve trends into one big picture, show their relationships, and how they connect and affect each other. Purpose is to give readers some insight and trigger their thinking and discussion about how to put these trends into practices.

Three Layers and Twelve Trends

As above graph, I put all these twelve trends into three layers, and mark them by numbers following how Gartner listed them in the article.

Business Strategies: For companies who provides IT solutions to customers/clients, based on recent market and pandemic effect, their business strategies need to be adjusted to “reflect a digital-first, remote-first business model to improve employee experiences, digitalize consumer and partner touchpoints, and build out product experiences” (Distributed Enterprises, Gartner) and “integrate employee experience, customer experience, user experience and multiexperience across multiple touchpoints to accelerate growth” (Total Experience, Gartner).

IT Operations: Operations, including business operations, devOps, and MLOps, need to be automated to enable agility for solution development, be adaptive to market, and flexible, scalable to grow. Creating operation pipelines to enable CICD and “automate updates to data, models and applications to streamline AI delivery” (AI Engineering, Gartner) become essential for the business succeed.

Solutions: Solutions are the deliverables that an IT company deliver to customers to resolve their certain business cases.

With the dynamic and fast changing market, the traditional solution/application development can not adapt well to the market requests and requirements.

In current market, an IT solution generally includes two parts, applications/services and ML models, and runs on a security mesh powered Cloud native platform.

When developing a solution, the developers, including software engineers for applications/services development and data scientist for ML models development, need to pay specific attention to:

  1. Application/service development needs to include composable components to “make it easier to use and reuse code, accelerating the time to market for new software solutions and releasing enterprise value” (Composable Applications, Gartner). Microservice architecture fits into this well.
  2. To best adapt to the dynamic business changes, the solution needs to be smart as an autonomic system which are self-managed software systems that learn from their environments and dynamically modify their own algorithms in real time to optimize their behavior in complex ecosystems.

Gartner’s Generative AI brings in an approach for solution architects/engineers to develop and deliver new features of a solution or even a new product solution to market.

All are connected

Although I discussed all twelve trends in three layers separately, they are connected to create an integrated ecosystem for IT solution development, delivery and lifecycle management. With modern market, Machine Learning technologies will be the key and be widely used in all these layers. Each layer also needs IT solutions support to make them run smoothly.

People may view these trends in a different way. Gartner puts these twelve trends into three themes:

  1. Engineering trust: including Data Fabric, Cybersecurity Mesh, Privacy-Enhancing Computation, and Cloud-Native Platforms.
  2. Sculpting change: including Composable Applications, Decision Intelligence, Hyperautomation, and AI Engineering.
  3. Accelerating growth: including Distributed Enterprises, Total Experience, Autonomic Systems, and Generative AI.

The goal of this blog is not to discuss how to catalog these trends, but to give a view of their connections, relations, so to give software engineers, data scientists, solution architects, product managers, and other decision makers an integrated picture, and hopefully trigger them to think of these trends in their daily work.






Software Architect and Developer

Love podcasts or audiobooks? Learn on the go with our new app.

Recommended from Medium

Making our Game more Immersive using Sound

Tutorial: Using MTurk and AWS Lamba with Amazon API Gateway

Impediments in the Backlog

Running Jmeter Load Tests and Publishing Jmeter Report Within Azure DevOps

How to use MailCatcher in Rails

Introduction to Redux in Flutter

Documents OCR: Improving Efficiency by Making PDFs Searchable

How to split a three-way RAID1 array

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store
Jingdong Sun

Jingdong Sun

Software Architect and Developer

More from Medium

Ai’s Role In Enhancing Project Management

Ai’s Role In Enhancing Project Management

Calculating the ROI of Low-Code & Bespoke Development

Why Devs Need Deep Customer Understanding for the Win

Dynamic QR Codes for Omnichannel Marketing

A computer screen with graphs showcasing marketing insights