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The American Academy of Nursing (AAN) announced its selection of highly distinguished nurse leaders for its 2026 class of Academy Fellows, including Marie Lourdes Charles, EdD, RN-BC, FNYAM, associate professor at the Lienhard School of Nursing.

Dr. Charles will be recognized for her significant contributions to health and health care at the Academy’s annual Health Policy Conference, taking place October 8–10, 2026, in Washington, DC. The theme of this year’s conference is “Digital Health: Promise, Responsibility.”

Dr. Charles is a community health nurse, researcher, and educator with over 40 years’ experience. Her practice, research, and scholarship aim at improving health outcomes by focusing on underrepresented populations, especially individuals with intellectual and developmental disabilities as well as people living in resource-poor communities. She is a founding member and vice-president of the Health Education Action League for Haiti (HEAL Haiti), collaborating with community partners in Haiti to provide resources, health screening, and education to underserved populations. She has also served as a liaison between Pace University and Caribbean Communities of Brooklyn and Queens to execute the All of Us Educational Program from the National Institutes of Health (NIH). Currently, she is involved in the PrEP Ring study in Uganda which was funded by several Pace University grants. Dr. Charles has received many awards for her contributions to Public Health including the Caribbean Impact Award from Caribbean Life and Advancing Health Equity Award from the Association of Community Health Nurse Educators (ACHNE).

According to the AAN press release, the 2026 Class of Fellows represents 39 states, the District of Columbia, and 17 countries, and reflects the powerful role nurses play in promoting health and well-being. Induction into the Academy is a significant milestone in which past and current accomplishments are honored by colleagues within and outside the profession.

AAN President Debra J. Barksdale, PhD, FNP-BC, FAANP, ANEF, FADLN, FAAN, said the vision, dedication and accomplishments of this year’s inductees represent the best of the nursing profession.

Through evidence-based innovation, leadership, and scholarship, they have improved outcomes, shaped policy and practice, strengthened nursing education and care delivery, and advanced scalable solutions that promote healthy lives for all people. Their accomplishments demonstrate the depth and reach that define Fellowship in the Academy.

Dr. Charles joins the following Pace Lienhard School of Nursing faculty Fellows:

• Harriet Feldman, PhD, RN, FAAN
• Sandra Lewenson
• Andréa Sonnenberg, PhD, WHNP, CNM-BC, FNAP, FNYAM
• Joanne Singleton, PhD, RN, FNP-BC, FAAN, FNAP, FNYAM

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When students arrive at Pace University, they expect more than classrooms and coursework. They expect a community where they can learn, work, perform, research, and grow while feeling safe, respected, and supported. Behind much of that work is Pace’s Office of Civil Rights Compliance (OCRC), a team focused on helping ensure discrimination and harassment do not become barriers to anyone’s education or career.

Led by Assistant Vice President and Pace’s Title VI and Title IX Coordinator Bernard Dufresne, the office oversees the University’s compliance with major federal civil rights laws, including Title IX, Title VI, and Title VII as well as state and local laws that prohibit discrimination and harassment. While many people are familiar with Title IX through conversations about sex-based discrimination and sexual misconduct, the office’s work extends much further, addressing concerns connected to race, national origin, shared ancestry, gender, and other protected characteristics.

This summer, the office will formally transition from the Office of Institutional Equity and Title IX Compliance to the Office of Civil Rights Compliance, a change designed to better reflect the full scope of the office’s responsibilities and provide a clearer path for community members seeking support.

“Our office exists to make sure discrimination and harassment don’t interfere with your education or job, and to help you understand your options if something goes wrong,” says Dufresne.

A growing area of focus nationally—and at Pace—is Title VI of the Civil Rights Act of 1964, which prohibits discrimination based on race, color, or national origin at institutions receiving federal funding. The law also applies to discrimination tied to shared ancestry or ethnic characteristics, making it increasingly relevant as colleges and universities navigate incidents involving antisemitism, Islamophobia, racism, and national-origin discrimination. The office’s expanded focus also reflects recent changes in New York State law requiring colleges and universities to designate a Title VI Coordinator to oversee compliance and response efforts related to discrimination and harassment covered under the statute.

