Exploring AI Assurance: Key Insights from the CQI Course

There are a lot of courses by many organisations on the topic of artificial intelligence (AI). I have personally taken 3 courses with Project Management Insitute and one platform specific with the work management tool Asana. They were all brilliant courses and contributed to enhancing my knoweldge in this topic, both as a project manager and as an asana user.

When the Chartered Quality Insitute launched its own AI course, I felt like I was AI’d out. Can I really handle another course? The course is the Future of Assurance and the potential of AI. It is directly related to my day to day role. So I signed up and started the course. I tell you, after the first couple of lessons, I could not stop. I was so into it, I was excited at every module that progressed. I was taking notes because the information mattered and provided tips I can use at work. Here are my learning and takeaways.

Quality Professionals who recognise that explainability in AI is not just about technical details but involves making AI decisions clear to non-technical stakeholders are uniquely positioned to advocate for the development of explainable AI models.

THe Future of Assurance Course, CQI 2024

Let me start with the course’s modules:

• The essentials of AI
• Navigating AI risks and benefits
• Building a foundation of ethical AI
• Selecting the right assurance approach
• Collaborating for AI assurance
• Upskilling your team for the AI age

Did you know that there are 6 subsets of AI? Did you know the challenges and considerations of AI that goes beyond ethical implications? Have you thought about how AI makes decisions and can you explain it?

The course helps you clearly define how you can use AI for your assurance services and how you can assure AI itself. For me personally, I liked that the course did not just explain that we have to have eithical AI. It explains why there are ethical concerns and it provides a framework to navigate those concerns. The course introduces a four stage lifecycle that you can follow while implementing AI.

If you always link assurance to audit, then this course will help you shift your mindset. Because while audit is a key element in assurance, it is not the only one. Selecting the correct assurance framework is very useful, especially when you select the framework that is relevent to your business and to the concerns and challenges that are deemed significant. The human-centered assurance is something that can easily be missed yet is very important.

I learned about the four different types of analytics and how they work with different types of AI. And finally, the emphasis of custmer and stakeholder does not go amiss from this course. So if you are starting on the journey of implementing AI, you can start by asking:

1. Why do we want to implement AI?
2. What process / product / or process are we targetting?
3. What data is being fed into the system?
4. How is the data being used to make decisions?
5. What governance framework is in place?
6. Are we creating this framework from scratch? or are we following a well established international standard (ISO42001:2023).
7. Who will I be working with and what will the responsibilities of this committee or team be?

Of course, plenty more questions to ask and layers to dive into, but this is a high level snapshot of what you will get from this course. If you have not signed up yet, do not wait and head to store.quality.org and purchase the course: The Future of Assurance and the Potential of AI. You will not be disappointed.

Post cover image was created by ChatGBT following the prompt: ‘can you give me an image to use for a blog to relfect the concept of AI assurance.’