Discover

Top AI Citation Management Tools: EndNote, Mendeley, RefWorks, Zotero

Aug 26, 2025 |

26 Mins Read

AI is now being built into some of these tools. These citation management tools are designed to help you with tasks like sorting references, checking for errors, or suggesting relevant sources.

This article explains how citation management works, what challenges it addresses, and how AI is being used in tools like Zotero, EndNote, Mendeley, and RefWorks.

What is citation management and why is it important

Citation management is the process of collecting, organising, and formatting reference information used in academic writing. A reference manager is software that helps with this process by storing citation details and generating bibliographies in different styles.

Writing citations by hand takes time and can lead to mistakes. Formatting errors, missing information, or inconsistent styles are common when done manually.

Citation management tools reduce these errors by automating formatting and organising references into folders or collections. Many of these tools also allow users to import references directly from academic databases.

AI is now improving citation management in several ways:

Automation: AI can detect duplicate entries and organise references automatically
Extraction: It can pull citation information from PDFs and websites
Suggestions: Some tools recommend related research based on your existing library

Comparing Zotero, EndNote, Mendeley, and RefWorks

These four citation management tools help you collect, organise, and cite research sources, but they are built for different users and needs.

Zotero is free, open-source software popular with students and independent researchers. EndNote is often used by institutions and professional researchers working with large reference collections. Mendeley combines reference management with academic networking features. RefWorks is a cloud-based tool designed for institutional use.

Tool	Cost	Platform	Storage
Zotero	Free (basic)	Windows, Mac, Linux	300MB free
EndNote	Paid	Windows, Mac	Unlimited (desktop)
Mendeley	Free (basic)	Windows, Mac, Web, Mobile	2GB free
RefWorks	Subscription	Web-based	Unlimited with subscription

Each tool uses AI differently. Zotero supports plugins that add AI features like citation suggestions. EndNote has tools to find full-text PDFs automatically. Mendeley includes AI recommendations for related research. RefWorks uses AI for document organisation.

Essential AI features for modern reference manager tools

AI in reference managers helps automate tasks that would otherwise be time-consuming and error-prone. These features support accuracy in citation formatting, help organise references, and assist with discovering new sources.

1. Automatic metadata extraction

Automatic metadata extraction uses AI to read documents and pull out citation details like author names, titles, and publication dates. This works by scanning PDFs or web pages and identifying citation patterns.

When you add a PDF to your library, the AI analyses the document structure, looking for title pages, author information, and reference sections. It then creates a citation entry with this information.

This feature is especially helpful when you are importing many documents at once. Zotero and Mendeley both excel at metadata extraction, making them popular citation software for Word integration.

2. Recommendation engines for research discovery

Recommendation engines suggest articles related to ones already in your library. These engines analyse your saved references and reading patterns to find similar research.

For example, if your reference manager contains several papers about climate change, the AI might suggest new climate research that cites or is cited by your saved papers.

Mendeley's recommendation feature examines your library content and suggests related papers from its database of millions of articles. EndNote offers similar functionality through its Web of Science integration.

3. Smart collaboration capabilities

Smart collaboration features help teams manage shared reference libraries. AI helps detect duplicate entries, suggest relevant collaborators, and manage editing conflicts.

For group projects, these features keep shared libraries organised and consistent. When multiple team members add references, AI can identify duplicates even when citation details vary slightly.

RefWorks and Mendeley offer strong collaboration tools. RefWorks allows real-time sharing and editing, while Mendeley lets groups share annotations and organise references together.

Pros and cons of each citation manager

Zotero

Zotero is a free, open-source citation manager developed by a non-profit organisation. It works through a desktop application and browser connector.

Strengths:

Free to use with basic features
Strong community support and regular updates
Excellent at capturing web content and metadata
Works well with both Word and Google Docs

Limitations:

Limited storage (300MB) on free accounts
Fewer built-in AI features compared to commercial options
Basic collaboration tools

Zotero is ideal for students, independent researchers, and anyone who wants a free, reliable citation manager without complex features.

EndNote

EndNote is a commercial citation manager with advanced formatting capabilities. It's commonly used in academic and research institutions.