“Our office exists to make sure discrimination and harassment don’t interfere with your education or job, and to help you understand your options if something goes wrong,” says Dufresne.

Title VI protections can apply in a range of situations: a student targeted for wearing a yarmulke or Star of David, a student harassed for wearing a hijab, or a faculty member mocking a student’s accent or native language. In these cases, the Office of Civil Rights Compliance reviews both the conduct itself and the impact it had on the individual(s) experiencing it.

Importantly, the office is not solely focused on formal investigations. Dufresne emphasizes that support often begins long before a complaint process formally starts.

“Central to our trauma-informed approach is acknowledging the difficulty of coming forward and whenever possible, we give the affected individual agency over how they wish to proceed,” he says. “We do that by explaining the difference between a formal complaint and supportive measures, allowing individuals to receive help without necessarily triggering a full investigation if they aren't ready.”

That support can include connecting individuals with resources, explaining reporting options, helping implement supportive measures, and coordinating with other offices across the University. The office works closely with Residential Life, Human Resources, Student Conduct, the Counseling Center, the Dean for Students offices, and the Office of Sexual and Interpersonal Wellness to ensure concerns are addressed appropriately and compassionately.

At the same time, Dufresne notes that one of the biggest misconceptions about the office is that it handles every form of conflict or misconduct at the University. The OCRC specifically addresses concerns involving discrimination and harassment tied to protected characteristics. Other workplace or student conduct concerns may fall under different offices, such as Human Resources or Student Conduct.

“Obviously, misconduct comes in various forms and our goal when we receive a report is to make sure that it’s being handled promptly by the right office,” says Dufresne.

The office also continues to evolve in response to feedback from students and the broader campus climate. Recent student survey data at Pace found that while many students believe reports of sex-based misconduct would be taken seriously, fewer students fully understood investigation procedures and available rights. The findings highlighted an ongoing need for clearer communication, stronger awareness, and more peer-based prevention efforts.

For Dufresne, building trust remains at the center of the work.

“Trust is a long-term project,” he says. “We cannot guarantee a specific outcome for every case, but we can guarantee a consistent, respectful, and dignified process.”

And for anyone unsure whether their experience falls within the office’s scope, his advice is simple: reach out anyway.

“You do not need to know whether something ‘counts’ as discrimination to reach out,” Dufresne says. “The office exists to ensure that your identity never becomes a barrier to your education or career.”

The Pace Community can expect to hear more from the office during the Fall 2026 semester.

Students, staff, faculty, families, and members of the broader community can learn more about available resources or to share a concern through Pace’s Guardian reporting system.

Pace Magazine brings Pace University’s people, ideas, and achievements to life through dynamic, high-impact storytelling. Published twice a year and distributed to alumni, donors, friends of the University, and the entire Pace Community, the magazine highlights the work and influence of our students, faculty, and alumni around the world.

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Scroll through any tech job board right now and you'll notice artificial intelligence roles dominating the listings. The salaries are six figures, the companies are household names, and the number of open positions keeps climbing. With that kind of demand, a master's in AI might seem like an obvious next step. But a graduate degree is a serious commitment of time and money that leaves you wondering, “Is a master's in AI worth it?”

That’s a fair question. Graduate tuition can run into the tens of thousands of dollars, and two years of full-time study means two years of income you’re not earning. If you’re considering a career change, the stakes feel even higher.

This guide will help you evaluate the decision by looking at how much AI professionals earn, which roles are hiring, how fast the field is growing, and what a structured program actually teaches. We’ll also cover when the degree may not be the right move, because an honest answer requires looking at both sides.

What Is a Master’s in AI, and What Does It Prepare You to Do?

A Master of Science in Artificial Intelligence is a graduate degree focused on the theory, design, and application of intelligent systems. Students study machine learning algorithms, natural language processing, computer vision, robotics, and the ethical considerations that come with deploying AI in real-world settings.

The degree differs from adjacent programs in meaningful ways. An MS in Data Science emphasizes statistical analysis, data visualization, and business intelligence, and while data science shares some overlap with AI (particularly in machine learning and Python programming), its focus stays on interpreting data rather than building autonomous systems. An MS in Computer Science covers broader territory, from operating systems to software engineering, with AI as one possible concentration.

