Quality Engineering and Testing Predictions for 2022

While each of the trends I predict for 2022 is important in its own right, it’s only when viewed holistically that the true picture of an evolving QE and Testing landscape can be seen. Of course, while a trend such as the growing use of artificial intelligence is always going to garner more excitement than others, it remains just part of the overall story.

Prediction 1: More attention on the orchestration of quality

We will see more attention being paid to orchestrating quality in organizations. What I mean by that is, management level expectations and targets with regards to quality will see minimum level standards and guidelines being defined for teams to work with. The position of quality architect will be elevated to a higher, enterprise level or a line of business level, with the task of defining quality standards and managing innovation on quality. I expect to see the rise of centers of excellence (COEs) meeting specialized testing expertise needs, such as performance testing, security testing and usability testing.

Prediction 2: Changing role of tester to quality engineer

Clearly the role of tester will continue to change and move in the direction of a quality engineer—somebody who enables the teams to achieve quality. This quality engineer will have a high level of technical skills combined with an understanding of business value in order to be a bridge between technology and business teams.

Prediction 3: An increase in intelligent test automation

I expect to see more intelligent test automation across all activities, not just the automation of test execution but also of script generation, data generation, and more. This will be a full end-to-end automation model; one that uses more intelligent techniques so that it’s not about taking every test case and automating them, but about enabling smart strategic decisions on what to automate and which technologies to use.

Prediction 4: More data-driven decisions

Of course, effective testing relies on data, and I predict more data-driven decisions being made around quality engineering. This means the definition and visibility of quality indicators will play a bigger role, as will the continuous monitoring of quality. This will see the monitoring of quality in production, with all the data used to guide decisions regarding the next sprint or project and where QE should be targeted to optimize efficiency.

Prediction 5: Further breakthroughs in the use of AI

I expect to see more intelligent test automation across all activities, not just the automation of test execution but also of script generation, data generation, and more. This will be a full end-to-end automation model; one that uses more intelligent techniques so that it’s not about taking every test case and automating them, but about enabling smart strategic decisions on what to automate and which technologies to use.

In summary

These predictions are not going to suddenly change the QE and testing landscape; rather they represent an evolving picture. In fact, all of these predictions are already underway, with each area growing in strength over time. I expect to see continuous improvement and broadening of scope where applicable, not just in 2022 but beyond. As the role of quality engineer continues to develop, all five areas should be viewed holistically to generate benefit and value.