AI across Elsevier: Advancing human intelligence with trust and integrity
Explore how Elsevier uses responsible artificial intelligence to power trusted research, healthcare and education solutions.

A different way to AI
Discover our AI-driven tools, peer-reviewed content and responsible AI approach, designed to accelerate discovery, improve decision-making and deliver real-world impact across science and health.
AI at Elsevier
We use AI to support impact makers across all fields, from health to education and R&D.
Los investigadores nos indicaron que una de sus principales preocupaciones sobre las herramientas de IA es el sesgo oculto. Por ello, nuestro objetivo es certificar que la metodología de clasificación de LeapSpace sea completamente neutral respecto a editoriales: sin trato preferencial y sin cajas negras.
Professor Jörg-Rüdiger Sack
Responsable del Consejo Asesor de LeapSpace | Presidente del Comité Asesor y de Selección de Contenidos de Scopus | Profesor Emérito en Escuela de Ciencias de la Computación de la Universidad de Carleton (Canadá)
Our approach to AI: Build verifiable AI with governed evidence
Build trusted AI workflows with governed evidence, clear attribution and human oversight.
Understand how Elsevier supports research-grade AI outcomes
Learn what “verifiable” means in practice for teams and institutions
Explore responsible AI governance and quality evaluation
Traditional vs AI research: Align AI workflows to research-grade trust
Discover where AI-assisted research speeds up discovery — and where traditional rigor keeps results reliable.
Compare speed, scale, discovery and reproducibility
See what governance must cover for research-grade trust
Use practical examples to guide adoption decisions
Capture AI value while managing risk and governance
Get a clear, decision-ready view of where AI delivers value and where safeguards matter.
Balance productivity gains with risks to integrity, safety and governance
Identify quality safeguards to look for before rollout
Use an adoption checklist to support responsible implementation
Evidence-based AI that supports better patient outcomes
Elsevier’s approach to AI in health connects clinical needs with trusted research. Learn how AI can help clinicians and researchers:
Find and review evidence faster
Make decisions with traceable, citable sources
Support transparency and accountability in clinical use
Align with responsible AI governance, including privacy and IP protection
Explore how AI can complement expert judgment in healthcare — while preserving the reliability of the scholarly record.
Responsible adoption that protects trust in learning and scholarship
Elsevier helps institutions use AI in ways that strengthen discovery, teaching and research integrity. Explore how AI can be applied with:
Trusted content and evidence traceability
Attribution and transparency for verifiable outcomes
Domain expertise and human oversight
Governance that supports privacy, IP protection, and neutrality
Practical guidance for AI literacy and leadership
Discover what trusted content means for research-grade AI and how academic communities can adopt AI responsibly.
Responsible AI is how Elsevier helps teams deploy AI with confidence — grounded in trusted evidence, privacy and IP protection, neutrality, transparency, and accountability. Explore our responsible AI approach, including the principles and policies that guide how AI should be developed, evaluated and governed.
Latest AI resources
Ver todos los artículos de ConnectAI products from Elsevier
Seminario web | IA en acción: sostenibilidad y eficiencia en la síntesis química