An MS in AI goes deeper into designing the systems themselves. Where a computer science degree covers breadth and a data science degree focuses on analysis, an AI degree trains you to build, train, and deploy models that learn and act on their own. The coursework centers on algorithm design, model architecture, and the engineering required to move AI from a research concept into a working product.

Most MS in AI programs are STEM-designated and take one and a half to two years to complete. Core coursework typically spans machine learning, deep learning, natural language processing (NLP), and computer vision, with electives or concentrations that allow students to specialize. Some programs emphasize research, while others take a project-driven, applied approach. At Pace University, for example, students can choose between a research-focused MS in Artificial Intelligence and a project-driven MS in Applied Artificial Intelligence with industry concentrations.

These programs serve various types of students, including recent college graduates looking to specialize, working professionals seeking technical depth, and career changers entering the field with a structured foundation.

Admissions Requirements for an MS in AI

Admissions requirements for MS in AI programs vary by school, but most share a common set of expectations. Understanding these requirements early helps you plan your application timeline and avoid last-minute surprises.

Most programs require a bachelor’s degree, ideally in computer science, engineering, mathematics, or a related STEM field. Some programs accept students from non-technical backgrounds and offer bridge or foundation courses to help them build the prerequisites. Application materials typically include a personal statement, a resume or CV, official transcripts, and letters of recommendation. Standardized test scores such as the GRE are required by some programs but optional at others.

Tuition, financial aid, and application requirements vary by school. The table below shows how Pace University compares to a typical program.

Typical program data reflects common admissions patterns across U.S. MS in AI programs as reported by university websites and graduate admissions aggregators such as GradSchoolHub and U.S. News Graduate Rankings. Pace University data sourced from pace.edu.

Why Earn a Master’s in AI Now?

The market data behind AI hiring is very strong, and several indicators suggest that now is a particularly good time to invest in this degree.

AI and machine learning specialist roles have grown by 176 percent in economies like India and the UK, according to the World Economic Forum’s (WEF) Future of Jobs Report. In the United States, the Bureau of Labor Statistics projects 34 percent growth for data scientists and 20 percent growth for computer and information research scientists through 2034. Both rates far exceed the three percent average for occupations overall.

The scale of the market reinforces these projections. The global AI market is estimated at $757.58 billion in 2026 and projected to reach $3.68 trillion by 2034. That level of investment is drawing AI adoption into every sector. AI adoption now spans 100 percent of industries surveyed by the World Economic Forum, including sectors such as mining and construction that have only recently begun integrating AI into their workflows.

Employer behavior reflects this demand. The same WEF study found that 77 percent of employers plan to upskill their workforce around AI tools, and 86 percent expect AI to transform their business operations by 2030. Demand for AI fluency has grown sevenfold in two years, faster than any other skill category tracked in U.S. job postings.

For prospective students, these numbers point to sustained demand rather than a short-term hiring spike. The companies investing in AI infrastructure today will need trained professionals to build, manage, and improve those systems for years to come.

Salary Potential and Career Outcomes for MS in AI Graduates

AI professionals typically command higher compensation than other tech roles. Workers with AI skills such as machine learning, deep learning, and prompt engineering earn a 56 percent wage premium over peers in similar positions without AI expertise. In the New York metro area, where Pace University is located, compensation runs above national averages across all AI positions.

The career paths below represent common roles for graduates with an MS in AI.

Salary data sourced from Glassdoor, NYC metro area (2026). Ranges reflect 25th to 75th percentile. *AI Ethics Specialist data sourced from ZipRecruiter. Actual compensation varies by employer, experience, and industry.

The Expanding AI Job Market

The career paths above show what individual roles pay. But the hiring picture is broader than any single title. AI is changing how entire industries staff their teams, and that creates long-term flexibility for graduates who build strong AI foundations.

Five years ago, AI hiring was concentrated in a handful of tech hubs. That has changed. Healthcare systems, banks, government agencies, manufacturers, and media companies are all staffing AI teams, and they need people who can build and manage these systems across very different operating environments.

The numbers behind this expansion are significant. According to AI Statistics, AI is projected to create 97 million new jobs globally, against an estimated 85 million displaced. Skills demand in AI-exposed occupations is shifting 66 percent faster than in roles with low AI exposure, per the World Economic Forum. And the number of AI-related roles has doubled across nearly all industries since 2016.

