Generative AI is transforming how we teach, research, work and serve our community. At Mississippi State University, every employee plays a vital role in shaping the future of AI education and practice. You do not need to be an AI expert to contribute — your curiosity, willingness to learn, and openness to new ideas are what drive innovation at MSU.
Success with AI is not about simply adopting new software or attending routine training. It’s about fostering a culture where learning, experimentation, and collaboration thrive. Every employee is empowered to explore AI tools, ask questions, share experiences, and support one another. Together, we build an environment where innovation flourishes and our vision becomes reality.
Continuous upskilling is essential as AI and machine learning become integral to our operations. Each of us must take ownership of our learning journey, seek out opportunities to grow, and help others do the same. Consider these guidelines as a living framework, designed to support you as we accelerate MSU’s leadership in AI.
Key actions for all employees
1) Commit to continuous skill development
- AI and GenAI will become a natural part of daily work.
- Seek out training opportunities and participate in peer learning.
- Share what you learn and help others grow.
2) Use approved platforms and protect data
Only use MSU-approved tools for Moderate- or High-Risk data.
Approved tools:
- Microsoft 365 Apps, including Copilot (login with netid@msstate.edu)
- Gemini (login with netid@msstate.edu)
- NotebookLM (login with netid@msstate.edu)
- Claude (request and purchase MSU enterprise account, login with netid@msstate.edu)
- Webex AI Assistant
All other AI tools should be treated as public or open platforms and are not suitable for MSU data designated as High-Risk or Regulated. Examples of public or open platforms include:
- Grok, Perplexity, other
- Cloud environments (AWS, Nvidia, Google CoLab, or others)
Do not use READ.AI for recording and transcription of meetings. Use MS Teams or Webex for this purpose. If you have used Read.AI and can’t clear it from your computer, please submit a ticket to ITS for help.
Know your data — classification and protection
High-Risk / Regulated Data
- Examples: FERPA, HIPAA, GLBA, or other highly controlled data.
- Requirement: Request approval before using any AI platform with personally identifiable information (PII) that falls into the FERPA, HIPAA, or similar category.
- Restriction: Use completely de-identified information unless otherwise approved.
- Example: You should not upload student work with names to an AI tool to help with grading. You should not upload employee names and salaries for analysis.
Moderate-Risk Data
- Examples: Data accessible only by logging in with your MSU NetID.
- Requirement: Use only in MSU enterprise-licensed tools.
- Restriction: Requires approval before use in any non-MSU platform.
- Example: You may use Copilot, Gemini, or Claude (must be logged in with NetID) to summarize internal financial documents or internal communications. You may use Teams features to record and transcribe meetings.
Low-Risk / Public Data
- Examples: Data already available to the public.
- Requirement: May be used in public tools; adjust tool settings to prevent training of large language models on your input.
Read the AI Data Security at MSU article for more detail. It is impossible to anticipate every possible use. If you are uncertain, contact the Chief Information Security Officer at security@msstate.edu.
3) Require human review before public release
- AI-generated content must not be made public without human review.
- No automated publishing by AI agents without approval.
- All public-facing website AI chat assistants should be approved before development and again before deployment.
4) Ensure quality, integrity, and address bias
- Verify facts, references, and citations.
- Check for bias in language.
- Employees are responsible for quality and integrity.
- Disclose AI assistance when appropriate and be truthful about use when asked.
- Set personal goals for learning AI tools.
5) Follow research and compliance requirements
- Follow agency-specific guidance, publisher guidance, and MSU policies.
- Consult the Office of Research Compliance and Security for questions.
6) Participate in training and capacity building
- Attend MSU workshops, online training, and vendor modules.
- Join the MSU AI Community
- Join peer learning sessions and departmental Teams.
Guidance for employees in hands-on, operational roles
Teams such as facility maintenance, landscaping, custodial services, and other hands-on roles may not immediately see a direct connection to AI adoption. There is no expectation for rapid or widespread adoption of AI tools where they do not naturally fit. Your contributions are essential to MSU’s success, regardless of the pace of technology change.
If new technologies emerge to support your work, MSU will provide guidance and support. All employees are encouraged to participate in university learning opportunities — no one should feel left out if they want to learn.