Strengths:

Powerful formatting options for complex documents
Strong integration with academic databases
Comprehensive search capabilities within the tool
Robust handling of large reference libraries

Limitations:

Requires purchase (though many institutions provide access)
Steeper learning curve than other tools
Less intuitive interface for beginners

EndNote works best for professional researchers, faculty members, and others who need advanced citation features and have institutional support.

Mendeley

Mendeley combines reference management with social networking features. It's owned by Elsevier, a global leader in advanced information and decision support for science and healthcare.

Strengths:

Social features to connect with other researchers
Good PDF annotation and reading tools
AI-powered article recommendations
Free basic version with 2GB storage

Limitations:

Some users have privacy concerns due to Elsevier ownership
Sync issues reported by some users
Premium features require subscription

Mendeley is particularly good for researchers who want to discover new content and connect with colleagues while managing their references.

RefWorks

RefWorks is a web-based citation manager typically accessed through institutional subscriptions. It focuses on ease of use and collaboration.

Strengths:

No software installation required
Good for team projects and collaboration
Works on any computer with internet access
Strong institutional support features

Limitations:

No free version for individual users
Fewer customisation options than other tools
Requires internet connection for most functions

RefWorks is best for students and researchers at institutions with RefWorks subscriptions who need simple, accessible citation management.

Zotero vs EndNote vs Mendeley vs RefWorks: which is best?

The best citation manager depends on your specific needs. There's no one-size-fits-all answer to the Zotero vs EndNote vs Mendeley vs RefWorks question.

For students and budget-conscious users, Zotero offers the best balance of features and cost. Its free version includes all essential functions, and it's relatively easy to learn.

For professional researchers working with large libraries, EndNote provides powerful organisation and formatting tools. Its advanced search functions and database integration justify the cost for many users.

For collaborative teams, both Mendeley and RefWorks offer good sharing features. Mendeley adds social networking, while RefWorks focuses on institutional access and ease of use.

When comparing specific tools:

Zotero vs EndNote: Zotero is free and simpler; EndNote offers more advanced features but costs money
Zotero vs Mendeley: Zotero has better browser integration; Mendeley offers better PDF reading tools
EndNote vs Mendeley: EndNote has more formatting options; Mendeley includes social features
Mendeley vs Zotero: Mendeley offers better recommendations; Zotero has a more open ecosystem

In addition, Zendy works alongside these citation tools by helping users discover and access research content before organising it in their citation manager of choice.

Tips for faster citation software for Word integration

All four major citation managers integrate with Microsoft Word, allowing you to insert citations while writing. This integration saves time and reduces errors.

Installing the plugin

For Zotero, the Word plugin installs automatically with the desktop application. After installation, check Word for a "Zotero" tab in the ribbon.

EndNote's "Cite While You Write" plugin also installs with the main program. If it doesn't appear in Word, open EndNote and select "Customize" to enable it.

Mendeley requires downloading "Mendeley Cite" separately from their website. This add-in works with recent versions of Word.

RefWorks uses the "RefWorks Citation Manager" add-in, which can be installed from Word's Add-ins store.

If a plugin doesn't appear, try restarting Word or checking that your citation manager is running.

Adding citations to your document

To add citations with Zotero, click the "Add/Edit Citation" button in Word. A search box appears where you can type author names or keywords to find references in your library.

With EndNote, use the "Insert Citation" button, then search your library. You can also insert multiple citations at once.

Mendeley Cite shows a sidebar where you can search your library and click references to insert them.

RefWorks Citation Manager also uses a sidebar approach, with search functionality and citation preview.

All these tools format citations according to your chosen style (APA, MLA, Chicago, etc.) and automatically create a bibliography at the end of your document.

Looking ahead: how AI shapes the future of citation management

AI is changing how researchers manage citations and discover new research. Future developments will likely make these tools even more helpful.

Natural Language Processing (NLP) is improving how citation tools extract information from documents. This means more accurate automatic citations from PDFs and web pages.

AI tools are getting better at suggesting relevant research based on your existing library and reading patterns. This helps researchers discover important work they might otherwise miss.

