This is the first blog in a three-part series on AI in Salesforce testing. Stay tuned for parts two and three!
The rise of artificial intelligence is bringing rapid innovation to Salesforce testing and promises increased reliability and better quality to software applications.
CEOs worldwide are putting AI at the top of their agendas, often pushed to innovate by either a desire to get ahead or a fear of getting left behind. But as in life, when we rush it, we risk it. Organizations rushing toward AI adoption without proper due diligence may jeopardize their systems, security, and valuable customer assets.
At Provar, we’re building powerful products to make Salesforce testing and quality management more accessible, efficient, and effective. And we are certainly not immune to the pressures – and the potential pitfalls – of using AI in testing without the right strategy.
In this blog, we’re outlining three major AI pitfalls in testing so you can watch out for them in your search to find the best Salesforce testing solution.
Pitfall #1: Technology Trends Over Trust and Transparency
Many organizations hastily embrace AI-powered solutions, prioritizing technology trends over trust and transparency. Rushing into AI integration without a customer-focused strategy can leave your Salesforce environment — and valuable customer data — open to risk.
Organizations must prioritize keeping customer data safe when integrating AI capabilities into their testing solutions. Hasty AI integration can open the door to security vulnerabilities, including prompt injection and risk of sensitive information, critical processes, and customer trust.
When evaluating an AI-powered testing solution, ensure it can withstand potential attacks and security breaches. Before moving forward, ask how the AI algorithms handle data, make decisions, and interact with other components of your testing ecosystem. And always remember that in all things, the customer comes first.
Pitfall #2: Overly Simplistic or Unrealistically Sophisticated Solutions
When choosing an AI-powered or AI-enabled automated test solution, it is critical to balance simplicity and sophistication. But this can be tough, especially when an organization is pushing for AI integration.
Often, organizations opt for a quick fix or overly simplified solution to integrate AI rapidly but fail to realize the shortcomings that may arise with hasty adoption. For instance, generative AI may rapidly generate code or test data but often lacks the precision necessary for effective testing and quality assurance without training.
On the other hand, organizations may be allured by complex AI models that require extensive training and resources. The time and effort required for training and implementation may outweigh the benefits of a complex solution — rendering it impractical for day-to-day operations.
Make sure you clearly understand your specific testing requirements, the complexity of an AI-powered solution, and a realistic view of the resources you have at your disposal before signing on to a new testing solution. A thoughtful approach should prioritize practicality, usability, and adaptability.
Pitfall #3: AI Adoption Without Security Infrastructure
When organizations adopt solutions “powered by AI” without carefully considering — and communicating — the security precautions they are implementing, they may encounter our third and final pitfall. Any test automation solution that touts AI capabilities must offer multiple layers of security to protect sensitive user data.
Furthermore, organizations must be ready to communicate their security strategies with their shareholders and customers. They should always have short-term and long-term security solutions to ease concerns and strengthen confidence. Companies must also explore enhanced, up-to-date security measures as they build their AI capabilities.
Always ask about an organization’s security plans and how a solution will keep up with rapid innovation. Look for short- and long-term goals and action plans to guarantee the solution will take your security seriously.
Conclusion
As AI continues to dominate the technology landscape, organizations and decision-makers must approach AI with discernment. By looking for common AI pitfalls, leaders can protect their organizations from potential risk and more easily identify testing solutions they can trust.
Provar proudly upholds our commitment to ethical and dependable AI enhancements and will continue to adopt AI with careful consideration. While we are certainly not the only test automation solution on the market, we want to ensure everyone has access to the information they need to make the best decisions for their organizations.
To learn more about AI in Salesforce 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!
