These AI-powered custom applications can make administrative tasks more efficient and convenient. For example, they can answer frequently asked questions, help with data retrieval, quickly providing information from long documents. Voice assistants can support accessibility by providing voice-controlled navigation.

• Data Privacy: Protect sensitive information and adhere to relevant data protection regulations, and university policies, including data classification guidelines.

• Accuracy and Quality: Ensure the information provided by the chatbot is accurate and appropriate is essential to maintain trust and reliability.

• Transparency: Clearly communicate to users that they are interacting with an AI-powered system, which helps foster trust and sets realistic expectations.

AI-powered virtual assistants can help with scheduling, reminders, and tasks. They can understand natural language commands and perform various tasks to assist users in their daily activities.

• Accountability and Responsibility: Ensure the virtual assistant is used responsibly by identifying the benefits and potential risks.

• Data Privacy: Protect sensitive information and adhere to data protection regulations, especially when virtual assistants handle personal data.

• Accuracy and Quality: Ensure the tasks performed by the virtual assistant are accurate and appropriate, as this is essential to maintain trust and reliability.

• Accountability and Responsibility: Ensure the AI tools are used responsibly by identifying the benefits (e.g.,  error reduction) and potential risks (e.g., security vulnerabilities).
• Accuracy and Quality: Regularly review and validate the AI-generated code snippets, suggestions, and debugging outputs to ensure they are accurate and appropriate.
• Over-reliance on AI: Avoid relying solely on AI-generated code without cross-verification, especially for critical or complex parts of the software.

Image Generation

Generative AI tools can be used to create new images based on specific inputs or parameters. Designers can use Generative AI to create artwork, explore styles, and generate design concepts. Image generation has applications to marketing and communications when organizations leverage AI-generated images for communications campaigns, social media posts, and advertisements.

• Biased Data: Monitor the AI tools for biases or unintended consequences in the images they generate, and make adjustments as needed.

• Copyright and IP: Ensure the AI-generated images do not infringe on relevant copyright laws and respect intellectual property rights.

• Ethical Considerations: Use the AI tools in a manner that aligns with ethical principles such as respect, fairness, and explainability.

AI can summarize long documents, articles, or reports into concise summaries. This may help users quickly understand the key points, and summarize primary findings and conclusions.

• Data Privacy: Protect sensitive information and adhere to data protection regulations and university policies when the AI tools access or process documents containing personal or sensitive data.

• Accuracy and Quality: Regularly review and validate the AI-generated summaries to ensure they accurately reflect the key points and conclusions of the original documents.

• Transparency: Clearly communicate to users and stakeholders the use of AI in the summarization process to foster an environment of trust and accountability.

AI tools can review and summarize legal contracts. For example, AI can quickly identify key terms and clauses in contracts, and flag potential risks and inconsistencies in contract language. Contract analysis can ensure compliance with policies and regulations.

• Data Privacy: Protect sensitive information and adhere to data protection regulations and university policies when the AI tools access or process legal contracts.

• Accuracy and Quality: Regularly review and validate the AI-generated summaries and analyses to ensure they accurately reflect the key terms and clauses of the contracts.

• Over-reliance on AI: Avoid relying solely on AI-generated contract analyses without human oversight, especially for critical or complex legal documents.

This involves automatically transcribing and summarizing meeting discussions. For example, AI can record and transcribe meeting audio, providing a written record of discussions. It can also summarize key points and action items, saving time for meeting participants. Meeting minutes can support transparency by providing a record of decision-making processes.

• Data Privacy: Protect sensitive information and adhere to data protection regulations and university policies when the AI tools access or process meeting audio and transcripts.

• Accuracy and Quality: Regularly review and validate the AI-generated transcriptions and summaries to ensure they accurately reflect the meeting discussions and key points.

• Transparency: Clearly communicate to meeting participants and stakeholders the use of AI in the transcription and summarization process and explain its capabilities and limitations.

AI can analyze texts, including analyzing feedback to gauge sentiment, generate insights and improve services. It can identify trends, helping to improve services and support. By understanding the sentiment behind feedback, one can address issues proactively. It helps in making informed decisions based on the tone of feedback.

• Data Privacy: Protect sensitive information and adhere to data protection regulations and university policies when the AI tools access or process feedback and other texts.

• Accuracy and Quality: Regularly review and validate the AI-generated insights and sentiment analyses to ensure they accurately reflect the feedback and trends.

• Biased Data: Monitor the AI tools for biases or unintended consequences in the text analyses they generate, and make adjustments as needed.

• Transparency: Clearly communicate to users and stakeholders the use of AI in the text analysis process to foster an environment of trust and accountability.

This involves tailoring content for different audiences. For example, AI can analyze user data to provide personalized content recommendations which in turn can provide more relevant and timely information.

• Data Privacy: Protect sensitive information and adhere to data protection regulations and university policies when the AI tools access or process user data.

• Accuracy and Quality: Regularly review and validate the AI-generated content recommendations to ensure they are accurate and appropriate for the target audience.

• Transparency: Clearly communicate to users and stakeholders the use of AI in the content personalization process and explain its capabilities and limitations.

Generative AI can analyze user data to create personalized messages and letters. By tailoring content to individual preferences, units can increase engagement.

• Accountability and Responsibility: Ensure the AI tools are used responsibly by identifying the benefits (e.g., relevance) and potential risks (e.g., content bias).

• Data Privacy: Protect sensitive information and adhere to data protection regulations and university policies when the AI tools access or process user data.

• Accuracy and Quality: Regularly review and validate the AI-generated messages and letters to ensure they are accurate and appropriate for the target audience.

• Ethical Considerations: Use the AI tools in a manner that aligns with ethical principles such as respect, fairness, and explainability.

This involves monitoring and categorizing expenses. For example, AI can analyze data to track spending across departments. It can also categorize expenses, providing insights into cost distribution, and improving  transparency and control over expenditures.

• Data Privacy: Protect sensitive financial information and adhere to data protection regulations and university policies when the AI tools access or process expense data.

• Accuracy and Quality: Regularly review and validate the AI-generated expense categorizations and insights to ensure they are accurate and appropriate.

• Transparency: Clearly communicate to users and stakeholders the use of AI in the expense tracking process to foster an environment of trust and accountability

This involves using AI to identify and prevent potentially fraudulent activities. For example, AI can analyze financial transactions to detect unusual patterns or anomalies. AI can provide real-time alerts and reports, allowing for analysis to determine potential fraud and timely intervention. Fraud detection systems can be continuously updated with new data and patterns to improve accuracy.

• Accountability and Responsibility: Ensure the AI tools are used responsibly by identifying the benefits (e.g., fraud prevention, financial security) and potential risks (e.g., false positives, privacy concerns).

• Accuracy and Quality: Regularly review and validate the AI-generated alerts and reports to ensure they accurately identify potential fraud and minimize false positives.

• Use System Without Understanding: Ensure that users understand how the AI tools detect fraud to prevent misuse or unintended consequences.