Some citation tools are beginning to explore integration with generative AI to help summarise articles, identify key citations, and even assist with literature reviews.

Zendy complements these citation managers with AI-powered research discovery and organisation tools. Its features help researchers find relevant content before adding it to their citation libraries.

The best citation managers will continue incorporating AI to make research workflows more efficient while maintaining accuracy and proper attribution.

Frequently asked questions about AI citation management

How do I choose between Zotero, EndNote, Mendeley, and RefWorks?

Consider your budget (Zotero is free, EndNote is paid), collaboration needs (RefWorks and Mendeley excel here), and institutional support (many universities provide EndNote or RefWorks). Try the free version of any tool before committing to see which interface you prefer.

Can I transfer my references between different citation managers?

Yes, most citation managers support exporting and importing references using standard formats like RIS or BibTeX. The transfer usually preserves basic citation information, though some custom notes or organisation may require adjustment.

Which citation manager has the best AI features currently?

Mendeley offers the strongest built-in AI features, particularly for research recommendations. EndNote provides powerful search and organisation tools. Zotero supports AI features through community-developed plugins.

Do citation managers work with Google Docs as well as Microsoft Word?

Zotero and RefWorks have direct Google Docs integration. Mendeley and EndNote have more limited Google Docs support, with EndNote requiring workarounds to use with Google's platform.

Are the AI features in citation managers difficult to use for beginners?

Most AI features in citation managers work automatically in the background. Features like metadata extraction happen when you add documents, while recommendations appear as suggestions. These require little technical knowledge to use effectively.

From Curator to Digital Navigator: Evolving Roles for Modern Librarians

With the growing integration of digital technologies in academia, librarians are becoming facilitators of discovery. They play a vital role in helping students and researchers find credible information, use digital tools effectively, and develop essential research skills. At Zendy, we believe this shift represents a new chapter for librarians, one where they act as mentors, digital strategists, and AI collaborators. Zendy’s AI-powered research assistant, ZAIA, is one example of how librarians can enhance their work using technology. Librarians can utilise ZAIA to assist users in clarifying research questions, discovering relevant papers more efficiently, and understanding complex academic concepts in simpler terms. This partnership between human expertise and AI efficiency allows librarians to focus more on supporting critical thinking, rather than manual searching. According to our latest survey, AI in Education for Students and Researchers: 2025 Trends and Statistics, over 70% of students now rely on AI for research. Librarians are adapting to this shift by integrating these technologies into their services, offering guidance on ethical AI use, research accuracy, and digital literacy. However, this evolution also comes with challenges. Librarians must ensure users understand how to evaluate AI-generated content, check for biases, and verify sources. The focus is moving beyond access to information, it’s now about ensuring that information is used responsibly and critically. To support this changing role, here are some tools and practices modern librarians can integrate into their workflows: AI-Enhanced DiscoveryUsing tools like ZAIA to help researchers refine queries and find relevant studies faster. Research Data Management Organising, preserving, and curating datasets for long-term academic use. Ethical AI and Digital Literacy Training Teaching researchers how to verify AI outputs, evaluate bias, and maintain academic integrity. Collaborative Digital Spaces Facilitating research communication through online repositories and discussion platforms. In conclusion, librarians today are more than curators, they are digital navigators shaping how knowledge is accessed, evaluated, and shared. As technology continues to evolve, so will its role in guiding researchers and students through the expanding world of digital information. .wp-block-image img { max-width: 65% !important; margin-left: auto !important; margin-right: auto !important; }

