5 steps for organizations to get started with AI
1. AI PRODUCTIVITY:
Begin your AI journey by activating AI features already available in your Microsoft suite. Microsoft Copilot integrates directly with Word, Excel, PowerPoint, and Outlook, providing immediate value without requiring new infrastructure. Users can use Copilot to draft documents, analyze spreadsheet data, create presentations, and summarize email threads. These tools can be deployed iteratively across departments, starting with power users who can become internal champions for the rest of the organization.
2. WORKFLOW & DOCUMENT INTELLIGENCE:
Some of the quickest areas of ROI in AI comes with exploring. Identify repetitive, rule-based processes that consume significant employee time and automate them using AI-powered tools. Microsoft Power Automate can handle document processing, data entry, approval workflows, and integration between different business systems. Using Power Platform's AI Builder, you can utilize AI models to detect document types and extract data to drive these automated workflows, which can connect to Microsoft SharePoint, Microsoft Teams, and many other third-party applications.
3. AI STRATEGY & GOVERNANCE:
Create a foundation for AI success by establishing clear data governance, ethical AI guidelines, and implementation standards. This includes data quality assessments, privacy compliance, and defining acceptable AI use cases for your organization. This can consist of leveraging Microsoft Purview for data discovery and classification across your M365 environment and utilizing the Microsoft 365 Security and Compliance Center to enforce AI governance rules and monitor compliance across all AI implementations.
4. LAUNCH AI PILOTS:
Select specific business challenges and use cases where AI can deliver measurable value with minimal risk. Customer service or internal facing chatbots, document summarization, or predictive maintenance are excellent starting points that can provide a clear ROI while building organizational AI experience. Plan to start small with several experiments before determining which use cases and AI solutions should proceed to the pilot stage.
5. BUILD INTERNAL EXPERTISE:
Invest in developing your team's AI literacy through structured training programs, workshops, and hands-on experience with AI tools. Create centers of excellence that can guide AI adoption across different departments and maintain best practices. Eventually, the input and experiences of these teams will create a cycle of evaluation and updating of your organization's AI strategy and governance plans.
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