Top 10 Cons & Disadvantages of Using Confluence

Confluence has evolved into a full AI-powered workspace, weaving together documents, whiteboards, databases, video, and organization-wide knowledge. Atlassian’s new Rovo AI now drafts content, summarizes pages, and searches across all connected tools. Yet even with these innovations, Confluence still introduces friction points that can slow teams down. Understanding these drawbacks helps teams prepare, adapt, and choose the right collaboration structure for their organization. Confluence’s appeal lies in its promise of one unified workspace where teams can think, plan, document, and collaborate.

With Atlassian’s 2025 overhaul—introducing Live Docs, AI drafting, AI-powered search, multi-app connectors, and Teamwork Collection bundles—Confluence now aims to replace traditional documentation tools entirely. But innovation brings complications. Users still face performance delays, steep learning curves, messy permissions, limited customization, and cost creep. Knowing these issues upfront helps teams prevent disruptions, scale responsibly, and avoid painful inefficiencies.

What Is Confluence?

Confluence is Atlassian’s AI-powered workspace designed to centralize documentation, accelerate team collaboration, and unify organization-wide knowledge. The 2025 version integrates Rovo AI for instant drafting, smarter search, and automated summaries while supporting flexible content types like Live Docs, Whiteboards, and Databases. Confluence now acts as a connected hub where teams plan, document, and align work across multiple tools and distributed environments.

Key Features of Confluence

• Live Docs: Real-time collaborative documents with AI-assisted editing and structuring.
• Whiteboards: Visual canvases for brainstorming, diagramming, and mapping workflows.
• Databases: Structured, customizable content tables for organized tracking and knowledge management.
• Rovo AI Drafting: Instant page creation, summaries, rewriting, and cross-document insights.
• AI-Powered Search: Unified search across Confluence, Slack, Google Drive, GitHub, Jira, and connected tools.
• Templates Library: Prebuilt templates for product plans, briefs, policies, and strategy documents.
• Team Spaces: Organized areas for departments, projects, or cross-functional initiatives.
• Deep Integrations: Connects with Jira, Slack, Figma, Miro, Loom, Google Workspace, and more.
• Video & Async Tools: Built-in video pages and summaries for clearer distributed communication.
• Teamwork Collection Compatibility: Works seamlessly with Jira, Loom, and Rovo for a unified work ecosystem.

Real-Life Example: A distributed product team uses Confluence to manage roadmaps, architecture documentation, and launch briefs. Rovo AI drafts initial pages while Databases track requirements and decisions. Jira integration links tickets directly to documents, creating a streamlined environment where planning, execution, and documentation stay perfectly aligned across time zones.

Top 10 Cons & Disadvantages of Using Confluence

Understanding Confluence’s limitations is essential before committing your organization’s resources and workflows to the platform. While Confluence offers powerful collaboration features, its drawbacks can significantly impact productivity, user adoption, and operational costs. Recognizing these challenges upfront allows teams to implement mitigation strategies, set realistic expectations, and make informed decisions about whether Confluence aligns with their specific needs and technical capabilities.

Below are the ten most significant disadvantages users commonly encounter:

1. AI Drafting Produces Inconsistent and Generic Output

Rovo AI speeds up drafting, but the content quality is inconsistent. Teams often receive vague, generic, or structurally incorrect pages that require substantial rewriting. This undermines the intended productivity boost and frustrates users who expect polished first drafts. Without strong internal content standards, AI-generated documents create more rework than value—especially in teams with strict tone, accuracy, and compliance requirements.

Key challenges behind this issue:

• AI often misinterprets technical requirements, producing superficial content.
• Output rarely matches brand voice without heavy manual correction.
• Multi-agent drafting generates inconsistent structure across related pages.

Real-Life Example: A product team used Rovo AI to draft a requirements page but discovered missing constraints, inaccurate assumptions, and unclear terminology. The AI produced a passable outline, but the team spent nearly two hours rewriting every section. Instead of speeding up documentation, the tool delayed sprint planning, forcing engineers to wait until the corrected content was ready for review.