The Bureau of Labor Statistics reinforces this outlook. Computer and mathematical occupations are projected to grow 10.1 percent through 2034, which is more than three times the average rate for the total economy. Data scientists rank as the fourth-fastest growing occupation nationally, and related research and engineering roles that include AI-focused positions also show well-above-average growth.

Additionally, new job categories are emerging alongside this growth. Roles such as prompt engineer, MLOps engineer, and AI solutions architect did not exist five years ago. According to MIT research, more than 60 percent of jobs held by U.S. workers in 2018 were in occupations that did not exist in 1940, and the pace of new job creation has only accelerated alongside advances in technology.

For someone evaluating a master’s in AI, these patterns offer reassurance. An MS in AI gives you a skill set that transfers across sectors and adapts as the technology develops.

MS in AI vs. Certifications, Bootcamps, and Self-Study

A master’s degree is one of several paths into AI, and each option serves a different career stage and goal. Here’s how they compare.

• AI bootcamps vary widely in length and cost. Full-time programs typically run four to 16 weeks, while part-time options can extend to six months or longer, with tuition ranging from a few thousand dollars to $15,000 or more. They focus on practical skills and job placement, covering tools such as Python, TensorFlow, and basic model development. Bootcamps can be a strong entry point for career changers who want to move quickly into junior roles. However, they rarely cover the mathematical foundations, research methodology, or systems-level thinking that advanced AI positions require.
• Online certifications from platforms like Coursera, edX, or Google offer focused skill-building at low cost. They work well for professionals who want to add a specific capability (such as prompt engineering or TensorFlow proficiency) without committing to a full degree. The tradeoff is limited depth and the fact that certifications carry less weight with employers hiring for senior or research-oriented positions.
• Self-study through open-source materials, research papers, and personal projects is free and flexible. While self-directed learning can supplement formal education or help someone test their interest in the field, it typically lacks the structured mentorship, portfolio validation, and professional network that employers expect for mid-level and senior AI roles.
• A master’s degree provides depth across all of these dimensions. It covers theoretical foundations (linear algebra, probability, optimization), builds applied experience through research and projects, offers career services and employer connections, and results in a credential that carries long-term recognition. For international students, a STEM-designated master’s also opens access to extended OPT work authorization in the United States.

The right path depends on where you are and where you want to go. If your goal is a narrow technical skill or an entry-level transition, a bootcamp or certification may be enough. If you’re aiming for research roles, senior engineering positions, leadership tracks, or international career mobility, a master’s degree can provide a stronger return.

When a Master’s in AI May Not Be Worth It

Here are situations where pursuing a master’s in AI may not deliver the return you expect.

• Your target role prioritizes experience over credentials. If you’re aiming for a position focused on implementation rather than design (for example, a junior developer applying pre-built models), employers may weigh a portfolio of completed projects and practical experience above a graduate degree.
• Your career goals are still undefined. Spending two years on a degree is a significant bet without a clear direction. Graduate school works well when you have a defined goal. Without one, gaining work experience first and returning to school once you understand which problems excite you may be the stronger path.
• The financial math does not work. If tuition would create a strain without scholarship support, employer sponsorship, or manageable loan terms, the investment may not pencil out. Review financial aid options carefully before committing.
• You already have deep AI experience. If you have years of hands-on AI work and a strong professional track record, the credential itself may add limited value. Senior professionals sometimes benefit from targeted certifications or executive education rather than a full master’s program.

None of these scenarios are permanent disqualifiers. They are timing considerations. The right time for a master’s in AI is when the investment aligns with a clear goal and a realistic plan to pay for it.

How Pace University’s MS in AI Prepares You for Career Success

Pace University’s AI master’s programs are built around technical depth, research access, and direct connection to the New York City job market. Here’s how the programs translate to career outcomes.

Two Programs, Two Approaches

Pace offers two graduate AI pathways through the Seidenberg School of Computer Science and Information Systems. The MS in Artificial Intelligence emphasizes research depth in machine learning, NLP, robotics, generative AI, and computer vision. The MS in Applied Artificial Intelligence takes a project-driven approach for professionals who want to implement AI in business environments, with concentrations in human-centric AI, data-centric AI, and computational intelligence. Both are two-year, STEM-designated, in-person programs with online options available for the Applied AI track.

