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Artificial Intelligence (AI), Big Data, Machine Learning, Bots, Predictive Maintenance. These are all terms that have become buzzwords in the tech community and have spilt over into other industries as the world awaits the next wave of technology.

Anyone who is interested in Artificial Intelligence, and specifically Artificial Intelligence within the Microsoft Stack, will quickly discover that it is a deep and complex world that requires specific knowledge in Azure. Making sense of the frameworks, infrastructure, services, algorithms, tools, apps, etc. can be overwhelming at first.


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In this post, I will give an overview of AI in relation to Dynamics 365, and show some practical examples of how you can leverage the capabilities for your own business. I will do this by answering the following questions:

  1. Why is Artificial Intelligence so important?
  2. How can Microsoft help you to implement AI
  3. How can it be utilized in your business?

I am not intending to make this a comprehensive post on each AI tool available for Dynamics 365, but I hope this gives you a broader understanding of what Microsoft is doing within Dynamics 365 and Azure. This can help with developing an AI strategy in your business or use the tools available to accelerate your existing AI Strategy.


1.  Why is Artificial Intelligence so important?

Ten years ago, there was much excitement about the iPhone’s potential. At the time, we didn’t understand just how much it would change the way we communicate and interact with technology. The same can be said of the Cloud. Most people heard of it, and some understood it, but most didn’t know how it would change our lives outside of having a “hard drive in the sky.” It is only in retrospect that we see how cloud services have gradually changed the way we consume data. A good example is how more services are becoming subscription-based. Streaming music and TV series, subscribing to your favourite software (e.g., Microsoft Office), are all realities today because cloud technology made it possible.

Why is Artificial Intelligence so relevant today? It’s not because it has not been relevant until now, it’s because it has not been possible. To prove this, let’s look at a definition of what AI is if you google it:

“The theory and development of computer systems able to perform tasks normally requiring human intelligence, such as perception, speech recognition, decision-making , and translation between languages.”

Tasks such as visual perception, speech recognition, decision-making, and translation all have one thing in common: they require large amounts of computational power. Most companies could not afford the needed computational power, but now can thanks to the cloud.

Just like ten years ago, we sit on the precipice of a world of possibilities. Tech giants are all hard at work creating services that can be used by businesses. Meanwhile, these same businesses are rapidly figuring out ways to optimize their operations by using those systems. No one can claim to have it perfectly right just yet, but we are making tremendous strides.


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2.  How can Microsoft help you to implement AI?

For most of us, the thought of building software to aid visual perception, speech recognition, decision-making, machine learning, and translation would end our journey into AI then and there. But Microsoft has made these jobs available as a service. This means you can simply plug these services into your business logic, and allow Microsoft to do the heavy lifting for you. Let’s have a look at how Microsoft is solving these problems:


The Microsoft AI Platform

The Microsoft AI platform can be broken down into three parts: Infrastructure, Services, and Tools.

AI Infrastructure

As you would expect, everything is built on the Azure platform. Microsoft’s Azure services mean that you can easily provision, maintain, and scale solutions. Another great feature which needs emphasizing is having all these services available as a trial. You can provision and test solutions for your business without incurring a significant investment cost before even ascertaining whether it will work for your business or not.

The AI Infrastructure has two elements: AI Compute and AI Data. AI Compute provides a variety of services to manage your computational requirements, and AI Data provides services for the storage and accessibility of Data. Big Data and Computational Power go hand-in-hand as you cannot analyze big datasets without access to large amounts of computational power.

AI Services

The services available on the platform can be broken down into three areas: Cognitive Services, Machine Learning Services, and the Azure Bot Service.

Cognitive Services

This enables visual perception, speech recognition, and translation.

Machine Learning Services

This facilitates advanced decision-making capabilities, and for applications to self-learn and auto-correct based on data received. A good example is how Microsoft is using machine learning to improve the accuracy of Sentiment Analysis in social media.

Azure Bot Service

Combined with Natural Language processing, the Azure Bot Service allows businesses to easily create Bots that integrate with Apps such as Cortana, Office 365, Skype, Slack, Facebook Messenger, and more are being added to the service regularly.


