.png)
Frameworks, core principles and top case studies for SaaS pricing, learnt and refined over 28+ years of SaaS-monetization experience.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
In today's rapidly evolving cybersecurity landscape, organizations are increasingly turning to AI-powered solutions to enhance their security operations capabilities. As these solutions incorporate varying degrees of autonomy, from basic automation to fully autonomous decision-making, pricing models are evolving to reflect the different value propositions. Let's explore how autonomy levels—commonly categorized as L0 through L3—affect security operations agent pricing and what this means for your organization's budget and security strategy.
Understanding Autonomy Levels in Security Operations
Before diving into pricing implications, it's important to understand what these autonomy levels represent:
L0: Manual Operations with Tool Assistance
At this level, human analysts perform most tasks manually, using tools that provide information but require human interpretation and action. These tools might include dashboards, SIEM systems, and basic alerting mechanisms.
L1: Assisted Operations
L1 security operations incorporate basic automation for routine tasks. Systems can gather data, correlate events, and provide recommendations, but humans make all significant decisions and take action.
L2: Supervised Autonomy
At L2, security operations automation handles many routine investigation and response activities independently. Agentic AI systems can execute predefined playbooks and workflows with minimal human intervention, though humans still supervise and intervene for complex scenarios.
L3: Autonomous Operations
L3 represents highly autonomous systems capable of making complex decisions independently. These AI agents can detect, investigate, and respond to threats with limited human oversight, learning and improving from experience while operating within predefined guardrails.
How These Autonomy Levels Impact Pricing
L0: Time and Materials Pricing
At the lowest autonomy level, pricing typically follows traditional models:
- High human labor costs (SOC analysts, incident responders)
- Per-seat licensing for basic tools
- Consulting services billed hourly
According to Gartner, organizations operating at L0 typically spend 60-70% of their security operations budget on personnel costs.
L1: Subscription with Volume-Based Components
As we move to L1, pricing models begin to shift:
- Base platform subscription fees
- Volume-based pricing metrics (number of alerts processed, devices monitored)
- Lower personnel costs, but still significant
A recent ESG study found that organizations implementing L1 automation saw an average 15-20% reduction in analyst hours spent on routine tasks.
L2: Usage-Based and Outcome-Based Pricing
With supervised autonomy, more sophisticated pricing models emerge:
- Usage-based pricing tied to automation activity (automated investigations completed, incidents remediated)
- Tiered pricing based on automation complexity
- Credit-based pricing systems for flexible consumption
Organizations leveraging L2 security operations automation report 40-60% efficiency gains in incident response times, according to IBM's 2023 Cost of a Data Breach report.
L3: Outcome-Based and Value-Based Pricing
At the highest autonomy level, pricing aligns closely with business outcomes:
- Outcome-based pricing tied to security posture improvements
- Risk-reduction metrics driving cost
- Premium pricing for advanced orchestration capabilities
- Value pricing based on prevented incidents
Key Pricing Strategy Considerations
When evaluating security operations solutions across autonomy levels, consider these factors that influence pricing:
1. Implementation Complexity and Time-to-Value
More autonomous systems (L2-L3) generally require:
- More extensive integration with existing security infrastructure
- Customization of guardrails and decision parameters
- Higher upfront costs but faster long-term ROI
2. LLM Operations Costs
Advanced agentic AI security solutions leveraging large language models face:
- Computation costs for LLM Ops that may be passed to customers
- API usage fees for decision-making processes
- Data processing and storage requirements that scale with autonomy
3. Risk-Sharing Components
Higher autonomy levels often introduce risk-sharing in pricing models:
- Vendors of L3 systems increasingly offer guarantees or SLAs
- Some pricing includes breach protection insurance
- Performance-based components where vendors share risk of system failures
Real-World Pricing Examples
Case Study: Fortune 500 Financial Institution
A major financial services company transitioning from L1 to L3 autonomy reported:
- L1 system: $1.2M annual cost ($800K platform, $400K dedicated analysts)
- L3 system: $1.5M annual cost (platform only) with 75% reduction in human analyst requirements
- Net savings: $1.1M annually when accounting for reduced personnel needs
Industry Averages by Autonomy Level
According to recent Forrester research on security operations pricing:
| Autonomy Level | Typical Annual Cost (Enterprise) | Primary Pricing Model |
|----------------|----------------------------------|------------------------|
| L0 | $1M-2.5M | Per-analyst/Per-tool |
| L1 | $800K-1.5M | Subscription + Volume |
| L2 | $1M-1.8M | Usage/Credit-based |
| L3 | $1.2M-2.2M | Outcome-based |
Future Trends in Autonomy-Based Pricing
The security operations market continues to evolve, with several emerging trends:
- Hybrid pricing models that blend usage, outcome, and subscription components
- Greater emphasis on ROI measurement tools bundled with solutions
- More sophisticated credit-based pricing systems allowing flexibility across autonomy levels
- Risk-based pricing adjustments based on threat landscape changes
Making the Right Choice for Your Organization
When evaluating security operations solutions across different autonomy levels:
Assess your current security maturity - Organizations with less mature programs may benefit from L1-L2 solutions before advancing to L3.
Calculate total cost of ownership - Look beyond subscription fees to include integration, training, and ongoing management costs.
Consider your risk profile - Higher-risk industries may justify premium pricing for advanced L3 autonomy capabilities.
Evaluate vendor pricing transparency - The best partners clearly articulate how autonomy capabilities translate to pricing components.
Start with targeted use cases - Consider implementing higher autonomy levels in specific security domains before expanding.
Organizations that align their security operations autonomy levels with their security maturity, available resources, and risk profile will achieve the best balance of protection and cost-effectiveness.
As security operations automation continues to advance, pricing models will increasingly reward efficiency, effectiveness, and measurable security improvements rather than simply tool access or data volume—making the higher initial investment in advanced autonomy levels worthwhile for many organizations.