Curriculum

Coursework maps directly to the hiring requirements for the roles listed earlier in this guide. Students in the MS in AI take courses such as Introduction to NLP, Pattern Recognition, and Advanced AI. Applied AI students take courses in Applied AI, Ethical Issues in AI, and Human-AI Interaction. The Applied AI program also accommodates students without prior technical backgrounds through foundation courses in coding and database management.

Research Access

Students work in three dedicated facilities: the Pace AI Lab, where faculty and students conduct training and research; the Robotics Lab, focused on autonomous systems and hardware integration; and the Augmented Intelligence Lab, which explores computer vision and human-computer interaction. Faculty-led research spans healthcare, education, and human-centered AI.

Faculty Expertise

The program is taught by researchers actively publishing and securing grants in AI.

• Professor Juan Shan, PhD, applies machine learning to predict knee osteoarthritis progression in medical patients.
• Professor Christelle Scharff, PhD, is a two-time Fulbright scholar who co-directs the Pace AI Lab.
• Professor Soheyla Amirian, PhD, specializes in explainable, interpretable, and accountable AI.
• In the Applied AI program, Professor Yegin Genc, PhD, directs the Augmented Intelligence Lab.
• Professor Zhan Zhang, PhD, has built one of Pace's most distinguished research programs, securing more than $2.5 million in federal grants and becoming the first Pace professor to earn funding from both the National Institutes of Health and the National Science Foundation. He is also the first Pace faculty member to receive the NSF CAREER Award, one of the most prestigious honors for early-career STEM researchers.

New York City Location

Pace’s campus places students in one of the world’s largest technology and innovation markets. Graduates work at organizations such as:

• Google
• Amazon
• Meta
• Microsoft
• JP Morgan Chase
• IBM
• Capital One
• United States Department of Defense
• OpenAI

Proximity to these employers means access to internships, career fairs, and professional events throughout the program.

Stem Designation and International Access

Both programs are F-1 visa eligible and STEM-designated. International graduates can apply for up to 36 months of OPT in the United States. The INSPIRE Program (International Student Professional Readiness Program) provides structured internship and career success support exclusive to Pace.

Career Services

Pace’s Career Services team offers resume development, interview preparation, and access to a job and internship database. This support begins in the first semester and continues after graduation. Ninety-six percent of Seidenberg graduates are employed, continuing their education, or pursuing service within one year of graduation.

Alumni Network

Pace’s global community includes more than 161,000 alumni across industries and geographies. That network opens doors to mentorship, referrals, and professional connections.

Admissions and Cost

Applicants submit a personal statement, resume, and official transcripts. Letters of recommendation are optional, and no GRE is required. Tuition is $1,670 per credit ($50,100 total). The program accepts students for fall, spring, and summer terms. Every admitted student is automatically considered for merit-based scholarships of up to $6,400, with additional aid available through graduate assistantships, endowed scholarships, federal loan programs, work-study, and military benefits including the GI Bill and Pace’s Veteran Tuition Scholarship.

How to Decide If a Master’s in AI Is Worth It for You

The answer depends on your individual circumstances. The following questions can help you work through the decision.

No single answer fits everyone. But for professionals with a clear goal, a realistic financial plan, and access to a strong program, a master’s in AI is one of the higher-ROI investments available in graduate education today.

Consider Your Next Steps with Pace

The data behind AI careers is compelling. Roles have grown 176 percent in recent years, the global AI market is on pace to reach $3.68 trillion by 2034, and professionals with AI training consistently outearn their peers. For professionals with the right goals and preparation, a master’s in AI can accelerate both earning potential and career trajectory.

The value of the degree depends on the program you choose and the effort you bring. Look for a curriculum that matches hiring requirements, faculty who are active in research, career services that connect you to employers, and a location that gives you access to the market where you want to work.

Pace University’s MS in Artificial Intelligence brings those elements together: a curriculum aligned with current hiring requirements, faculty conducting funded research, and proximity to one of the country’s largest concentrations of AI employers.

