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Home Discover our latest blogs Discover our latest blogs Navigating data, security and compliance challenges in Microsoft 365 Copilot adoption
Digital Workplace
6 minutes reading

Navigating data, security and compliance challenges in Microsoft 365 Copilot adoption

The integration of AI tools like Microsoft 365 Copilot into workplaces around the globe has sparked excitement and caution alike. Employees, eager to improve productivity, often use AI tools on work devices, inadvertently exposing corporate data to open models. This creates significant challenges for businesses striving to maintain control over sensitive information. As organizations seek managed solutions, the focus on secure AI usage has never been greater.

Pieter van Dieren

Pieter van Dieren

January 07, 2025

For IT professionals and decision-makers, the question isn’t merely about the productivity merits of adopting AI, but about ensuring its safe and compliant implementation. This blog dives into the security and compliance challenges of AI and explores practical ways to address them.

Data security issues with AI integration 

Integrating AI tools like Microsoft 365 Copilot into organizational workflows brings unique and complex challenges. Companies often struggle with issues such as oversharing of information, poor response quality, and unauthorized access to data. Addressing these challenges is crucial to avoid unintended consequences that could harm an organization’s reputation or market position, or even lead to regulatory violations.

According to the Gartner survey (2024), 57% of organizations opted for limited rollouts to low-risk or trusted users in their efforts to mitigate initial security risks. Additionally, 40% of organizations experienced significant delays in rolling out Microsoft 365 Copilot due to concerns about security and oversharing. The 2024 Forrester report highlights similar challenges, noting that unauthorized use of AI tools and shadow IT increases the risk of data breaches and noncompliance, and stressing the need for robust governance frameworks. All this underscores the importance of carefully assessing possible vulnerabilities when integrating AI tools, especially when sensitive data is involved. Potential concerns include:

Risk of oversharing and unauthorized data access: Oversharing and unauthorized use of AI tools are significant concerns, with over 60% of Gartner respondents identifying risky default configurations during deployment. For example, an employee working with a sensitive spreadsheet containing salary information may unintentionally expose data through Microsoft 365 Copilot, raising the risk of sensitive information being included in AI-generated outputs, which could harm the organization’s reputation or violate privacy regulations. Strict data-sharing settings and protocols are essential to mitigate these risks. 

Poor response quality and inaccurate content: Microsoft 365 Copilot can produce poor-quality responses or ‘hallucinations’ (answers that are misleading, incorrect or fabricated) due to outdated, missing or redundant content. Gartner found that 52% of respondents had experienced this issue. Establishing high information management maturity ensures that AI tools work with accurate, complete and current data, reducing the risk of incorrect outputs. 

Deployment delays due to security concerns: Security and data governance concerns also contribute to deployment delays. Gartner found that 40% of organizations experienced delays of three or more months due to concerns about data security and oversharing risks. Addressing these issues early is crucial to streamline adoption. 

Low information management maturity: Only 27% of Gartner respondents reported high information management maturity. Without well-established processes, tools, and policies for data governance, data quality, information security, and lifecycle management, the likelihood of hallucinations and data exposure increases. Investing in improving data governance is essential before fully integrating AI tools like Microsoft 365 Copilot. 

Best practices for AI security

Ensuring the secure adoption of AI tools like Microsoft 365 Copilot requires a proactive approach. Organizations must recognize that the starting point will vary greatly depending on their specific needs and existing security processes. No organization has everything perfectly in place, and the initial steps taken can differ significantly from one customer to another. So a flexible and responsive approach is key to effectively managing risks and adapting to diverse requirements.

In addition, data security has been largely overlooked in recent years, and this is now becoming painfully evident as organizations implement Microsoft 365 Copilot. To mitigate these issues, organizations need to consider several key practices to align AI integration with compliance requirements:

  1. Document sharing settings: Identify which data is sensitive within your organization, and then review document sharing policies to ensure that this information remains controlled. Establish clear guidelines for using AI with different types of documents. 
  1. Permission models: Implement robust permission models that confirm only authorized users can access critical data. Ensure AI follows these permissions to limit the risk of unintended exposure. 
  1. Information protection policies: Align information protection policies with industry security standards. Use tools to classify and safeguard sensitive data, establishing clear data handling and storage protocols. 
  1. Data Governance Tools: Utilize data governance tools like Microsoft Purview to help classify and protect sensitive information. This includes building workflows that ensure secure data storage and management while streamlining compliance efforts. 

