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How it’s transforming business processes
Business process automation has been a thing for quite some time now, and it has helped many companies improve their operations and transform the way work is done. When embedding AI into business processes became possible, automation evolved over the years from structured development logic to a more dynamic, robust approach.
Why is AI automation transforming business processes?
First things first, let’s acknowledge that one of the main reasons AI has become a key part of automation is all the hype that came with large language models and agents.
All industries have always had some type of pressure to operate faster, more efficiently and smarter, and with artificial intelligence being mentioned everywhere, this pressure is now impossible to ignore.
Automation has been helping industries to replace manual and repetitive tasks for decades, and when adding artificial intelligence features to workflows, AI brings a whole new layer of possibilities when it comes to automation:
- Read data from unstructured documents like contracts
- Extract meaning in an image
- Classify emails or customer feedback
- Read data from invoices or receipts
- Faster processing times with automatic decision-making
What makes AI automation different from traditional automation?
Traditional automation requires every trigger, condition, and action to be defined in advance. It works well when processes are predictable, but when more complex business cases try to be solved with this approach, it has a ceiling. Here is when AI automations come into play: add context-based capabilities, decision-making and adaptability.
| Traditional Automation | AI Automation |
Driven by | Pre-defined rules | Goals and context |
Exception handling | It needs to have been configured for exceptions | Adapts to different contexts and inputs |
Learns over time | No | Yes |
Handles unstructured data | Limited | Yes (documents, emails, images) |
Logic | Every scenario pre-mapped | Guided by intent and outcomes |
Best for | Repetitive, predictable tasks | Complex, context-based actions |
Key Benefits of automating processes with AI
Examples of using AI in automations can apply to many processes and departments, such as:
- Marketing and sales: automatically classifying leads and sales opportunities.
- Finance and accounting: extracting data from accounts payable invoices and posting invoices automatically into an accounting system.
- Compliance: scan and analyze all types of documents, including unstructured data such as contracts, PDFs and images.
When implementing AI into automations companies can see the following benefits:
- Increased efficiency
- Improved accuracy
- Adaptability
- Freeing teams for higher-value work or as we prefer to call it: discovering the joy of automation!
AI Automation in the Microsoft Power Platform ecosystem
AI can be integrated in Power Platform automations through different tools: AI Builder, Microsoft Foundry (Azure Cognitive Services, Agents, Azure Open AI) and through third party apps or systems.
AI Builder is the official Power Platform tool to use artificial intelligence capabilities in Power Automate. From the AI Builder, developers can leverage:
- Models for common business scenarios that are ready to use (like invoice data extraction, receipts or business cards)
- Creation of custom models that users to automate document processing of their own forms.
- Custom prompts to perform different types of actions that can range from classifying emails to extracting data from unstructured contracts.
Learn how you can integrate AI in Power Automate in our blog dedicated to this topic.
Discover the joy of automation
Whether you’re taking your first steps into AI automation or looking to take what you’ve already started to the next level, we can help you with our Microsoft Power Automate consulting services and Copilot Studio integrations.
