Microsoft Copilot - How should business start the AI journey safely and cost effectively?

A structured approach that prioritises strong foundations in security and data governance, alongside strategic, measurable adoption.

Here's how businesses can begin their Microsoft Copilot journey with safety and cost-effectiveness in mind:

Phase 1: Getting Ready Safely with Strong Foundations

1. Define business objectives and AI use cases before implementation. It's crucial to identify the key challenges and opportunities AI can address, aligning your AI strategy with your organisation's business goals and desired measurable outcomes. Focusing on high-impact areas first will help maximise the return on investment. For example, AI tools can enhance customer support, boost productivity, strengthen security and compliance, and improve data analytics.

2. Review security and data settings of Microsoft Copilot. Copilot is designed to inherit existing Microsoft 365 data and security permissions and highlights the importance of having solid content management practices and data governance in place before rollout.

   
   

   • Audit Existing Policies: Work with AI Help to review current data and security policies, including data access conditions, retention controls, and sensitivity labels. These policies can be centrally managed and applied across the organisation.

   • Leverage Microsoft Purview: Utilise Microsoft Purview for integrated data security, governance, compliance, and privacy across your data estate, including protecting data in pre-built and custom generative AI applications. It also provides tools for AI activity insights, ready-to-use policies to safeguard data in AI prompts, and compliance controls for optimal data management.

   • Implement Zero Trust Security: Microsoft 365 E3 (and above) adheres to Zero Trust principles, transitioning from a "trust-by-default" to a "trust-by-exception" approach, which includes Multi-Factor Authentication(MFA) and continuous access checks.

   • Understand Data Storage and Privacy: Copilot data stays within a business's Microsoft 365 service boundary; however, the company must check its data processing commitments and data boundary rules. User prompts and responses are considered your data when managed through Microsoft Entra and can be accessed through eDiscovery and legal holds. Copilot data is encrypted during transmission and is not used to train external LMs.

   • Address "Shadow AI": With rapid user adoption, unsanctioned AI app usage ("shadow AI") heightens the risks of sensitive data leakage. New controls such as AI web category filters in Microsoft Entra internet access, assist in enforcing detailed access policies, and Microsoft Purview browser Data Loss Prevention (DLP) controls stop sensitive data from being typed into generative AI apps.

   
   

3. Create an AI Council. Many organisations establish cross-functional AI councils to oversee and guide the development, deployment, and evaluation of AI solutions, ensuring compliance with relevant regulations and ethical standards. This council should include enablement, change management, an executive sponsor, and a risk management expert.

   
   

4. Establish responsible AI principles and frameworks by ensuring a committed, accountable, and ethical implementation of AI.

• Build a responsible AI standard: The type of framework that offers practical guidance based on principles of fairness, reliability, privacy, security, inclusiveness, transparency, and accountability. Use to identify, measure, and manage risks throughout the AI development cycle.

• Trustworthy AI: Success relies on the reliability of AI tools, which is why your framework for creating and rolling out generative AI should be built on three pillars: security, privacy, and safety.

• Secure Future Initiatives: Prioritise cybersafety through this initiative, grounded in principles of designing products with security first, ensuring security features are mandatory, and continuously enhancing measures to meet evolving threats.

Phase 2: Cost-Effective Implementation and Adoption

1. Begin with pilot programs and purposeful seat assignments.

   • Pilot Program: Begin with a small test group or department to identify specific use cases, gather feedback on usability and efficiency, and refine the method before rolling it out fully. This iterative process helps teams build confidence and showcase value.

   • Intentional Seat Assignments: To maximise business impact, focus Copilot licences on two or three key areas of the business instead of spreading them thinly. Target heavy users of Microsoft 365 products. Many early adopters began their careers in customer service, sales, marketing, HR, and finance, where teams often spend a significant amount of time on repetitive tasks and data analysis, summarising meetings, and generating content.

     
     

2. Provide Ongoing Training and Support

   • Build New Habits: Effectively managing change is crucial; Copilot should be viewed as a new way of working, not merely a new technology. Management should assess attitudes and expectations, emphasising that users are "in the driver's seat".

   • Ongoing Training: Provide continuous training as users personalise Copilot. Prompting is a new skill, and better inputs lead to better outputs. Resources like Copilot workshops, and Copilot adoption guides can support this.

   • Foster Community: Promote collaboration and knowledge-sharing through user groups (e.g., group chats) to build a vibrant learning ecosystem. Find "AI Champions" or early adopters to lead by example and motivate others to use the technology more widely.

     
     

3. Leverage Microsoft's AI Ecosystem

   • Microsoft 365 Copilot: Copilot is integrated into familiar apps like Word, Excel, Outlook, and Teams, it provides document creation, data analysis, and communication capabilities. It supports employees to focus on high-value tasks by simplifying routine work.

   • Copilot Chat: Provides a basic AI solution with free AI chat powered by GPT-4 and web grounding. Some agents are available at no extra cost, while those accessing SharePoint are charged based on usage. This offers a cost-effective entry point.

   • Copilot Studio: A low-code tool that enables you to extend Microsoft 365 Copilot with custom agents, plugins, or connectors, integrating Copilot with business data and automating workflows.

   • Microsoft Fabric: The data analytics management system infused with AI that combines OneLake data storage, data engineering, data integration, analytics, and business intelligence.

   
   

4. Measure Success and Refine

• Quantify Impact: Measure key performance indicators such as time saved on manual tasks, increased customer satisfaction, faster security response times, and better data-driven decision-making.

• Use the Copilot Dashboard: Microsoft Copilot Dashboard offers continual visibility into AI's influence on productivity by tracking usage and adoption with real-time data and insights. This helps leaders identify where Copilot adds value and where enablement strategies can be enhanced.

• Celebrate Successes: Publicly recognising efforts and sharing success stories encourages further adoption and engagement.

  
  

By following these steps, businesses can safely navigate their Microsoft Copilot journey, ensuring data protection and ethical use, while also maximising their investment and achieving significant productivity improvements and cost savings.

Start today, AI Help for business is here to assist you in navigatimg this journey, and you can start now by booking a session with an AI expert here.