These best practices form the basis for a secure AI strategy, helping organisations minimise risks while benefiting from AI capabilities.

The importance of user adoption 

Beyond technical measures, developing a culture that promotes data security awareness is crucial. User adoption plays a critical role in successfully implementing data security measures. Essentially, it means ensuring that employees: 

  • Understand the measures: Employees need to know what they are being asked to do in terms of data security protocols and tools. 
  • Understand the purpose: It's crucial to explain why these measures are necessary – what the potential risks are and how these measures protect the organization and its data, as well as how they fit into the broader goals of compliance and security. 
  • Are engaged: When employees see the value and purpose behind security best practices, they are more likely to follow them correctly and consistently, reducing risks and improving outcomes.

Security readiness for M365 Copilot assessment 

One effective approach to ensuring secure AI usage is conducting a thorough security assessment. A security assessment can help organisations review their data sharing settings, permissions, and protection policies, allowing them to better understand their data access environment. Through this assessment, organisations can identify who potentially has access to sensitive data both inside and outside the company, and ensure that data handling practices align with security standards through robust protective measures. 

An experienced partner for a lasting solution 

In addition to initial assessments, organizations may benefit from working with an experienced partner that provides lasting solutions for data security and governance. Such a partner can help establish policies that streamline data governance, support compliance efforts, and ensure secure data storage and management. 

Beyond technical implementation, it’s also important to develop strategies that align with your particular goals and challenges. A holistic approach ensures that businesses are equipped not only to manage current risks but also to develop a strategy and culture around AI that allows them to adapt to emerging opportunities and threats as technology evolves.  

An essential part of this process is fostering user adoption by educating employees about the importance of data security, especially when starting to classify sensitive data. Clear communication and specific adoption programs help employees understand why these measures are necessary, ensuring the organization gets the most out of tools like Copilot while maintaining a "secure by default" foundation. 

An experienced IT services partner can provide guidance on integrating AI in line with your business objectives, as well as creating frameworks for ethical AI use, employee training programs, and governance structures to ensure ongoing adaptability and compliance as AI technologies and regulations evolve. 

Managing the Microsoft 365 Copilot transition with Cegeka 

When it comes to adopting AI tools like Microsoft 365 Copilot, partnering with experienced security providers can significantly ease the transition. Cegeka offers a Microsoft 365 Copilot security assessment, professional guidance, and ongoing managed solutions that help organizations adopt AI effectively and securely. 

Cegeka’s managed services ensure a smooth transition by focusing on secure and compliant integration. Rather than overhauling existing systems, Cegeka’s experts work in close cooperation with organizations to help them to integrate AI tools like Microsoft 365 Copilot effectively within their current frameworks, as part of a broader digital transformation. By simplifying the process of transitioning to AI and providing ongoing managed services, Cegeka helps organizations advance while gaining the competitive edge and peace of mind that comes from knowing that the experts are in your corner.

In close cooperation 

In developing a best-fit strategy for your unique situation, we work closely with your team from the outset. Our collaboration begins with a security and compliance workshop, in which we: 

  • identify your objectives and strategy regarding data security, privacy, and compliance 
  • show how you can detect, investigate, and act on data security and privacy risks 
  • demonstrate ways to accelerate your compliance journey with Microsoft technologies such as Purview 
  • provide actionable next steps based on your needs and objectives, developed in dialogue with your stakeholders 

We then conduct a data security review, engaging with your team to understand your priorities, initiatives, and the key factors shaping your compliance strategy. Together, we identify potential or actual organizational data risks, delve into the challenges posed by dark organizational data, and examine how insider actions may contribute to breaches. We then analyse these findings collaboratively, providing insight into where to begin and discussing Microsoft’s approach to data security and compliance. This process establishes clear, actionable steps that we work on together. 

Cegeka can remain involved long-term to support your organisation as you implement and evolve your data security and compliance strategy.

Conclusion 

Innovation that comes at the risk of data security is a risk no organisation can afford to take. However, with the right strategies and expertise, the challenges of adopting AI tools like Microsoft 365 Copilot can be effectively managed. By focusing on compliance and security, organisations can confidently embrace AI while mitigating risks. Partnering with an experienced security provider like Cegeka equips organisations to identify and mitigate risks associated with AI implementation, implement protection and governance best practices, and catalyse their AI evolution. In an era of rapid digital transformation, companies that prioritise secured data and AI-enabled workflows will be best positioned to thrive in a future full of innovations that have yet to be imagined. 

Pieter van Dieren

Pieter van Dieren

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