Responsible AI adoption for higher education instructors

As artificial intelligence (AI) becomes an increasingly important part of higher education, your institution’s instructors must find responsible ways to adopt and share these tools.

The introduction of AI should be strategic and mindful to avoid common pitfalls, like amplifying biases or leaving student data unprotected. How your institution approaches higher education AI adoption will impact the integrity of your programs, so understanding the best practices is essential for supporting positive learner outcomes.

Your university or college can foster a culture of responsible AI use with careful forethought and planning. We are sharing different ways your faculty can capitalize on AI without sacrificing quality student experiences.

What is responsible AI adoption in higher education?


Your higher education institution has a duty to introduce and embrace artificial intelligence in a beneficial and trustworthy manner. Creating clear guidelines and promoting the ethical use of these advanced technologies will help your college or university maximize the benefits of leveraging AI while minimizing the potential repercussions.

Responsible instructor AI adoption is essential for:

Maintaining academic integrity


A 2023 study revealed that 56% of college students admitted to using AI to complete their coursework and assignments. With learners already actively utilizing these tools, understanding the role of AI and sharing policies for students and staff can help your institution protect academic integrity.

Students are responsible for turning in original work that accurately cites their sources and is free of plagiarism. They must learn how to use AI as a supplementary tool rather than a shortcut. Responsible AI adoption is key to maintaining high standards for academic integrity at your institution.

Fostering equity and inclusion


How your organization handles AI adoption will impact equity and inclusion across campus. There are various ways for your institution to do this:

  • Offer training and instructional opportunities for your entire community to learn how to use these solutions effectively.
  • Share equal access to university-sponsored AI tools and platforms.
  • Promote the use of AI to address accessibility barriers for students with disabilities.
  • Train AI models with diverse and representative data to combat biases.

Preparing faculty and staff for the future of AI


As artificial intelligence becomes a more significant part of society, colleges and universities will benefit from staying at the forefront of these advancements. This technology is revolutionizing how many industries operate. Higher education institutions can prepare students for a future of interacting and working with these tools by providing education on best practices. Embracing new tech can help your institution evolve and ultimately equip students with the insights they need for success.

AI best practices and considerations for university faculty


Higher education institutions can optimize AI adoption by following a few best practices:

1. Discuss the implications of AI with students


College or university faculty should discuss artificial intelligence openly with their students, especially relating to the acceptable uses of AI for class. Fostering an ongoing conversation about the implications of these modern technologies can help your community understand AI’s role in the future of both education and the working world.

Highlight the value and importance of producing original work, especially in an academic or professional context. Discuss AI as a tool to support the learning process rather than something that replaces the need for diligent research and work.

Share the potential drawbacks of artificial intelligence, such as:

  • Unreliable results and hallucinations.
  • Limited contextual understanding.
  • Privacy and intellectual property concerns.

2. Prioritize data quality and accuracy


Generative AI tools are not fool-proof and will sometimes offer false or irrelevant insights. Users shouldn’t rely on AI alone. They should verify their results with critical thinking and do their due diligence.

The faculty at your higher education institution should emphasize the importance of data quality and supporting ideas with proof. A student’s ability to provide data-backed evidence and demonstrate good analytical skills will benefit their success in and out of the classroom.

When using AI-powered systems to automate administrative tasks like tracking class attendance or grading quizzes, your instructors should always review the data to ensure accuracy and fairness.

importance of data quality

3. Be choosy about your AI tools


Your faculty should be selective about the AI tools they utilize and the platforms they allow students to use for class work. Each solution has different capabilities, limitations, and costs.

Ensure your instructors are purposefully and deliberately selecting AI tools. The options they choose should align with the specific assignment or activity. They should also enhance the course’s overarching learning objectives and help students gain a stronger understanding of class content. They should look for tools that empower students to think critically, enhance creativity, and help them apply essential topics.

4. Be transparent about AI use


An important element of responsible faculty AI adoption is fostering transparency about using these solutions with students. Higher education institutions can benefit from taking a human-centered approach to implementing new technologies. Your instructors should be honest about how they are utilizing AI to support the operations in their classroom. Ensure they explain how these tools are there to enhance learning experiences and not replace them.

Fostering an open conversation about artificial intelligence across campus is key to reaping the most benefits and creating a culture of continuous improvement and innovation.

5. Continuously monitor and update your AI models


Ongoing monitoring and refining is an important part of using AI tools effectively. The models your instructors use should be continuously improved and updated to deliver the most accurate, comprehensive and timely results for your institution’s users.

Your faculty should have protocols to follow regarding ongoing learning and retraining their AI models as new data emerges and the tool’s capabilities advance. Higher education institutions should prioritize gathering regular feedback from students and faculty to identify new opportunities to enhance the AI tools your community uses.

6. Maintain data privacy and security


Every faculty member who utilizes artificial intelligence must understand the necessity of strong data privacy and security practices.

Your instructors should always get consent before obtaining and using student data. They should also prioritize keeping that information safe and communicating its purpose and uses with students.

