One barrier to AI evolving beyond a conversational tool into a truly impactful enterprise solution is its lack of deep insights, limited access to relevant data, and insufficient understanding of enterprise-specific processes and workflows. Simply providing unrestricted access to systems like SharePoint does not address this gap.
Additionally, users often struggle to articulate detailed support requests, submitting vague descriptions such as "computer crashed" or "account not working," which complicates the AI's ability to diagnose and resolve issues effectively.
First-level user support teams dedicate significant time and resources to performing basic checks, such as verifying whether an account is enabled or expired, properly provisioned, or if a device is correctly enrolled in Entra/Intune with policies applied, and confirming membership in default distribution lists.
Although access to this data is typically restricted to support teams, these routine tasks often delay resolutions and frustrate users, as many issues could be quickly resolved or at least clearly communicated with better access and automation.
Enhancing response times and elevating the customer support experience does not require traditional lateral scaling; instead, integrating intelligent AI solutions is the key to transformative efficiency.
Imagine an AI model with access to relevant IT data, operating 24/7, capable of collecting user inputs, including screenshots, to accurately identify issue types—whether an account problem, device issue, or a simple password reset. Using Azure Functions, the model could securely retrieve IT data from the tenant to inform its decisions. For straightforward issues, the AI could directly provide solutions to the user. For complex cases requiring escalation, the AI could generate a detailed ticket for Tier 2 support, including an accurate description of the issue and initial troubleshooting steps, streamlining the resolution process.
The most accessible approach to begin developing this AI IT support bot is to create a Proof of Concept (PoC) using Copilot Studio, Power Automate, and Azure Functions. In the future, further development could leverage Azure AI Foundry to enhance the bot’s capabilities with more advanced, enterprise-tailored AI models and scalability.
Featured image generated with Grok Imagine
