Description

In this interactive, hands-on pre-conference workshop, participants will learn how to design and build practical AI agents or automated workflows using tools such as ChatGPT and Microsoft Copilot. Through hands-on activities, attendees will explore how AI agents can streamline their own work as well as the work of teams they lead, support decision-making, and expand their leadership impact in this rapidly evolving space. The workshop will also introduce essential AI guardrails for protecting sensitive data, managing risk, and using generative AI responsibly. Participants will leave with new knowledge and skills for developing AI solutions that align with the policies, security requirements, and IT standards of their colleges and universities.

Learning Objectives

By the end of this session participants will be able to:

• Design and build a practical AI agent or automated workflow using tools such as ChatGPT Edu, Microsoft Copilot or a similar software offering.
• Identify opportunities to use AI agents to streamline work, strengthen decision-making, and enhance individual and team effectiveness.
• Learn about how to apply appropriate AI guardrails to protect sensitive data, manage risk, and align solutions with institutional policies, security requirements, and IT standards.

*To attend the pre-conference workshop, you must sign up for the Forum.

Return to WLF Home Page

Stefani Langehennig | Assistant Professor of the Practice in the Business Information & Analytics Department, University of Denver

Description

Artificial intelligence is increasingly being used to support decision-making across higher education administration, yet many leaders are still determining where these tools add value and where caution is warranted. This session examines AI as a leadership and decision-support tool in administrative and financial settings, focusing on judgment, risk, accountability, and organizational governance. Participants will explore what current AI systems can and cannot reliably do, common sources of error and bias, and practical considerations for responsible use. The session emphasizes how leaders can leverage AI to improve decision quality while maintaining appropriate human oversight and accountability.

Learning Objectives

By the end of this session participants will be able to:

• Recognize the strengths and limitations of current AI systems in administrative and financial decision-making.
• Evaluate potential risks, biases, and accountability challenges associated with AI-assisted decisions.
• Apply practical principles for responsible AI use within higher education administrative environments.

Return to Main Page