AI for MSP Growth Newsletter Series, Newsletter 8 of 12
Most MSPs do not lack security tools. They lack prioritization of security.
SIEMs, EDRs, MDR platforms, identity providers, firewalls, and vulnerability scanners all generate signals. What they do not generate is clarity around which risks deserve immediate attention versus which ones simply add noise.
As environments become more complex, security operations that rely on manual triage and static severity rules break down.
This is where AI-driven security operations and risk scoring begin to matter.
The operational problem MSPs quietly face
Traditional security operations assume all alerts can be reviewed, categorized, and handled in sequence.
That assumption is no longer realistic.
Modern MSP environments generate thousands of security events per client, per day. Most are benign. Some are important. A few represent material business risk.
The challenge is that traditional tools treat these events independently.
• An alert does not know the value of the asset it impacts
• A vulnerability score does not reflect exploit likelihood in that environment
• Identity anomalies are reviewed without a full behavioral context
The result is alert fatigue, delayed response, and inconsistent risk decisions.
What this actually is
AI-driven security operations and risk scoring use machine learning to continuously evaluate security signals across client environments and rank issues based on actual business risk rather than just technical severity.
Instead of reacting to alerts in the order they appear, AI evaluates:
• Which assets are most critical to the client
• Which identities carry elevated privileges
• Which vulnerabilities are most likely to be exploited
• Which behaviors meaningfully deviate from normal patterns
The output is not more alerts. It is a prioritized risk view that shows your team where to focus first.
Why this matters to MSP leadership
Security operations tend to break at scale.
As client counts increase and security tooling expands, MSPs reach a point where adding more tools or more analysts no longer improves outcomes.
AI-driven risk scoring changes that equation by allowing MSPs to:
• Focus limited security resources on high-impact threats
• Respond faster without increasing headcount
• Apply consistent security decisions across all clients
• Clearly explain security posture to executives, boards, and insurers
For MSP owners, this directly impacts margins, scalability, and client confidence.
What AI changes inside MSP security operations
AI introduces correlation, context, and prioritization across the entire security stack.
Instead of evaluating events in isolation, AI evaluates relationships.
- Asset-aware risk scoring AI factors in asset criticality, user role, data sensitivity, and exposure. A vulnerability on a domain controller is not treated the same as one on a low-impact workstation.
- Behavioral baselining and anomaly detection AI establishes normal patterns for users, devices, and applications. Deviations are evaluated based on risk, not just rule violations.
- Threat likelihood versus theoretical severity. Traditional CVSS scores explain how bad something could be. AI evaluates the likelihood of exploitation in that specific environment.
- Continuous risk posture assessment. Risk scores change as configurations, behaviors, and threat intelligence change. Risk management becomes continuous, not periodic.
The problem MSPs are trying to fix
Most MSPs are trying to address three security challenges simultaneously.
- Alert overload: Security teams spend time on low-impact events while meaningful risk competes for attention.
- Inconsistent prioritization. Different technicians make different judgment calls about urgency, creating operational and liability risk.
- Poor executive communication. Clients hear about incidents, not overall risk posture, which erodes trust and increases churn.
AI-driven risk scoring addresses all three by introducing consistency, clarity, and focus into security operations.
How does this change the MSP’s role with clients
With AI-based risk scoring, the MSP stops acting like a reactive security responder and becomes a risk advisor.
Client conversations shift from:
• “Here are the alerts we handled” to
• “Here is your current risk exposure, what changed, and what we are doing about it”
That shift increases perceived value, strengthens retention, and supports higher-margin security services.
Real-world scenarios we are seeing
An MSP managing regulated clients used AI-driven correlation to identify that repeated low-severity alerts traced back to a single identity misconfiguration. Fixing one root issue reduced alert volume across multiple tools.
An MSP running a lean SOC used AI-based risk scoring to prioritize incidents tied to privileged identities. Mean time to containment improved without increasing headcount.
An MSP preparing clients for cyber insurance renewals used risk scoring trends to demonstrate proactive security management. Renewal friction dropped and client confidence improved.
The takeaway
Security operations are no longer about seeing everything. They are about understanding what matters most.
AI-driven risk scoring enables MSPs to scale security operations intelligently, reduce noise, and align technical responses with business impact.
For MSP leaders, this is not a tooling decision. It is a maturity decision.