How your faculty members collect, store, share, and analyze data matters. They can combat many AI-related threats by ensuring they work with secure platforms that have adequate security measures, like strong access controls and data encryption.

7. Establish ethical AI guidelines


Your higher education institution must develop comprehensive artificial intelligence guidelines to ensure your faculty utilizes these tools ethically. These guidelines should include:

  • Ways to ensure fairness and mitigate bias.
  • Rules for using student data.
  • Accessibility requirements.
  • A schedule for updating AI systems.


In addition to understanding the moral implications of artificial intelligence, your instructors should also communicate the importance of responsible AI and data use.

Having the right policies in place will help your faculty navigate fair AI utilization and educate students about leveraging these solutions ethically.

8. Regularly evaluate the impact of AI tools


The faculty at your higher education institution will benefit from continuously assessing the AI tools they use in terms of effectiveness, performance, and the results they provide.

The purpose of introducing AI to the classroom is to support and improve educational outcomes. By evaluating their impact, your instructors can ensure they use effective, ethical tools that enhance academic achievement.

How instructors can use AI responsibly


Using AI can help your faculty manage their workloads, enhance academic research, inform advisement, and stay on the cutting edge.

Explore responsible AI uses for instructors below:

Personalized learning


A great way to utilize AI is by analyzing student data for personalized learning recommendations.

Your faculty would have to spend days on end analyzing the past performance of each student, getting to know their specific learning style and suggesting tailored materials for each person. AI allows instructors to provide more individualized attention without overwhelming them with additional work and research. They can use automated tools to generate adaptive course materials and access analytical tools to track each student’s pace and learning needs.

AI can help your institution’s instructors align teaching practices with student preferences to support improved learning and performance outcomes.

Automated grading


An AI-powered grading system can be an incredible time-saver for busy faculty members. These solutions can automate the review and scoring process for homework assignments, quizzes, and exams. AI tools with advanced natural language processing capabilities can even analyze written responses.

Instructors can save significant time with these systems, and students can benefit from getting feedback sooner. An important element of responsible AI adoption is ensuring your faculty continues to monitor these systems and their limitations. They should continue to give each student’s work the necessary time and attention to support optimized learning outcomes.

Virtual tutoring and teaching assistants

Virtual tutoring and teaching assistants


Another way your instructors can capitalize on artificial intelligence is by utilizing automated virtual teaching assistants. These AI-powered solutions make it possible for students to access support and help with their coursework around the clock. Instructors don’t have to spread themselves too thin to provide additional tutoring to struggling individuals. The right tool can help students find the information and clarification they need to succeed in class.

Your faculty members should closely monitor these solutions and provide guidance to students on how to use them effectively. Instructors should not rely solely on AI assistants to offer support outside of the classroom, but these solutions can be an advantageous addition.

Alerts for at-risk students


AI models can analyze student data to determine common warning signs that an individual is struggling with their workload. They monitor and evaluate various factors, such as attendance, assignment completion, and performance. If a student exhibits any problematic behavior, an AI-powered solution can alert your faculty members and support early intervention.

Your instructors should use these alerts as a starting point. Upon learning that a student is at risk of failing or dropping out, faculty should investigate the situation further to learn more about the student and their unique circumstances.

Plagiarism detection


Artificial intelligence can be a highly useful tool for analyzing student work and flagging instances of plagiarism, which is a very serious offense in higher education. Faculty members are responsible for ensuring their students are turning in original work. AI-powered solutions can scan submissions and compare the content with texts from a massive database. If an individual copies content, the tool will detect and flag the issue.

Your instructors should take additional time to validate plagiarism alerts and understand if, why, and how the student turned in potentially stolen work. With the rise of generative AI tools, faculty must also be aware of individuals using AI to complete their assignments.

Automated attendance tracking


For higher education students, class attendance plays a key role in their academic success. Faculty can leverage automated, AI-powered attendance tracking software. To utilize these tools responsibly, your instructors should consider different contextual factors that could potentially impact attendance. These include:

  • Illness.
  • Emergencies.
  • Technical complications.


Exercising a little flexibility and understanding is important when it comes to attendance because there are valid reasons why an individual may be unable to come to class. Instructors should recognize these nuances and use their discretion to maintain the most accurate and fair student attendance records.

Content recommendations


Artificial intelligence can be a powerful tool for finding tailored content recommendations for the classroom. Your faculty can use these solutions to find personalized resources that support and align with their course’s primary learning objectives.

It is beneficial for educators to use AI content recommendations to supplement their teaching materials and instructor guidance. They should also prioritize critical thinking and assess recommended content to ensure it is:

  • High quality.
  • Credible.
  • Relevant.


AI may not promote the most diverse and inclusive perspectives, so instructors must prioritize using balanced and inclusive materials.

Course suggestions for academic advising


Many college and university instructors also work as academic advisors for students. They can leverage artificial intelligence to monitor student performance and suggest course sequences.

