ITS AI Hub [Mockup082026]
Approved AI Services
Use this tool matrix to quickly compare USF-provided AI solutions and find the best fit for your needs. Note that in some cases, tools are licensed for specific areas, so be sure to check the data types each tool is approved for, as detailed below the matrix.
AI Use, Security, and Acquisition at USF
[placeholder text] At USF, we support using AI to enhance learning, research, and operational efficiency. To ensure safety and integrity, all faculty, staff, and students must adhere to the University's Guidelines for Responsible Use of AI covering data security, privacy, compliance, copyright, and academic integrity. Before adopting new tools or logging into university systems, please review our account credential policies and acquisition approval workflows below.
USF Credentials
If you're planning to use your USF credentials (username or email) to create an account in a free or paid subscription, you must adhere to these guidelines.
Key Factors To Consider When Using AI-enabled Technologies
DATA SECURITY AND PRIVACY | RESPONSIBLE USE | ACADEMIC INTEGRITY | WARNINGS And AWARENESS |
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DO NOT input sensitive data such as PII/SPII, Internal, Confidential, or Highly Confidential data. DO NOT enter institutional data into third-party AI systems. Such data may be transmitted, stored, or shared externally, outside our control, risking privacy and security. Users should opt out of any data sharing to protect institutional confidentiality. DO NOT integrate University systems into 3rd party AI platforms. This includes building agentic AI or custom GPTs that connect to USF systems. | Comply with FERPA, privacy laws, Guidelines for Responsible Use, and Information Security Policy. Be transparent about how GenAI is employed. Take into consideration accessibility, ethical, and inclusion aspects of GenAI use. Use only USF-approved AI tools. (see matrix below) Be accountable and transparent about the use of AI platform. | Adhere to USF's Academic Integrity & Honor Code. Check DLI's resources on course design and planning. Refer to your School & Faculty to provide additional instructions as needed. Cite AI usage for transparency. | Validate and verify output for accuracy, bias, and hallucinations. Appropriate treatment of copyrighted material. Stay alert & report any phishing emails and "deepfakes" (i.e. video/audio mimicking an individual without their consent). Use only Public data for input. If Internal or Confidential data is needed, please see a list of USF-approved AI platforms (see matrix below). |
Technology Acquisition Approval
Per the Purchasing Guidelines anything above $10K has to be approved the VP-CIO.
| DATA CLASSIFICATION | PUBLIC | INTERNAL | CONFIDENTIAL | HIGHLY CONFIDENTIAL |
| Definition | Non-sensitive and non-confidential. Examples include content available on the public facing web pages of www.usfca.edu. | Requires protection against unauthorized disclosure, modification, destruction, and use, but the sensitivity is less than that for Confidential information. Examples include internal memos, correspondence, ITS network security policies, and staff handbooks. | Sensitive information about individuals and about the University. This includes PII. Current and former students that are protected by FERPA are included. | Sensitive information which, if it became available or was exposed to unauthorized users, creates risk for identity theft therefore requiring notification of affected individuals and possible legal and reputation risk to USF. Examples include government issued identity numbers, bank account numbers, credit card numbers, and drivers' license numbers. |
| Applications that can be used | Any | USF-approved enterprise applications only. Submit an New Technology Assessment (NTA) if unavailable or unsure. | USF-approved enterprise applications only. Submit an New Technology Assessment (NTA) if unavailable or unsure. | Please reach out to infosec@usfca.edu for further consultation. |
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