AI Tools

Tools connect both Data and Services. I won’t go into detail but will mention that this is where the majority of the “custom” work will be done to bring the Services, Data, and your business logic together.


Artificial Intelligence and Big Data in dynamics 365


3.  How can it be utilized in your business?

Now that you have a broad overview of how Microsoft is facilitating Artificial Intelligence, let’s look at how this relates to Dynamics 365, and specifically, your business. To answer this question, I will focus on two areas:

  1. What is Microsoft doing?
  2. What can you do?


1.    What is Microsoft doing?

Over and above the services, tools, and infrastructure, Microsoft is also working to incorporate AI into Dynamics 365. Here is a summary of how AI embeds into Dynamics 365:


  • Product Cross-Sell recommendations. Dynamics 365 will make recommendations based on what other customers are buying, and the purchase history of the customer.
  • Auto-updating of Client record information based on Social Insight. Using LinkedIn Sales Navigator, client records can be kept up-to-date from the information available on LinkedIn.
  • Predictive Scoring. Using Dynamics 365 Customer Insights, you can configure predictions on records such as opportunities at risk, leads likely to qualify, cases that may breach their SLA, etc.


  • Auto-suggestions of Knowledge Base Articles. Given the problem that is defined, Dynamics 365 will make suggestions of Articles that are used to resolve similar cases.
  • Case-topic Analysis. This is a preview feature that analyzes Case Topics to provide insight into what problems customers are regularly logging for cases. This is useful for enhancing the Knowledge Base.

Project Services

  • Resource Scheduling Optimization. This functionality is handy not only to optimize scheduling to reduce travel time but can also schedule activities on a recurring basis.

Field Services

  • Resource Scheduling Optimization. As with Project Services, this functionality can not only optimize scheduling to reduce travel time but also schedule activities on a recurring basis.


2.    What can you do?

Larger companies are using Artificial Intelligence to create virtual agents. These are agents that can act as the first line of support (in the form of a chat-bot) for either Customer Service or Sales.

Another useful distinction is to identify virtual jobs. You do not necessarily have to create an agent that can do everything a typical employee would do, but only certain tasks that are easy to replace with Artificial Intelligence.

Here’s what you can do in your business:


  • Campaign automation with machine learning. Using Customer Insights, machine learning can automatically segment customers from their interactions with your business across all departments.
  • Targeted Marketing with Lead Scoring. Using Customer Insights, Leads can be scored and targeted appropriately.


  • Predictive Forecasting. An area that is currently and will continue to receive a great deal of attention. Microsoft has a released a case study on this, and it is worth pursuing for your business.


  • Chatbot. There is a great tool called CafeX that allows you to enable live chat that easily integrates with your website or customer portal. Using the Bot Framework, you can integrate the live chat with a chatbot.

Field Service

  • Predictive Maintenance with IoT. Enabling IoT on your machines with products that customers buy allows you to monitor and predict more effectively when to schedule maintenance.


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Artificial Intelligence is becoming part of everyday life whether we are paying attention to it or not. Operating Systems and Software Applications, in general, are going to get better at using AI to either help users get jobs done more quickly or complete them entirely unassisted. For the small to medium-sized company, Artificial Intelligence will adopt reactively.

For Larger organizations looking to remain competitive or stay ahead of the curve, AI will need to be part of their strategy. “Training” one chatbot to perform customer service tasks makes business sense if the virtual agent can service thousands of customers simultaneously without needing a lunch break. If your business is small and remains “high-touch” then it may not be required. Regardless of the size of your business, don’t dismiss AI as something that is a fad. It is very much here to stay.


Written by The Sherweb Team Collaborators @ Sherweb

As a value-added cloud solutions provider, Sherweb is dedicated to providing more for its partners, direct customers and extended network. The Sherweb Blog is just one example of how we make this happen, and our team members frequently collaborate on content to ensure it's as beneficial as possible for our readers. If you like what you see here, we strongly encourage you to subscribe!