Faculty members should have a clear understanding of how AI systems work and the factors they consider when making suggestions. Different advisees will have special circumstances and questions that advisors must think critically about to ensure they provide the most comprehensive and helpful recommendations for the individual.

Advisors should never rely entirely on AI tools for course suggestions and academic advising efforts.

Curriculum development assistance


Artificial intelligence can help your higher education institution’s faculty streamline and automate its administrative tasks. One of the most important of these tasks is curriculum development.

AI can help your instructors with data analysis, content curation, and personalized learning. When working on curriculum mapping, AI can help your institution with learning outcomes, activities, and assessments designed to optimize your educational pathways. These tools help deliver impactful student experiences with data-backed decision-making.

Request a demo of Watermark Student Success & Engagement


If your higher education institution is interested in helping its faculty and advisors improve student outcomes with precise, actionable data, turn to Watermark Student Success & Engagement.

Our tools will help your college or university increase engagement, retention, and degree completion by turning your institution’s data into actionable insights. With our AI equity and student success solution, your institution gets access to custom reports, guided pathways for students, and so much more.

Are you interested in seeing Student Success & Engagement in action? Request a demo online to get started today!

Request a demo of Watermark Student Success & Engagement
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Maximizing the Impact of Course Evaluations During COVID

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Microcredentials and How ePortfolios Can Highlight Them

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How to use SIS data at your school

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Minority Male Success Initiative (MMSI): A Catalyst for Change

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What Year Is Most Critical for College Student Success?

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How to use LMS data to support curriculum development

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MSCHE Accreditation: 7 Things Peer Reviewers Wish You Knew

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Use ePortfolios to give students a leg up in job searches

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The Power of Non-Academic Outcomes

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Where Are They Now? An Update on our 2020 Watermark Scholars

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The “who” and “what” of university administration

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Understanding the Support Needs of Community College Students

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Faculty Search Committees: What Are They and What Do They Do?

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How to make assessment simpler

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Turning Process Into Progress: Using Technology to Drive Institutional Improvement

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Keeping up with 2024 higher ed trends?

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How to Prepare for a Virtual Assessment Site Visit

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Transforming the Student Co-Curricular Experience of Community Colleges

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Tracking Progress With Student Learning & Licensure

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Online Course Feedback 101: From the Physical to the Digital Classroom

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How to prepare for an accreditation peer review visit

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Overcoming financial obstacles with help from higher education institutions

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Preparing for Life on Sabbatical

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Partnering With NCCCS to Help Students Succeed

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How to reduce faculty workload using technology

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Positive Change During Challenging Times: How Six Leaders Transformed Higher Education During the Pandemic

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How to Support Grad Students

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Best Practices to Reengage Community College Dropouts

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How to support students struggling with time management

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How to switch accreditors as a higher ed institution

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How Your College Can Support Veterans

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Predictive and Prescriptive Analytics’ Role in Fighting College Attrition

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How to prepare for a successful CAEP accreditation

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Top Course Evaluation Questions

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Top Things to Consider When Hiring a Student Success Coach

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Continuing education evaluation guide

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Identifying at-risk students through the course registration process

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Creating equity solutions

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5 Creative ways to use end-of-semester assessment data

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11 community college trends for 2023

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The importance of data transparency for higher ed success

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Higher education institutional outcomes – defining a proficiency scale

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How to democratize data at your institution to improve student outcomes

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Demonstrating faculty influence on student success with Radford University

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Developing proactive advising techniques

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The differences between direct and indirect measurement

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Discover the secrets of faculty “buy-in”

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Does the classroom environment matter?

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Collecting Feedback With Watermark Course Evaluations & Surveys

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Barriers to using assessment results and how to overcome them

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Engaging faculty in the new school year

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How to use institutional data to spot students likely to transfer

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Top reasons why students transfer and what your institution can do

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Supporting working-class students: 7 ways to show support

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How to support incoming transfer student success

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Why cloud-based video feedback software is helpful for higher ed

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How to track the results of culturally responsive education

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Watermark vs. Civitas
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Watermark vs. Civitas

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How to attract and retain top faculty at your institution

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How to be an effective program dean

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Building soft skills for future careers: Integrating professional development into your curriculum
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Building soft skills for future careers: Integrating professional development into your curriculum

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15 common challenges that first-year students face
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15 common challenges that first-year students face

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How to spot struggling first-year students and intervene
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How to spot struggling first-year students and intervene

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12 tips to improve first-year college student performance
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12 tips to improve first-year college student performance

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Weighing legacy admissions: What to consider at your institution

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Key metrics for mid-semester program reviews: What to measure and why

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Supporting student success during midterms

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Understanding the student engagement software space

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7 student engagement software trends to watch for in 2025

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7 innovative assessment practices to transform your institution

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Cultivating faculty development amid the uncertain future of tenure

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Involving faculty in accreditation processes

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Striking a balance: Guiding long-term faculty success in both research and teaching

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Leading causes of faculty burnout and how to spot it

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The impact of AI on institutional research 

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