Nov 25, 202512 Mins ReadDiscover

Strategic AI Skills Every Librarian Must Develop

In 2026, librarians who understand how AI works will be better equipped to support students and researchers, organise collections, and help patrons find reliable information faster. Developing a few key AI skills can make everyday tasks easier and open up new ways to serve your community. Why AI Skills Matter for Librarians AI tools that recommend books, manage citations, or answer basic questions are becoming more common. Learning how these tools work helps librarians: Offer smarter, faster search results. Improve cataloguing accuracy. Provide better guidance to researchers and students. Remember, AI isn’t replacing professional judgment; it’s supporting it. Core AI Literacy Foundations Before diving into specific tools, it helps to understand some basic ideas behind AI. Machine Learning Basics:Machine learning means teaching a computer to recognise patterns in data. In a library setting, this could mean analysing borrowing habits to suggest new titles or resources. Natural Language Processing (NLP):NLP is what allows a chatbot or search tool to understand and respond to human language. It’s how virtual assistants can answer questions like “What are some journals about public health policy?” Quick Terms to Know: Algorithm: A set of steps an AI follows to make a decision. Training Data: The information used to “teach” an AI system. Neural Network: A type of computer model inspired by how the brain processes information. Bias: When data or systems produce unfair or unbalanced results. Metadata Enrichment With AI Cataloguing is one of the areas where AI makes a noticeable difference. Automated Tagging: AI tools can read through titles and abstracts to suggest keywords or subject headings. Knowledge Graphs: These connect related materials, for example, linking a book on climate change with recent journal articles on the same topic. Bias Checking: Some systems can flag outdated or biased terminology in subject classifications. Generative Prompt Skills Knowing how to “talk” to AI tools is a skill in itself. The clearer your request, the better the result. Try experimenting with prompts like these: Research Prompt: “List three recent studies on community reading programs and summarise their findings.” Teaching Prompt: “Write a short activity plan for a workshop on evaluating online information sources.” Summary Prompt: “Give me a brief overview of this article’s key arguments and methods.” Adjusting tone or adding detail can change the outcome. It’s about learning how to guide the tool rather than letting it guess. Ethical Data Practices AI tools can be useful, but they also raise questions about privacy and fairness. Librarians have always cared deeply about protecting patron information, and that remains true with AI. Keep personal data anonymous wherever possible. Review AI outputs for signs of bias or misinformation. Encourage clear policies around how data is stored and used. Ethical AI is part of a librarian’s duty to maintain trust and fairness. Automating Everyday Tasks AI can take over some of the small, routine jobs that fill up a librarian’s day. Circulation: Systems can send overdue reminders automatically or manage renewals. Chatbots: Basic questions like “What are the library hours?” can be handled instantly. Collection Management: AI can spot patterns in borrowing data to suggest which books to keep, reorder, or retire. Building Your Learning Path Getting comfortable with AI doesn’t have to mean earning a new degree. Start small: Take short online courses or micro-certifications in AI literacy. Join librarian groups or online forums where people share practical tips. Block out one hour a week to try out a new tool or attend a webinar. A little consistent learning goes a long way. Making AI Affordable Many smaller libraries worry about cost, but not every tool is expensive. Free Tools: Some open-access AI platforms, like Zendy, offer affordable access to research databases and AI-powered features. Shared Purchases: Partnering with other libraries to share licenses can cut costs. Cloud Services: Pay-as-you-go plans mean you only pay for what you actually use. There’s usually a way to experiment with AI without stretching the budget. Showing Impact Once AI tools are in use, it’s important to show their value. Track things like: Time saved on cataloguing or circulation tasks. Patron feedback on new services. How often are AI tools used compared to manual systems? Numbers matter, but so do stories. Sharing examples, like a student who found research faster thanks to a new search feature, can make your case even stronger. And remember, the future of librarianship is about using AI tools in libraries thoughtfully to keep libraries relevant, reliable, and welcoming spaces for everyone. .wp-block-image img { max-width: 75% !important; margin-left: auto !important; margin-right: auto !important; }