Solution: Create AI style guides, enforce mandatory templates, and require human review before publishing AI-generated material. This reduces rewrites and ensures Rovo aligns with team expectations, resulting in far more reliable productivity gains.

2. Performance Slows Down in Large, Content-Heavy Spaces

Confluence struggles when spaces contain thousands of pages, databases, and large whiteboards. Loading delays appear frequently, especially when using anchors, macros, heavy media, or multiple integrations. AI search indexing also becomes slower at scale. As content volume expands, users experience longer wait times, reduced responsiveness, and inconsistent performance—disrupting day-to-day workflows and slowing decision-making during high-pressure moments.

Main drivers behind this bottleneck:

• Heavy pages with embedded media load noticeably slower.
• AI search indexing deteriorates when many apps are connected.
• Large whiteboards render inconsistently, affecting real-time collaboration.

Real-Life Example: A global HR department maintained hundreds of policy pages inside a shared space. After connecting Slack, Google Drive, and Jira, searches that previously took seconds began taking 10–15 seconds. Employees complained that retrieving essential compliance guidelines was too slow, forcing them to bypass Confluence entirely and rely on outdated local file copies.

Solution: Archive unused spaces, compress media-heavy pages, and reduce unnecessary connectors. Establish a structured space hierarchy to minimize indexing strain and improve platform stability across large teams.

3. Permission Complexity Causes Access Confusion and Security Risks

Confluence offers detailed permission control, but the system is confusing. Space-level, page-level, and group-level rules often conflict, creating inconsistent access outcomes. As organizations scale, administrators must constantly resolve permission errors. AI summaries add new risks by exposing information indirectly. Misconfigurations can disrupt collaboration, leak sensitive content, or block key contributors from accessing essential documents.

Underlying factors contributing to confusion:

• Layered permission rules override each other unpredictably.
• Space defaults often ignore intended page-level restrictions.
• AI summaries can surface restricted content unintentionally.

Real-Life Example: A financial firm discovered confidential engineering notes appearing in Rovo’s AI summaries for employees without proper access. Space settings were misconfigured, and several groups inherited unintended permissions. The incident forced the company to conduct a full audit, tighten controls, and introduce new approval processes—costing significant operational time and producing major internal concern over data exposure.

Solution: Use standardized permission groups, apply space blueprints, and conduct quarterly audits. This reduces accidental exposure and ensures consistent access across all organizational content.

4. Costs Increase Quickly Due to Essential Paid Add-ons

Confluence appears affordable until teams realize many vital functions require paid marketplace apps. Advanced diagramming, workflow automation, reporting tools, and database expansions often come from premium plugins. As requirements grow, subscription costs escalate. Smaller teams frequently underestimate the total expense, leading to budget strain and dependency on third-party vendors for core functionality.

Why costs spiral for many organizations:

• Key collaboration features require separate plugins.
• Workflow automation often depends on premium tools.
• Database extensions frequently involve additional subscriptions.

Real-Life Example: A digital agency migrated from Notion, expecting Confluence to meet all documentation needs. Instead, they purchased multiple plugins for diagramming, analytics, and workflow automation. Their annual cost exceeded $3,600 just for add-ons. Leadership acknowledged that Confluence was powerful but significantly more expensive than originally projected.

Solution: Audit required features beforehand and negotiate enterprise bundles. Consolidate duplicate apps and limit plugin use to prevent cost escalation.

5. Non-Technical Users Face a Steep Learning Curve

Despite UI upgrades, Confluence remains complex for newcomers. Users must learn content types, templates, permissions, databases, whiteboards, and macros. AI suggestions sometimes confuse beginners further. For teams migrating from simpler platforms, the adjustment period is long. Non-technical staff struggle most, creating dependency on experienced users and increasing overall onboarding time.

