Artificial intelligence has seamlessly integrated into the field of quality assurance. While technology still has room to grow, it already delivers significant benefits in terms of testing coverage, depth, and speed.
At Gofore, we have firsthand experience with AI assistants, which we have been developing to support quality assurance and testing efforts. In this blog post, we’ll dive into what our AI assistant entails and explore the opportunities AI brings to our work.
What is an AI assistant?
An AI assistant won’t do your work, but it accelerates and supports it in innovative ways. You can ask the assistant questions like “What does this requirement mean?” or discuss how a particular requirement should be tested. It can even create and execute automated test cases. The key functions and direct benefits of the AI assistant can be summarised as follows:
- Integrating and analysing data
- Processing requirements and test cases
- Automating repetitive tasks
- Enhancing traceability and real-time troubleshooting
For example, the assistant simplifies identifying conflicting requirements, reduces the need for manual effort, and enables more effective decision-making. What a powerhouse!
Challenges of the AI assistant
Like any tool, the AI assistant has its challenges. The biggest one being understanding context. Without sufficient background information and proper context, the assistant may make incorrect conclusions. Human input is also required to validate outputs, such as test cases or automation scripts, adding extra steps to the process and limiting the assistant’s autonomy.
Another major challenge is data collection and integration. For the assistant to function effectively, it requires large volumes of data from various sources. Combining and processing this data requires technical work and meticulous planning. The biggest obstacle here is ensuring the classification and accuracy of the data, as the assistant cannot inherently determine what is relevant or outdated. These issues can slow down deployment.
The market value of the AI assistant
We were motivated to develop the AI assistant because of the possibilities for the market and its users. Its most significant contributions include:
- Speed and efficiency
- Expanded testing coverage
- Targeted and personalised use of information
Speed and efficiency come from the assistant’s ability to quickly identify errors and suggest corrections, process source materials, and customise outputs. This saves hours or even days of work. The assistant adds remarkable value, particularly in test automation and data analysis.
For instance, the assistant helps design negative test cases – scenarios that account for potential failures. This expands testing coverage by supporting analysis and perspectives that might not occur to human testers.
Unlike a traditional search tool, the AI assistant personalises information to meet the user’s needs, whether they are a test designer or a test automation engineer. Generative AI doesn’t just provide generic answers; it tailors its solutions to fit the user’s context.
A revolutionary approach to testing
These capabilities make the AI assistant a groundbreaking way to leverage data and enhance testing processes, particularly in terms of speed and analytical depth.
This potential makes the use of AI so exciting – it opens doors to possibilities we can’t yet fully grasp, even shaping the way we work in the future. There’s no area that cannot benefit from AI’s capabilities, and the next evolutionary step will bring us closer to autonomous AI agents capable of performing certain tasks independently.
In the next part of this blog series, we’ll discuss testing AI applications. Later posts will feature Gofore’s Granny Bot and how AI can support customer interview coaching. The possibilities for AI are endless, both in enhancing expertise and building business!
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