What about AI in D365FO?

What about AI in D365FO? If you work with D365FO, I think you surely have asked yourself already this question. Also did I. At the moment more and more information becomes available and I thought it would be good to summarize some of these information and share in an article.

Because of my Finance background, in this article I will mostly (but not completely) focus on what I have found related to Dynamics 365 Finance. One of the sources that helped me a lot is the webinar 'Optimize Financial Operations with AI-Infused Processes', given by Mark Traverso Shivam Pandey and April Olson . Highly recommended to watch this webinar! At the bottom of this article I have added a list of other sources where you can find more information.

See this article as a first introduction. You will not find in detail how everything works, because a lot can't be used in general already. But I hope it will give a picture about (coming) possibilities and the way AI will takes place in D365FO so that you can form an image and have a starting point to delve further.

The place of AI in D365 Finance

Financial processes at the moment are still very manual and reactive. But every repetitive process has the opportunity to be automated. Focus in D365 Finance will be related to customer payments, intelligent budget and forecasting and Invoice automation:

With AI the purpose is to save time for employees to give them the ability to do more strategic activities. These activities can be driven by actual real intelligent data and based on the way AI can move through information quickly and learn you have information much earlier than you would have known this in the past.

Example 1: Customer payments insights

Last year I wrote about a new feature 'Collections coordinator'. In that article I already referred to the Customer payment insights that would come with AI. In D365 Finance you can use AI for these insights. First you are going to create a prediction model:

Based on this AI model the 'Customer credit and collections' workspace will be extended with new tiles related to customers and transactions predicted to be paid late:

If you click on these tiles you will get the detailed information. By the transactions predicted to be paid late you can see the predictions related to the payments of the customer:

Where in the old situation most of the customer invoices where followed up when the due date was already reached, now based on this AI prediction you have the option to get ahead of this and take action faster to get your money on time.

Example 2: Cash flow forecast

One of the most important things for a company: having a healthy cash flow. Based on AI possibilities a new overview will become available:

This dashboard has several tabs with information. for example the 'Cash forecast' tab where based on AI you get a longer time stamp of your cash development:

Also options will come to create multiple snapshots of forecasts (with information from D365 Finance or other sources) and compare this with the actuals:

Example 3: define organizational rules to default financial tags

More then a year ago I wrote an article about Financial tags. Financial tags where brand new at that moment. You can already use them in D365 Finance. The values needs to be entered manually, but an option will come to define rules for defaulting financial tags values. AI can be used to create these rules:

I think having these rules available will be the gamechanger for financial tags! Because with automatic filling the added value of financial tags will be bigger and the adoption to use will become more easy.

Example 4 (not Finance): Confirmed purchase order changes

It is not in Dynamics 365 Finance but based on D365FO also the workspace 'Confirmed purchase order changes' is worth to be mentioned. This is a workspace where the impact of changed purchase orders on the process will be presented and where you can do actions based on this AI generated information:

• Send AI generated emails or messages to vendors.
• Ask CoPilot for suggestions how to solve an expected problem based on a changed purchase order (for example when the delivery date has been moved on to a date when the purchase order already should have started):

What will be the impact for using AI in D365FO?

Above I have written about some examples where AI will come into D365FO. I think more and more AI will impact our way of working with D365FO. When you ask me about my first impression about the impact of AI in relation to D365FO, three areas comes up in my mind immediately:

1. Repetitive tasksAI will be used more and more to do repetitive tasks. Where AI can learn quickly repetitive tasks can be done in D365FO, like creating emails to customer for open due invoices or making posting proposals.
2. PredictionsAI will be used more and more to make predictions. In the examples above related to Customer credit and collections and Cash flow you can already see that AI can analyze and structure the D365FO data (including data from other sources) which makes that predictions will become available much quicker and more accurate then before.
3. Using relevant information to get smart outcomesThe options to use Copilot for help will give users much more possibilities to use the data of D365FO to resolve unexpected situations more quickly. See for example the Confirmed purchase order change options written above, where you can chat with the D365FO data to get a solution for a problem. With the possibility of being able to add your own files that AI may use in this option (for example the specific D365FO work instructions of your company) on top of what is common available on Microsoft Learn also much more information will be available to get help by using D365FO in common.

Prepare for AI in D365FO

It will not take long before we are all going to use AI in D365FO. Will everything be great and can everything by solved then? I can't tell. But in the webinar Optimize Financial Operations with AI-Infused Processes that I mentioned above, one of the sheets ties in with what I often discuss with companies and consultants: data quality!

Data quality and improving data quality is an underestimated topic. But the quality of your data will be crucial for the quality of your experiences when it comes to use intelligence in automating or optimizing processes. Of course we already knew that data quality in ERP software like D365FO is highly important, but based on the many current possibilities for human intervention my experience is that a lot of companies still accept low data quality. But what if AI will created automated proposals in D365FO based on your low data quality? What if conclusions will be made based on incorrect D365FO data?

In the digital feedback loop from Microsoft you can see that Intelligence and Data is the center between all applications working together:

High data quality is key, also in D365FO. Do you really want to use the benefits of AI and prepare? Start working on optimizing your data quality already. Appoint ‘data stewards’ in your company that will be responsible for monitoring and improving data quality. Organizations needs to adapt a way of working where data quality is crucial and make sure al employees will have this focus as well. It is not a coincidence that one of the first lessons in the Learning Path 'Implement Copilot for Microsoft 365' is to prepare your data: https://lnkd.in/e3JqGqUj

Sources

I hope this article gives you a good start about what kind of AI will come in D365FO in the next future. Do you want to know more? Here you can find a list of sources that I have used:

• The webinar mentioned in the beginning of my article (too important to not share again, if you work with D365 Finance you have to watch this to get an impression).
• A video created by Drew Lencsak with explanation about the 'Confirmed Purchase orders with changes'.
• The Microsoft Learn page about organizational rules to default financial tags.
• The Microsoft Cloudblog about AI and demand planning, including a video about Demand planning and the Confirmed purchase orders with changes.