Key reasons onboarding feels overwhelming:

• Too many content types behave differently.
• Interface updates change workflows yearly.
• AI recommendations introduce unfamiliar structures.

Real-Life Example: A marketing team transitioning from Google Docs spent weeks learning Live Docs, Databases, and Whiteboards. Even basic tasks—like reorganizing page structure—required guidance. Productivity slowed across multiple campaigns as staff relied on IT support to troubleshoot formatting issues and permissions while adapting to Confluence’s multi-layered interface.

Solution: Create structured onboarding programs with role-specific templates. This reduces confusion and accelerates adoption for non-technical contributors.

6. Formatting Breaks During Copy-Paste and Export Operations

Copy-pasting into Confluence frequently produces broken formatting. Fonts, spacing, tables, and lists often shift unpredictably. Exporting to PDF also yields inconsistent results. These issues force users to reformat content manually, slowing workflows—especially when working with legal documents, marketing materials, or externally shared deliverables requiring a polished presentation.

Why formatting fails repeatedly:

• Sanitization breaks complex HTML layouts.
• Imports from Office tools lose styling.
• PDF exports render inconsistently across templates.

Real-Life Example: A compliance team copied policy updates from Word into Confluence. The resulting page contained distorted tables, mismatched bullet styles, and inconsistent spacing. Fixing the layout took nearly two hours. Exporting the final version to PDF made formatting worse, forcing a complete rebuild using a different template.

Solution: Adopt native Confluence templates and limit external copy-paste. Use standardized formatting tokens for consistent presentation across all documents.

7. AI Search Often Delivers Irrelevant or Outdated Results

AI-powered search promises instant answers but frequently misses user intent. It sometimes prioritizes old pages, surfaces irrelevant documents from connected apps, or misinterprets ambiguous queries. This undermines trust in the system, forcing users to manually navigate spaces or browse page trees—slowing productivity and increasing frustration in fast-paced environments.

Contributing factors to search inaccuracy:

• AI overweights outdated yet popular content.
• Connectors introduce irrelevant external material.
• Ambiguous phrasing confuses query interpretation.

Real-Life Example: A support engineer searched for the latest release notes but repeatedly saw outdated pages and unrelated Jira tickets. The AI search ranked old content higher due to historical activity. The engineer had to manually browse multiple spaces to locate the correct version, wasting valuable time during a customer escalations cycle.

Solution: Use strict naming conventions and archive stale pages. Maintain organized space hierarchies to improve AI indexing and result relevance.

8. Whiteboards and Databases Still Lack Advanced Capabilities

Confluence’s Whiteboards and Databases aim to replace Miro and Notion, but they remain limited. Whiteboards slow down in large teams, while databases lack advanced relations, formulas, and filtering. Power users quickly outgrow these tools, forcing teams to return to specialized platforms for complex planning, mapping, or structured content management.

Why these tools fall short:

• Databases lack a deep relational structure.
• Whiteboards lag during heavy collaboration.
• Feature parity with competitors is incomplete.

Real-Life Example: An architecture team attempted to move complex diagramming workflows from Miro to Confluence Whiteboards. They ran into missing connectors, slow zooming, unstable rendering, and limited diagramming features. After multiple failed sessions, the team reverted to Miro for all technical mapping and planning.

Solution: Use Confluence tools for lightweight tasks only. Retain specialized external apps for complex or high-stakes workflows.

9. Administrative Workload Remains High in Growing Organizations

As teams scale, Confluence administration becomes heavy. Space cleanup, permission management, template updates, lifecycle tracking, and duplicate content removal require constant attention. AI helps summarize pages, but cannot replace governance. Many enterprises require dedicated admins to maintain structure and prevent content sprawl.

Major factors increasing admin overhead:

• Frequent template updates require oversight.
• Space bloat creates structural chaos.
• Permissions drift due to organizational changes.

Real-Life Example: A fintech company with thousands of employees accumulated hundreds of duplicated pages during a restructuring. Consolidating content, redesigning templates, and recalibrating permissions took an administrator three weeks. Without ongoing governance, teams repeatedly created redundant material that complicated navigation and diluted trust in documentation accuracy.

