More than 1,100 nursing simulation educators gathered in Oklahoma City for INACSL 2026, themed "Pioneering Possibilities." The DDx team hosted a focus group with prelicensure nursing faculty from programs across the country, walked the floor, and listened carefully to what educators are actually working through at the moment.
Here is what we took away: communication practice is a gap no current tool is closing well, however, one DDx by Sketchy is built to bridge. Faculty are open to AI when it reduces their burden, and nursing programs need a dedicated clinical prep layer. A platform that prepares students for simulation and beyond.
The pressure on nursing programs is structural, not situational
The conditions nursing programs are operating in right now are genuinely difficult. The COVID-19 pandemic accelerated a workforce crisis that had been building for years. According to a 2023 National Council of State Boards of Nursing study, approximately 100,000 registered nurses left the workforce during the pandemic due to burnout and stress, with another 610,000 projected to leave by 2027.
According to AACN's 2025–2026 Enrollment and Graduations report, BSN enrollment grew 7.6% and master's programs grew 6.8% — the strongest growth in years. At the same time, more than 93,000 qualified applicants were turned away from nursing schools in 2025 due to faculty and resource constraints, a record high. Research published in Nursing Outlook and cited in AACN's Faculty Shortage Fact Sheet projected that one-third of the nursing faculty workforce in baccalaureate and graduate programs would retire by 2025, and the pipeline of replacements has not kept pace.
Programs are being asked to prepare more students for clinical practice with fewer faculty and less time. That math does not resolve in a single hiring cycle. And it shapes every conversation about simulation, AI, and what clinical preparation can realistically look like going forward.
What we heard at INACSL 2026
The "Pioneering Possibilities" theme was wise and reflective of the existing opportunities nursing programs currently face. The Hayden Vanguard Lecture, delivered by Dr. Mary Fey of the Harvard Center for Medical Simulation, offered a frame that resonated across the conference: competency-based education becomes transformational not through frameworks alone, but through the quality of the coaching relationship. When faculty time is consumed by setup, logistics, and manual evaluation, those moments become rare.
That framing shaped how we listened in our focus group. The educators in the room represented a range of programs and experience levels and more than half were already using AI-enabled simulation. Nearly 36% were already using virtual simulation to fulfill or replace clinical hours. This was not a group that needed to be convinced simulation has value. They were working through what good simulation actually looks like at the volume and complexity their programs now require.
A few things came through clearly.
Communication is the biggest unmet gap. Across the room, the theme that surfaced most consistently was not clinical knowledge, it was communication confidence. One faculty member from Madison College put it directly: "We want students to be able to say things in a way patients will understand. You spend all this time learning medical terms, but you need to translate them." Every tool in the room had been evaluated partly on this dimension, and most had fallen short. The tools educators named as current solutions were generally rated as adequate for knowledge check but limited for the realistic, interactive patient conversation practice nursing students need.
Clinical judgment development requires knowing the 'why,' not just the 'what.' When we walked through DDx during the session, what landed most was the emphasis on clinical reasoning behind each action. Not just what to do in a given clinical situation, but the why. That distinction matters for the NextGEN NCLEX, which evaluates how students reason through ambiguous clinical situations, not just what they recall. Faculty are looking for tools that make rationale visible, not just assessable.
Where DDx fits and what we are still learning
The focus group made one thing clear: faculty are not looking for more to manage. They are looking for tools that do the heavy lifting so they can focus on the coaching and clinical judgment conversations that only they can have. That is the need DDx is built to meetAnd the focus group confirmed where it lands and where the work continues.
What resonated most:
- AI-enabled patient conversation was the standout feature. Attendees said directly that the conversation piece was "more valuable — that's the biggest gap." No current tool in the room was closing it well.
- Clinical reasoning depth, not just what to do, but why. Faculty reworking curricula around the Next Generation NCLEX recognized the emphasis on reasoning behind each clinical action as the missing layer in their current simulation stack.
- The "clinical prep assignment" frame landed better than "simulation." Educators saw DDx as structured preparation that happens before the manikin or clinical site — additive to what they already have, not a replacement for it.
As one nurse educator from Madison College put it: "We want students to be able to say things in a way patients will understand. You spend all this time learning medical terms, but you need to translate them."
Curious what DDx looks like for undergraduate nursing? See what is ready to implement today!
Frequently asked questions
What is the connection between the Next Generation NCLEX and AI-enabled simulation? The NextGen NCLEX evaluates clinical judgment, how students reason through ambiguous, high-stakes clinical situations rather than discrete knowledge recall. AI-enabled case simulation gives students structured, repeated opportunities to practice that reasoning with realistic feedback, which is difficult to provide at scale through traditional faculty-led simulation alone.
How does AI-enabled clinical preparation differ from traditional nursing simulation? Traditional simulation like manikins, standardized patients, lab-based scenarios are high-touch and faculty-intensive by design. AI-enabled clinical preparation is not a replacement for that; it is multifaceted. However, it functions best as structured pre-simulation work that builds foundational clinical reasoning and communication skills before students enter the lab or clinical site. Faculty in our focus group described it as "good assignments to connect the dots" rather than a simulation alternative.
What communication skills can AI-enabled patient conversations actually develop? The most consistent gap nursing faculty identify is translating clinical knowledge into patient-accessible language. Skills like explaining diagnoses, medications, and care plans in ways patients can understand and act on. AI-powered patient conversation practice gives students a realistic environment to work through that translation repeatedly, with feedback, before those conversations happen with real patients.
Does using AI in clinical preparation reduce faculty involvement? The goal is to reduce faculty burden on routine delivery and evaluation, not to remove faculty from the learning process. When AI handles consistent case delivery, performance analytics, and structured feedback, and remediation planning, faculty are better positioned for the coaching and debrief work that makes simulation and clinical education effective.
What should nursing programs look for when evaluating AI clinical preparation tools? The criteria that surfaced most consistently in our focus group: Does it require significant faculty setup time? Does it generate feedback students can act on, not just scores? Does it cover the case types your curriculum requires, including pediatrics, mental health, and community health? Does it align to AACN Essentials and the NCSBN Clinical Judgment Model? And does it fit into your existing curriculum without requiring a full structural overhaul to adopt?
References
American Association of Colleges of Nursing. (2026). 2025–2026 Enrollment and graduations in baccalaureate and graduate programs in nursing. AACN. https://www.aacnnursing.org
American Association of Colleges of Nursing. (2024). Nursing faculty shortage fact sheet. AACN. https://www.aacnnursing.org/Portals/0/PDFs/Fact-Sheets/Faculty-Shortage-Factsheet.pdf
Fang, D., & Kesten, K. (2017). Retirements and succession of nursing faculty in 2016–2025. Nursing Outlook, 65(5), 633–642.
Nishimura, A., Ota, Y., & Kasahara, Y. (2025). Impact of simulation-based learning and previous academic achievement on clinical judgment in nursing students. JMAJ. https://doi.org/10.31662/jmaj.2025-0299
Street, M., & colleagues. (2025). Comparing artificial intelligence-enhanced virtual reality and simulated patient simulations in undergraduate nursing education. Clinical Simulation in Nursing. https://www.nursingsimulation.org/article/S1876-1399(25)00097-0/fulltext
