AI for Research

Researchers and professionals are navigating a rapidly expanding ecosystem of AI‑enabled research tools, many of which promise discovery, synthesis, and insight, but differ substantially in how they work, what they can access, and the kinds of work they support. In this environment, the challenge becomes learning how to identify, evaluate, and use AI research tools that truly fit specific research needs.

This course helps researchers—eand other professionals who do research as part of their job—develop landscape awareness and critical evaluation of AI research tools, then thoughtfully apply the tools in their own research workflows.  

Using a set of robust, field‑validated AI research tool directories, along with techniques such as AI tool chaining, participants in this course will learn to design and adapt AI‑supported workflows aligned with their own research processes, while keeping human judgment central to verification and responsible use. The goal is to enable participants to confidently navigate an evolving AI research landscape and integrate AI in ways that strengthen research rigor and integrity.  

Whether you are an instructor, a graduate student deep in the trenches of research, or an industry professional who finds yourself regularly engaged in research activities, this course will help you understand how to use AI research tools to your advantage, increasing research productivity without sacrificing quality.  

COURSE At A Glance
 

July 20 – August 3, 2026

Live Zoom Sessions: 
July 23 & July 30, 2026

 

Online

Hybrid

Cost

Early Bird or Stout Proud $249, Regular $299

What will you gain?

• Explain the difference between general-purpose AI tools and research-focused AI tools, and why differences in system design lead to different kinds of research outputs
• Evaluate AI-generated research outputs for accuracy, completeness, bias, and usefulness based on system design and data sources
• Understand how to act on AI-generated research outputs, including what to verify, when additional evidence is required, and how AI use should be cited or disclosed in research contexts
• Find and assess AI research tools using a curated set of directories to select tools that align with specific research needs
• Design a robust and adaptable AI-supported research workflow, applying techniques like AI tool chaining

Who should enroll?

• Academic and research support professionals in any industry or field
• Industry professionals who do research as an aspect of their job
• Faculty and researchers in research-intensive domains
• Graduate students and postdocs

What will it cost?

• Early Bird Discount (Register by July 13, 2026): $249
• Stout Proud Discount (UW-Stout Faculty, Staff, Student, and Alumni Registration): $249
• Regular Registration: $299

Important Notes: 

• Faculty/Staff/Students: Use your UW-Stout email when registering to receive discount.
• Alumni: Reach out to gieskingj@uwstout.edu to receive a discount code BEFORE completing the registration form.
• FAQs: For information on Payment and Cancellation Policy, Disability Accommodations, and other issues, please visit the Frequently Asked Questions page.