Ready to take the next step? Request more information about Pace’s AI master’s programs today to get started.

Frequently Asked Questions

Is it worth it to do a master’s in AI?

A master’s in AI is worth it for professionals targeting research, senior engineering, or leadership roles in the field. AI-skilled workers often earn a higher wage premium, and AI specialist roles have grown by 176 percent in recent years. The investment pays off when paired with a clear career goal and a program that provides hands-on research, employer connections, and a recognized credential.

Will a master’s in AI help me get a job?

A master’s in AI can significantly improve your job prospects, particularly for competitive positions. Three out of four employers prefer master’s-level candidates for AI roles, and the Bureau of Labor Statistics projects 20 percent growth in AI and machine learning positions through 2034. A strong program also provides internship access, career services, and a professional network, all of which support job placement.

What’s the average salary with an AI master’s?

The average salary for professionals with an AI master’s degree varies by role, but AI engineers in the New York metro area earn an average of $175,000 per year, and AI research scientists average $203,000 per year, according to Glassdoor. Compensation depends on role, industry, and experience level. See the career paths section above for role-by-role breakdowns.

Is a master’s in AI worth it for career changers?

A master’s in AI can be a strong investment for career changers, because structured programs build technical foundations, portfolio work, and professional connections that self-study alone rarely provides. Pace University’s MS in Applied AI accommodates students without prior technical backgrounds through foundation courses in coding and database management.

How long does an MS in AI take to complete?

An MS in AI typically takes one and a half to two years to complete as a full-time student. Pace University’s program is designed as a two-year, in-person program with fall and spring start dates.

What careers can you pursue with a master’s in artificial intelligence?

A master’s in artificial intelligence prepares graduates for roles including machine learning engineer, AI engineer, data scientist, NLP engineer, computer vision specialist, robotics engineer, AI product manager, AI research scientist, AI ethics specialist, and data engineer. See the career paths section above for salary ranges and the skills each role requires.

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For adolescent girls and young women in sub-Saharan Africa, HIV prevention is not simply a matter of medical access. It is shaped by stigma, gender norms, family dynamics, provider attitudes, transportation barriers, health policy, and whether a prevention tool fits the realities of daily life.

That is where research led by Pace University College of Health Professions faculty members Erica L. Gollub, DrPH, MPH, professor of health science, and Marie Lourdes Charles, EdD, RN-BC, FNYAM, associate professor of nursing, are making an important contribution. Their work highlights two essential forces in global public health: health care providers as the bridge between innovation and access, and global research rooted in meaningful local partnerships.

Their study, “‘Some people fear injection and others don’t want to swallow tablets, while others forget’: Health care provider perspectives on the PrEP (dapivirine) ring in rural Uganda (‘ProPrEP’),” examines how health care providers understand and respond to the dapivirine vaginal ring (DVR), a monthly, user-controlled HIV prevention method. The full research team includes Gollub and Charles of Pace University; Esther Nakyaze of Catholic Relief Services; and Drs. Marc Sklar and Murokora Daniel of Babies and Mothers Alive Foundation.

Adolescent girls and young women are central to this study because they remain among the populations most disproportionately affected by HIV. In sub-Saharan Africa, they account for more than 60 percent of adults living with HIV, and one in four new HIV infections occurs among women ages 15–24, despite the fact that they make up only 10 percent of the population. In Uganda, that gender disparity is especially clear: HIV prevalence among young women ages 15–24 is 2.9 percent, compared with 0.8 percent among young men. Those numbers underscore why prevention tools must be designed not only to work medically, but also to fit the social, cultural, and practical realities of young women’s lives.

“The research that we do anywhere is going to support women getting access to HIV tools everywhere."

Charles and Gollub recently presented their work as part of Pace’s annual conference hosted by the Office of Research and Graduate Education, an opportunity to share research that sits at the intersection of public health, nursing, global health equity, women’s autonomy, and implementation science.

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The study focused on 60 health care providers in the Rakai and Kyotera districts of rural Uganda, including nurses, midwives, and community health workers. Through focus group discussions, the researchers explored provider perspectives on the DVR’s potential benefits, barriers to use, and the education needed to support adolescent girls and young women.

