The artificial intelligence conversation has yet to slow. Regarding testing, AI is poised to revolutionize how we protect our Salesforce environments and ensure the most effective applications possible.

On December 14, Provar hosted a webinar titled “Unraveling AI’s Hidden Hurdles in Test Automation”. The webinar aimed to demystify AI’s role in testing and simplifying complex concepts while delving into its transformative potential and inherent challenges.

The webinar recorded 287 registrants and was exceptionally well-attended. It fostered a high level of engagement through Q&A sessions, surveys, and polls. In an opening poll, we found that 39% of attendees utilize AI daily and 20% weekly, 29 individuals don’t currently leverage generative AI, a surprising revelation in a landscape where folks are rushing toward ChatGPT adoption. Our speakers, Robin Gupta, VP of Engineering, and Indu Sharma, Product Manager, hypothesized that this might be due to workplace access restrictions — but it was an interesting ice breaker to get us started!

Robin and Indu offered invaluable insights during the webinar, discussing how AI changes software testing, challenges with using AI for testing, the good and bad aspects of AI, how to use AI the right way, and what AI actually is in layman’s terms.

Indu highlighted critical ethical and practical considerations in AI adoption, emphasizing the pivotal role of high-quality training data.

“The effectiveness of AI in testing relies heavily on the quality of training data. If not diverse, bias and unfair treatment might seep into testing outcomes.”

– Indu Sharma, Product Manager, Provar

Robin addressed an intriguing question during the Q&A portion and emphasized the necessity for testers to upskill in AI. His advice? Start with a basic understanding, likening AI models to programming languages. He stressed the importance of gradually delving into technical courses, underlining the need for AI skills to supplement testers’ expertise in solving real-world use cases.

“What skills do testers need to develop to work effectively with AI and testing? One, I would say, is to start simple. First, understand what a large language model is, and think of it as a programming language, like how you would use Java. Writing that test automation software is similar to how you would use a large language model for genetics of the test cases, right? To go about that learning process, you can start very non-technical, or maybe with some of the very friendly courses that we have on the University of Provar. Then gradually ramp up on some of the technical ones, maybe using OpenAI or building something custom. But what skills will testers need? I think this is the time in our lives that all of us need AI skills. We need to really understand how this can supplement us, how it can become the man plus the machine to solve some of the use cases.”

– Robin Gupta, VP of Engineering, Provar

The discussion explored how AI reshapes software testing, spotlighting automated test case generation, defect identification, and root cause analysis. However, Indu cautioned against blindly embracing AI trends, urging meticulous planning while integrating AI into existing testing processes, especially in companies reliant on legacy systems.

“AI relies heavily on data, and we cannot ignore the fact that the effectiveness of AI in testing relies heavily on the quality of training data. So we need to make sure that the data on which it is trained is correct and accurate and it does not lead to any flawed testing outcomes. If the training data used to teach the AI models is not diverse, the system may not adequately represent the world scenarios leading to bias testing outcomes. We also must understand that there are still companies who are using the legacy systems for software testing, so integrating AI into existing testing processes requires careful planning and expertise. We should not just push ourselves towards AI just because everyone else is doing it.”

– Indu Sharma, Product Manager, Provar

The webinar gave participants new insights and a deeper understanding of AI’s potential and its accompanying challenges. Robin and Indu shared excerpts from Provar’s latest white paper, The Pitfalls of AI in Test Automation: What You Need to Know to Keep Your Salesforce Environment Secure, inviting attendees to download it for free after the event for more insights and actionable strategies to safely and successfully integrate AI into their Salesforce testing strategies.

This webinar was one for the books, and as always, we thank everyone who attended, including Robin and Indu, for their valuable insights. If you missed the live webinar, catch the recording here and download the white paper above! Stay tuned for future webinars, where we will feature Provar experts and guests discussing the latest in testing and the Salesforce landscape.

Want more information on AI in testing, how Provar integrates ethical AI into its offerings, and what you should keep in mind when adopting AI into your Salesforce strategy? Download our latest white paper, The Pitfalls of AI in Test Automation: What You Need to Know to Keep Your Salesforce Environment Secure, for free today!