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Frameworks, core principles and top case studies for SaaS pricing, learnt and refined over 28+ years of SaaS-monetization experience.
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Artificial intelligence has evolved dramatically over the past few years, but perhaps nothing is more exciting than the emergence of agentic AI. Unlike traditional AI systems that simply respond to queries, agentic AI can take initiative, make decisions, and execute multi-step tasks with minimal human oversight. For SaaS companies spanning multiple horizontal categories—from marketing to finance to HR—these capabilities represent a transformative opportunity.
But what exactly are the realistic applications available today or on the near horizon? Let's explore 28 practical use cases for agentic AI across horizontal SaaS categories that could fundamentally change how businesses operate.
What Is Agentic AI?
Before diving into specific use cases, let's clarify what makes agentic AI different from traditional AI systems. Agentic AI refers to AI systems that can:
- Act autonomously to accomplish goals
- Plan and execute multi-step processes
- Learn from outcomes to improve future performance
- Interface with various systems and tools
- Make decisions based on contextual understanding
These AI agents don't just answer questions—they solve problems by taking action.
Customer Service & Support
1. Autonomous Support Ticket Resolution
AI agents can triage, investigate, and resolve support tickets without human intervention. By accessing knowledge bases, previous similar cases, and customer data, these agents can handle routine issues from start to finish, only escalating truly complex situations.
2. Proactive Customer Success Monitoring
Instead of waiting for problems, agentic AI can continuously monitor customer usage patterns, identify potential issues before they become problems, and reach out proactively with solutions or assistance.
3. Guided Product Onboarding
AI agents can serve as personalized onboarding specialists, guiding new users through product setup and training based on their specific role, industry, and objectives—dynamically adjusting the process based on user actions and questions.
4. Customer Feedback Analysis & Implementation
Beyond simple sentiment analysis, agentic AI can process customer feedback, identify actionable insights, prioritize suggested improvements, and even draft implementation plans for product teams.
Sales & Marketing
5. Intelligent Lead Qualification & Routing
AI agents can evaluate incoming leads based on multiple data points, conduct initial engagement to gather additional information, and route prospects to the appropriate sales representatives with comprehensive context notes.
6. Personalized Content Generation Campaigns
Rather than one-off content creation, agentic AI can develop and execute multi-touch content campaigns, generating personalized assets for different stages of the buyer journey and adapting based on engagement metrics.
7. Competitor Intelligence Gathering
AI agents can continuously monitor competitor websites, social media, and product updates to compile comprehensive competitive intelligence reports, highlighting changes and strategic implications.
8. Autonomous A/B Test Management
From hypothesis development to test design, implementation, analysis, and application of learnings, agentic AI can manage the entire A/B testing lifecycle across marketing channels.
Finance & Operations
9. Expense Anomaly Detection & Investigation
When unusual expenses appear, AI agents can investigate by gathering context, requesting explanations from employees, cross-referencing policies, and either approving or flagging for human review with a complete audit trail.
10. Intelligent Cash Flow Forecasting
AI agents can combine historical data, current receivables/payables, seasonal trends, and macroeconomic indicators to generate dynamic cash flow forecasts and suggest optimization strategies.
11. Autonomous Accounts Receivable Management
From sending initial invoices to following up on late payments with appropriately escalating communications, AI agents can manage the entire collections process while maintaining positive customer relationships.
12. Vendor Contract Optimization
AI agents can analyze vendor contracts, identify opportunities for consolidation or renegotiation, and even conduct initial negotiation conversations to secure better terms.
Human Resources
13. Complete Candidate Sourcing & Screening
AI agents can search across multiple platforms for candidates, conduct initial screening conversations, administer skills assessments, check references, and present hiring managers with comprehensive candidate packages.
14. Personalized Employee Onboarding
Beyond standard checklists, agentic AI can create customized onboarding experiences, schedule appropriate introductions, provide just-in-time training, and check in regularly during an employee's first months.
15. Proactive Retention Management
By monitoring signals like decreased engagement, missed promotions, or market compensation changes, AI agents can identify flight risks and suggest personalized retention strategies to managers.
16. Continuous Learning Program Development
AI agents can create customized learning paths for employees based on their roles, goals, and skill gaps, continuously updating recommended resources and tracking progress.
Project Management
17. Autonomous Project Status Tracking
Instead of asking for updates, AI agents can monitor various systems, analyze progress, identify blockers, and compile comprehensive status reports without disrupting team workflow.
18. Intelligent Resource Allocation
When new projects arise, AI agents can analyze current workloads, skills needed, and priorities to recommend optimal resource allocation and scheduling.
19. Meeting Efficiency Optimization
AI agents can prepare for meetings by gathering relevant documents, summarizing previous discussions, creating agendas based on outstanding items, and following up on action items afterward.
20. Risk Identification & Mitigation Planning
By analyzing project plans against historical data, AI agents can proactively identify potential risks, suggest mitigation strategies, and monitor for early warning signs.
IT & Security
21. Continuous Security Posture Management
AI agents can continuously scan systems, evaluate configurations against best practices, identify vulnerabilities, and either remediate issues automatically or create prioritized action plans.
22. Intelligent Incident Response
When security incidents occur, AI agents can contain the immediate threat, gather relevant logs and information, initiate predetermined response protocols, and provide comprehensive incident briefings.
23. Automated User Access Reviews
AI agents can conduct regular access reviews by gathering activity logs, comparing access to role requirements, identifying anomalies, and either making or recommending access changes.
24. System Performance Optimization
Rather than just monitoring, agentic AI can identify performance bottlenecks, test potential solutions in non-production environments, and implement optimizations with minimal disruption.
Data & Analytics
25. Continuous Data Quality Management
AI agents can monitor incoming data, identify quality issues, investigate root causes, implement corrections, and maintain comprehensive data quality metrics.
26. Insight Generation & Distribution
Beyond creating reports, agentic AI can identify meaningful patterns in data, generate insights tailored to different stakeholders, and distribute findings through appropriate channels.
27. Data Pipeline Maintenance & Optimization
AI agents can monitor data pipelines, troubleshoot failures, optimize performance, and adapt to changing data structures or volumes.
28. Contextual Analytics Assistance
When users are examining data, AI agents can proactively suggest relevant additional analyses, explain unexpected patterns, and translate complex statistics into business implications.
The Future of Work with Agentic AI in SaaS
As these examples demonstrate, agentic AI isn't just automating tasks—it's transforming entire workflows and enabling new capabilities. The most successful SaaS companies will be those that effectively combine human and artificial intelligence, allowing each to focus on their strengths.
For humans, this means less time spent on routine processes and more capacity for creative thinking, relationship building, and strategic decision-making. For businesses, it means unprecedented efficiency, consistency, and scalability.
However, implementing agentic AI successfully requires thoughtful consideration of:
- Clear scope and boundaries for AI agent authority
- Appropriate human oversight mechanisms
- Training on company-specific processes and values
- Integration with existing systems and workflows
- Change management for affected teams
The transition to agentic AI won't happen overnight, but forward-thinking SaaS companies are already beginning their journey. Those who effectively harness these capabilities will likely establish significant competitive advantages in their respective markets.
Which of these use cases would create the most value for your organization? The answer probably depends on your current pain points, but the potential of agentic AI to transform horizontal SaaS categories is clear. The question isn't if these capabilities will become mainstream, but rather when—and which companies will lead the way.