For Gollub, who has spent decades working in HIV prevention, the urgency is clear.

“HIV prevention needs are critical among the population of adolescent girls and young women worldwide, but particularly in sub-Saharan Africa,” she says. “It’s one thing to have tools and medications to prevent HIV infection. It’s another thing to be able to have them be used.”

The distinction between availability and real-world use is at the heart of the research. In public health, innovation only matters when people can access it, trust it, and use it. The DVR offers a discreet, nonhormonal option that women can insert themselves and use for one month at a time. Because it is not a daily pill, does not require frequent injections, and can be used privately, providers in the study see strong potential for the ring to reduce stigma and expand prevention options.

Gollub describes the ring as “revolutionary,” particularly because it gives women a prevention option that is largely in their own hands.

“It does put control in the hands of women for the very first time in a really meaningful way,” she says.

That control matters. Both Gollub and Charles emphasize that women’s HIV risk is often tied to broader issues of power, autonomy, and gender inequality. In many contexts, young women may not be able to negotiate condom usage, openly seek sexual health services, or disclose that they are using HIV prevention.

Charles notes that provider buy-in is especially important in communities, particularly patrilineal ones, where health care workers hold significant authority and power. In that sense, providers are not simply delivering a new method, they are the bridge between a promising biomedical innovation and the women who may benefit from it.

“You’re talking about a society that does not question authority,” she says. “Therefore, if the provider does not embrace the treatment, they will not pass it on.”

The study finds that providers are enthusiastic about the ring as an additional HIV prevention option, particularly because it may address some barriers associated with existing PrEP methods. Providers cite concerns that some people fear injections, others dislike swallowing tablets, and others forget to take daily pills. They also see the ring’s privacy as a major advantage for young women who may fear stigma from partners and parents, or community members as a whole.

At the same time, providers identify real implementation challenges, including community misconceptions, partner resistance, supply issues, policy barriers around sexual health education, and the need for provider training. The study also finds that male involvement is critical. Although the ring may offer women more autonomy, providers emphasize that educating men and gaining their support could help reduce resistance and improve uptake.

“One thing that came out was that we need men. We need their buy-in,” Charles says. “No matter how we circle it, how we approach it, men still have a say in this conversation.”

That insight reflects the complexity of global public health work: successful uptake requires more than a product. It requires trust, education, cultural awareness, and partnership. The research shows that health care providers can play a pivotal role in translating scientific progress into community-level impact.

“One thing that came out was that we need men. We need their buy-in,” Charles says. “No matter how we circle it, how we approach it, men still have a say in this conversation.”

The project also demonstrates the strength of interdisciplinary collaboration at Pace’s College of Health Professions. Gollub brings expertise in HIV/AIDS epidemiology and public health, while Charles brings deep experience in nursing, community health, and global health education. Together, they partnered with Babies and Mothers Alive Foundation, a Ugandan-led organization focused on reproductive, maternal, and newborn health.

That local partnership was central to the project’s success. Rather than approaching the work as outside researchers entering a community, collecting data, and leaving, the Pace faculty collaborated with partners who understood the local health system, the providers, and the communities involved.

“We really worked with an ongoing collaboration with that site,” Gollub says. “We all put in different skills, and we made this wonderful mosaic.”

Charles describes the experience as a learning opportunity on both sides.

“In the process, we learn what it takes to do global study,” she says. “Each side learned something.”

That collaborative approach is central to the impact of the work. By listening to providers already embedded in local health systems, the research identifies practical steps that could improve training, counseling, outreach, and policy as the PrEP ring becomes more widely available.

The implications extend beyond Uganda. As Gollub notes, research in one setting can inform HIV prevention for women globally, including in the United States.

“The research that we do anywhere is going to support women getting access to HIV tools everywhere,” she says.

For Pace, the study is a powerful example of faculty research that connects public health innovation with real human need. It reflects CHP’s commitment to socially responsive, globally minded health education and to preparing health professionals who understand that improving care means understanding people, communities, and systems.

Charles puts the global stakes simply: “What happens to your neighbor eventually happens to you.”

Through their work, Charles and Gollub are helping ensure that more women have access not only to HIV prevention tools, but also to choices, information, and support. In global health, that is a major win.