Solution: Implement strict governance rules, automate cleanup reminders, and use space blueprints to maintain a consistent structure across the organization.

10. Integrations Still Break or Sync Incorrectly

Confluence supports many integrations, but connectors occasionally malfunction. Previews fail to update, permissions conflict between systems, or tokens expire silently. Because AI depends on connector reliability, integration failures ripple into search, summaries, and recommendations. Teams relying on synced content risk using outdated information during critical reviews.

Issues behind integration instability:

• API tokens expire without warning.
• Third-party rate limits disrupt syncing.
• Permission mismatches cause preview failures.

Real-Life Example: A product team linked Figma prototypes to Confluence. During a stakeholder review, they discovered the embedded preview showed old screens because the Figma token had expired. Key decisions were based on outdated visuals, forcing the team to repeat the meeting and repair damaged credibility.

Solution: Refresh tokens regularly and test critical integrations weekly. Establish fallback workflows for reviews where synced content accuracy is essential.

Overcoming Confluence Challenges

Teams can reduce Confluence friction through structured governance and standardized workflows. Success requires enforcing naming conventions, archiving outdated content, and consolidating plugins to control costs. Train users with template-based onboarding to minimize formatting issues and confusion from new features. Apply centralized permission groups to avoid security risks and perform quarterly audits to maintain order.

• Test Integrations and Refresh Tokens: Regularly refresh API tokens and test critical integrations weekly to prevent sync failures. Establish fallback workflows for important reviews where connector reliability is essential, ensuring teams never base decisions on outdated information.
• Enforce Naming Conventions and Archive Content: Establish strict naming standards across all spaces and regularly archive outdated pages. This improves AI search accuracy, reduces indexing strain, and helps teams locate relevant documents faster while maintaining organizational clarity.
• Consolidate Plugins and Control Costs: Audit required features before purchasing add-ons and negotiate enterprise bundles when possible. Eliminate duplicate plugins and limit marketplace apps to essential functions only, preventing unexpected budget escalation and vendor dependency.
• Implement Template-Based Onboarding: Create structured onboarding programs with role-specific templates and standardized formatting guidelines. This accelerates user adoption, reduces confusion for non-technical staff, and minimizes formatting errors that slow down collaborative workflows.
• Apply Centralized Permission Groups: Use standardized permission groups with space blueprints and conduct quarterly access audits. This prevents accidental data exposure, resolves permission conflicts, and ensures consistent security controls across all organizational content and user levels.
• Use Specialized Tools for Complex Tasks: Reserve Confluence for lightweight diagrams and structured documentation while maintaining specialized external platforms for advanced workflows. This prevents feature limitations from disrupting critical work requiring sophisticated diagramming, database relations, or analytical capabilities.

Video About Confluence

Video resources help users understand Confluence’s strengths, weaknesses, and practical applications. Tutorials cover Rovo AI drafting, Live Docs collaboration, database structuring, and whiteboard workflows. Other videos demonstrate permission management, space organization, and integration troubleshooting. Comparisons between Confluence, Notion, SharePoint, and Google Workspace also highlight use-case differences. The video below provides valuable insights about using Confluence at scale.

Conclusion

Confluence’s evolution into an AI-powered workspace creates new opportunities and new challenges. Rovo AI accelerates drafting and search, but introduces inconsistency. Expanding content types improves collaboration yet increases platform complexity. Performance struggles, administrative overhead, and permission confusion remain persistent issues. Integration failures and cost creep add operational friction for growing organizations.

Despite these limitations, Confluence delivers substantial value when paired with proper governance, structured onboarding, and disciplined content management. Its ability to centralize knowledge, streamline documentation, and align cross-functional teams makes it one of the most capable platforms available. With deliberate planning and strong internal processes, organizations can overcome Confluence’s weaknesses and unlock its full collaborative potential.

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