Elsevier’s Sherpath AI wins Best AI-Powered Tutoring Solution at the 2026 CODiE Awards

Elsevier today announced that Sherpath AI has been named Best AI-Powered Tutoring Solution at the 2026 CODiE Awards, the technology industry’s long-running, peer-reviewed awards program. Winners were revealed following finalist selection and a second-round peer review.

Sherpath AI is a tool to help students and educators navigate courses, exam preparation and the transition into clinical practice. Nursing students can ask questions with natural language in the same way they would speak to a tutor, and Sherpath AI provides answers based on verified, trusted nursing education content with source citations for accuracy. A diverse range of multimedia tutorials increase engagement in learning content.

Brent Gordon, President of Healthcare Education at Elsevier, said: “This fantastic award recognizes the value of combining our evidence-based content with Generative AI to create a truly personalized learning tool for students. Sherpath AI has been able to improve student engagement and help faculty address the capacity challenges institutions face across nursing education, and we are honored to recieve the recognition of this CODiE award.”

This year’s CODiE program recognized excellence across 75 categories and is widely regarded as a premier peer-reviewed recognition of innovation in business and education technology.

Judges praised Sherpath AI for engaging users directly, transparently providing answers based on trusted content, and meeting students where they are, saying “this product checks all the boxes and offers a secure, individualized learning experience.”

You can find out more about Sherpath AI here.

About the CODiE Awards

Founded in 1986, the CODiE Awards recognize companies, products, and leaders shaping the future of technology. The program is known for its rigorous, peer-reviewed evaluation process and trusted reputation for recognizing excellence across software, digital learning, AI, data, cybersecurity, and emerging technologies. Winners are selected through expert judging, transparent evaluation criteria, and community voting.

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