Make sure your IT team holds the right cards

June 1st is the International Day of Board- and Card Games. At Brightest, we are fans of games, whether board or card, and we love winning them. We also like to win when it comes to IT projects and digitalization. It helps to have the right cards in hand as a company and team. Today, one of those major trump cards is AI. Nut how can you effectively use AI for software quality and software testing? We’re happy to explain.

The Use of AI Models in 2024

As the weeks and updates of ChatGPT, Claude, etc. pass, many business leaders realize that AI is here to stay. According to research (MuleSoft 2024), a whopping 80% of companies today are already using multiple AI models. The top three barriers to implementation cited by IT managers are (1) system integration, (2) security risks, and (3) ethical considerations. So, this brings us to how AI is being used in IT organizations, especially in (software testing) teams.

Preparing for the Future of Software Quality with AI

Preparing today, despite the barriers, determines whether your IT team (and company) will be ready for the future. Step one is to train employees and collect high-quality data to train AI models. We also recommend modernizing and making IT infrastructure and making it flexible to support the growing demands of AI.

In addition, AI also presents an opportunity to the shortage of experiences QA professionals in the job market. Virtual test engineers can take over many testing tasks from QA professionals. This allows them to focus on more challenging tasks such as test strategy, automation, and integrations. Integrations are one of the main reasons companies are struggling to implement AI today. Research shows that the average company uses no less than 990 applications across the organization. Those freed-up hours certainly come in handy to ensure all of these interact seamlessly.

The Importance of Cybersecurity

With the growing integration of AI in business processes, concerns about cybersecurity are also increasing. The most frequently heard concern from clients regarding security is the protection of proprietary data/documentation. The best advice we can give is not to use open-source AI models. All data shared via standard (non-paid) AI models is a “wish come true” for many cybercriminals and/or open-source AI models. A second tip we like to share is to set up recurring pentests. This way, you keep control over your company’s evolving IT landscape and stay aware of potential (new) risks.

Conclusion

The use of AI is reaching new heights every day, and the future promises even more innovation and growth. Use the current momentum to prepare and take measures at various levels within the organization. This way, your company benefits from AI’s possibilities and maintains a competitive edge in an increasingly dynamic business environment. Would you like to draw up a roadmap towards the use of AI in QA and more QA-efficiency together? We’d be happy to assist!