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Automation and Artificial Intelligence Study Commissioned by Keysight Technologies

Keysight commissioned a study to understand how increasing complexity in electronic design and development is impacting companies. In this study, Forrester conducted an online survey of 406 test operations decision-makers at organizations in North America, EMEA, and APAC to evaluate current testing capabilities for electronic design and development and to hear their thoughts on investing in automation (including AI). Forrester conducted the online survey, which included questions provided to the participants asked about their organizations’ current testing environments, future investments, challenges, and expected outcomes from testing automation. The study was completed in December 2021.

Executive Summary

In technology development, companies collect great amounts of data, but they typically store it in functional silos, which creates artificial barriers to making holistic, agile design processes. By using data integration, analytics, artificial intelligence (AI) and machine learning (ML) both on-premise and in cloud-based environments, firms can fulfill long-standing promises in DevOps and TestOps.

The world of testing and validation is increasingly complex; are firms keeping up? 

While respondents report relatively high satisfaction with their variety of testing methods, very few use an automated test approach or AI for integrating complex testing. 


The Goldilocks testing struggle: too much, too little, or just right?

Accurately finding bugs/issues is a technical issue that arises because of over-testing and complexity. Overall, this increases security risk, costs, and extends product time-to-market. Testers feel the challenge to cover every possible scenario and avoid release of faulty products, but that conflicts with the ever-increasing time to market challenge. 


Find the balance and improve results with artificial intelligence and automation

Despite their reported high satisfaction levels with their testing methods, companies are interested in moving to more automated approaches and using AI for integrating complex test suites. They understand this will increase their productivity, simulate product function or performance, and shorten design cycles, thereby, reducing product time to market.

In turn, this improvement in the testing and development process will yield higher customer satisfaction and increase product sales or revenue. They recognize that reducing time to market can be achieved by better analytics on current test and measurement data, integrated software tools across the product development lifecycle, and an improved ability to share data across teams.

Key Recommendations

Read the complete study for Forrester's recommendations for companies to move forward with increasing the amount of automation and intelligence in testing electronic systems.