This is the third blog in a three-part series on AI in Salesforce testing. Be sure to read the first two blogs, “Common AI Pitfalls in Testing to Watch Out For” and “Unjumbling the Jargon: A Guide to Today’s Test Automation Slogans and AI-Related Claims,” and stay tuned on our blog for more conversations around AI!

As artificial intelligence continues to command the automated testing marketplace, it is increasingly important to distinguish between promising AI capabilities and potential pitfalls. 

However, selecting the right automated testing solution for your organization can be almost impossible without a clear picture of your testing needs and a solid understanding of AI capabilities.

Luckily, the experts at Provar are ready to help. In this blog, we coded some standard AI capabilities into categories you’ll recognize. A “red flag” signals that you should hold off on adoption for now. “Yellow flag” features should be approached with caution. AI capabilities worth your immediate attention have been labeled “green flags.”

Red Flags: Hold Off on Incorporating These AI Capabilities for Now

Your AI implementation strategy should not include AI capabilities until improvements are made. The risks of incorporating these AI components into your test automation will almost certainly outweigh the benefits. 

AI that requires access to sensitive information but lacks proper security measures: 

If AI requires access to sensitive data for training and testing but doesn’t include localized data privacy and security measures — skip it. This technology can open your Salesforce environment to unnecessary risk and security threats. 

AI models with inherent bias: 

When AI models have inherent bias built in, it can have severe consequences for your testing and render results inaccurate or, worse, catastrophic. 

AI components that do not offer seamless integration: 

Your automated testing solution needs to work for you. If the AI components offered do not seamlessly integrate with your existing tools, it’s unsuitable for your organization. 

AI that promises to test your AI: 

Human influence will always be essential, no matter how far AI advances. Please don’t rely on an AI-based solution that eliminates the human element; it will miss the nuances necessary for a solid test strategy. 

Yellow Flags: AI Capabilities to Approach with Caution

The AI capabilities listed below should be implemented with caution. Analyze your organization’s testing needs and discern these AI offerings with discernment. 

AI that requires intensive training: 

If an AI-enhanced solution requires extensive training or specialized expertise, evaluate whether or not it is practical for your organization’s day-to-day operations. 

Brand new AI: 

When you rush it, you risk it. And while being an early adopter certainly has its allure, the right automated testing solution needs an established foundation and a solid security plan. 

AI for its own sake:

The use of AI in testing should always be purpose-driven and customer-centric. Stay cautious and aware of your intentions on innovation; if trying to stay ahead of the game has you making hasty decisions, hold off on AI integration. 

Green Flags: Worthwhile AI Capabilities in Testing

In this case, we give these AI capabilities in automated testing the green light — or flag. These AI capabilities offer organizations more excellent automated test capabilities and better quality assurance, all with the help of artificial intelligence. 

AI components that efficiently tackle menial tasks:

AI capabilities in automated testing have been proven to perform well when tackling menial and repetitive tasks, freeing up teams to spend time on more complex projects. 

AI components that can be used as simulators:

AI components — including performance testing, security testing, user behavior testing, and predictive analytics — can simulate results based on historical data and empower your teams to make more informed decisions. 

AI components that provide accurate insights: 

AI capabilities that give clarity and accuracy can be helpful, including chatbots and virtual assistants that help customers with FAQs and insights based on patterns and historical data. 

Conclusion

As the AI-influenced automated testing landscape evolves, it will become increasingly important to consider the AI capabilities and components that Salesforce testing solutions tout. By evaluating the AI capabilities of an automated testing solution in terms of your organization’s specific needs, you can transform your testing and alter your day-to-day operations. 

Since 2014, Provar has been an industry leader in test automation and quality management. We remain committed to ethical, purposeful AI integration that ensures efficiency, reliability, and security in today’s dynamic testing environments. By offering our insights, we hope organizations can more easily identify the AI-driven automated test solution that suits their unique testing needs. 

To learn more about how artificial intelligence transforms automated testing, download Provar’s latest white paper, “The Pitfalls of AI in Test Automation: What You Need to Know to Keep Your Salesforce Environment Secure,” today!