AI for MSP Growth Thesis Newsletter Canonical 12-Part Series
This 12-part series was created after countless conversations with MSP executives who all express the same frustration. They are told they need to implement AI, yet when they ask where, what, or why, they are met with sales pitches. Marketing firms, sales organizations, legal providers, HR consultants, and service delivery companies all claim AI is essential to their specific area.
What is missing is an executive-level, holistic view. MSP leaders need a framework that explains how AI impacts the organization as a whole, when adoption truly makes sense, and where AI delivers measurable value. This newsletter series provides that structure. It focuses on the how, when, and where of AI adoption, while leaving the decision of whom to partner with entirely up to the MSP.
This series was created to give MSP executives a clear, holistic framework for understanding where, when, and why to adopt AI, without being sold a solution.
If you are an MSP or a Vendor looking for assistance with any of the initiatives discussed in this series, you can review our growing MSP Business Growth Marketplace to explore vetted, vendor-agnostic partners aligned to your stage of growth: https://bizadvisoryboard.com/msp-business-growth-marketplace/
- AI Is Transforming MSP Service Desks Faster Than Anyone Expected https://www.linkedin.com/pulse/ai-transforming-msp-service-desks-faster-than-anyone-expected-daigle-szxhe
- How AI Strengthens MSP Security Operations and Threat Detection https://www.linkedin.com/pulse/how-ai-strengthens-msp-security-operations-threat-detection-daigle-xcqce
- How AI Improves Proactive Monitoring and Observability for MSPs https://www.linkedin.com/pulse/how-ai-improves-proactive-monitoring-observability-msps-paul-daigle-fhuue
- How AI Accelerates Preventive Maintenance and Patch Intelligence https://www.linkedin.com/pulse/how-ai-accelerates-preventive-maintenance-patch-paul-daigle-yonwe
- How AI Enhances Technology Lifecycle Management for MSPs https://www.linkedin.com/pulse/how-ai-enhances-technology-lifecycle-management-msps-paul-daigle-vnwoe
- How AI Improves MSP Vendor Management and Tool Stack Decisions https://www.linkedin.com/pulse/how-ai-improves-msp-vendor-management-tool-stack-decisions-daigle-kcobe
- AI for MSP Client Retention and Churn Prediction https://www.linkedin.com/pulse/ai-msp-client-retention-churn-prediction-growth-series-paul-daigle-wdpne
- AI in MSP Security Operations and Risk Scoring. You are reading it now.
- AI for MSP M&A Readiness and Due Diligence. Status: Published or Pending. See newsletter feed: https://www.linkedin.com/in/pauldaigle100/recent-activity/newsletter/
- AI for MSP Marketing Performance and Lead Quality. Status: Published or Pending. See newsletter feed: https://www.linkedin.com/in/pauldaigle100/recent-activity/newsletter/
- AI in MSP Executive Decision Making and KPI Intelligence. Status: Published or Pending. See newsletter feed: https://www.linkedin.com/in/pauldaigle100/recent-activity/newsletter/
- The AI-Enabled MSP: What Top Performers Are Doing Differently. Status: Published or Pending. See newsletter feed: https://www.linkedin.com/in/pauldaigle100/recent-activity/newsletter/
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About Paul Daigle
Paul Daigle is a seasoned executive and advisor with over 30 years of experience helping businesses scale, improve profitability, and prepare for growth, capital, or exit. His work focuses heavily on Managed Service Providers and the broader IT channel.
Paul has managed and advised organizations responsible for more than $1 billion in assets, raised capital for over 130 companies, and guided businesses through mergers, acquisitions, turnarounds, and public market transactions. He has served on more than a dozen public and private boards, including multiple roles as Chairman.
As the creator of the MSP Business Evaluator and Accelerator, Paul provides MSP owners with clear benchmarks, peer-group comparisons, EBITDA insights, and practical roadmaps to improve valuation and operational maturity. His work is used by MSPs, private equity firms, capital providers, and strategic buyers to evaluate performance and reduce risk.
Paul is the Senior Managing Partner of BizAdvisoryBoard and regularly advises executives on strategy, scale, governance, and long-term value creation.
If you would like to discuss MSP growth, security maturity, valuation, or how AI fits into your business strategy, you can book a 30-minute strategy session here: