Teams Real Simple with Pictures: User-to Group Affiliation, or Using Machine Learning to provide Access Review recommendations of Team Members

Some of the things I've been doing this past week: wrapping up the roll out to Switzerland. Prepping from a backend perspective for Germany. Completing a migration from Arvato to Pearson VUE. Scrubbing out anything I can find in reference to Azure AD with extreme prejudice. Progressing multiple DevOps items for net adds to portal UI's for better UX. Then there was Inspire (I managed to get to about 30 sessions all in all). Oh, and testing out the new Secure Service Edge functionality in Entra. These are just some of the high level items from my current corp portfolio. And that doesn't take into account MCT. Nor MVP and community activities. So to use analogies it's like an all you can eat buffet out there right now. And pretty much every day feels like this great game of whack-a-mole. But, then again, I admittedly enjoy it - and besides I'm accustomed to the old perpetual firehose. But one increasing challenge - and one which sits sqaurely within this growing dialogue of needing Copilot and AI for specific roles - is staying current. A legit use case is awareness and knowing when all of these diamonds of useful functionality ship across the stack which could make a real difference to ones role. One such functionality is the new User-to-Group Affiliation for Microsoft Entra Access Reviews which I only saw referenced on a social thread this week where a.) I could have easily missed it and b.) could directly help me with my role since I myself am an access reviewer in my own organisation. So what exactly is it? As written 'This Machine Learning based recommendation...' '...detects user affiliation with other users within the group, based on organization's reporting-structure similarity. [It] relies on a scoring mechanism, which is calculated by computing the user’s average distance with the remaining users in the group. Users who are distant from all the other group members based on their organization's chart, are considered to have "low affiliation" within the group' (Microsoft, 2023). In laymans, it's a functionality within the Microsoft Entra ID Governance SKU which helps you reach a decision on whether users should be in that group (hence Team) or have access to an App based on Entra ID properties. Is this important? Well, yes in theory. We ought to operate on Zero trust and principle of least priviledge, and as an access reviewer it could draw attention to those who may not need access, or if we look at it in another sense it could prompt us as admins to action in regards sanitising Entra ID and our org structure. But therein lies the catch. Sidestepping the inevitable conversation of added cost requiring reviewers hold a SKU over and above P2 - for it to work best requires a clean directory. In my experience, this is typically more an exception or luxury as opposed to the rule, and since the solution is based on machine-learning you can't make the assumption it's guaranteed to be right - so there may be some investment in training it in order to sharpen it up.