Nov 25, 202511 Mins ReadDiscover

Key Considerations for Training Library Teams on New Research Technologies

The integration of Generative AI into academic life appears to be a significant moment for university libraries. As trusted guides in the information ecosystem, librarians are positioned to help researchers explore this new terrain, but this transition requires developing a fresh set of skills. Training your library team on AI-powered research tools could move beyond technical instruction to focus on critical thinking, ethical understanding, and human judgment. Here is a proposed framework for a training program, organised by the new competencies your team might need to explore. Foundational: Understanding Access and Use This initial module establishes a baseline understanding of the technology itself. Accessing the Platform: Teach the technical steps for using the institution's approved AI tools, including authentication, subscription models, and any specific interfaces (e.g., vendor-integrated AI features in academic databases, institutional LLMs, etc.). Core Mechanics: Explain what a Generative AI platform (like a Large Language Model) is and, crucially, what it is not. Cover foundational concepts like: Training Data: Familiarise staff with how to access the institution’s chosen AI tools, noting any specific authentication requirements or limitations tied to vendor-integrated AI features in academic databases. Prompting Basics: Introduce basic prompt engineering, the art of crafting effective, clear queries to get useful outputs. Hallucinations: Directly address the concept of "hallucinations," or factually incorrect/fabricated outputs and citations, and emphasise the need for human verification. Conceptual: Critical Evaluation and Information Management This module focuses on the librarian's core competency: evaluating information in a new context. Locating and Organising: Train staff on how to use AI tools for practical, time-saving tasks, such as: Generating keywords for better traditional database searches. Summarising long articles to quickly grasp the core argument. Identifying common themes across a set of resources. Evaluating Information: This is perhaps the most critical skill. Teach a new layer of critical information literacy: Source Verification: Always cross-check AI-generated citations, summaries, and facts against reliable, academic sources (library databases, peer-reviewed journals). Bias Identification: Examine AI outputs for subtle biases, especially those related to algorithmic bias in the training data, and discuss how to mitigate this when consulting with researchers. Using and Repurposing: Demonstrate how AI-generated material should be treated—as a raw output that must be heavily edited, critiqued, and cited, not as a final product. Social: Communicating with AI as an Interlocutor The quality of AI output is often dependent on the user’s conversational ability. This module suggests treating the AI platform as a possible partner in a dialogue. Advanced Prompt Engineering: Move beyond basic queries to teach techniques for generating nuanced, high-quality results: Assigning the AI a role (such as a 'sceptical editor' or 'historical analyst') to potentially shape a more nuanced response. Practising iterative conversation, where librarians refine an output by providing feedback and further instructions, treating the interaction as an ongoing intellectual exchange. Shared Understanding: Practise using the platform to help users frame their research questions more effectively. Librarians can guide researchers in using the AI to clarify a vague topic or map out a conceptual framework, turning the tool into a catalyst for deeper thought rather than a final answer generator. Socio-Emotional Awareness: Recognising Impact and Building Confidence This module addresses the human factor, building resilience and confidence Recognising the Impact of Emotions: Acknowledge the possibility of emotional responses, such as uncertainty about shifting professional roles or discomfort with rapid technological change, and facilitate a safe space for dialogue. Knowing Strengths and Weaknesses: Reinforce the unique, human-centric value of the librarian: critical thinking, contextualising information, ethical judgment, and deep disciplinary knowledge, skills that AI cannot replicate. The AI could be seen as a means to automate lower-level tasks, allowing librarians to focus on high-value consultation. Developing Confidence: Implement hands-on, low-stakes practice sessions using real-world research scenarios. Confidence grows from successful interaction, not just theoretical knowledge. Encourage experimentation and a "fail-forward" mentality. Ethical: Acting Ethically as a Digital Citizen Ethical use is the cornerstone of responsible AI adoption in academia. Librarians must be the primary educators on responsible usage. Transparency and Disclosure: Discuss the importance of transparency when utilizing AI. Review institutional and journal guidelines that may require students and faculty to disclose how and when AI was used in their work, and offer guidance on how to properly cite these tools. Data Privacy and Security: Review the potential risks associated with uploading unpublished, proprietary, or personally identifiable information (PII) to public AI services. Establish and enforce clear library policies on what data should never be shared with external tools. Copyright and Intellectual Property (IP): Discuss the murky legal landscape of AI-generated content and IP. Emphasise that AI models are often trained on copyrighted material and that users are responsible for ensuring their outputs do not infringe on existing copyrights. Advocate for using library-licensed, trusted-source AI tools whenever possible. Combating Misinformation: Position the librarian as the essential arbiter against the spread of AI-generated misinformation. Training should include spotting common AI red flags, teaching users how to think sceptically, and promoting the library’s curated, authoritative resources as the gold standard. .wp-block-image img { max-width: 65% !important; margin-left: auto !important; margin-right: auto !important; }

Return to blogs

Accelerating Research