Monetising the AI Challenge: The 3 Service Lines for MSPs

Key Takeaways

• The ANZ market is moving, not shrinking. Technology spending continues to rise, but investment is flowing towards software, infrastructure, governance, and AI-enabled services rather than traditional support models.
• Customers have already bought AI. Many organisations are already using AI tools, yet few have implemented meaningful governance or oversight.
• Data readiness is the new starting point. Classification, governance, identity protection, backup, and recovery are becoming essential prerequisites for AI adoption.
• AI governance is a recurring revenue opportunity. Managed service providers (MSPs) can create long-term services around compliance, agent governance, visibility, and risk management.
• The biggest opportunity is inside your existing customer base. Increasing service value per tenant often delivers better returns than adding new logos.
• The future belongs to outcome-based services. Customers increasingly pay for reduced risk, compliance readiness, resilience, and business outcomes rather than technical activity.

How Can MSPs Win the Next Wave of Growth?

Across Australia and New Zealand (ANZ), organizations are facing slower growth, higher costs, and persistent productivity challenges. The core message from the ANZ OnPoint MSP Roadshow: Monetising the AI Mess is that the MSP market is moving, not disappearing. Customer budgets are moving toward software, cloud infrastructure, data protection, and AI, while traditional labour-led IT services face margin pressure. 

Most customers already have AI and are experimenting with Microsoft Copilot, ChatGPT, AI assistants, and AI agents, but still struggle with visibility, governance, compliance, or operational control over those technologies. According to AvePoint’s State of AI 2026 Report:

• Nearly 47% of employees use AI agents daily or weekly.
• Around 88% of organisations experienced at least one agent-related security incident.
• About 21% of organisations cannot account for unsanctioned AI agent activity and spend.

For MSPs and channel partners, this transformation has created the next major recurring revenue opportunity. Omdia forecasts that the global partner opportunity tied to AI services will reach $276 billion by 2030 — underscoring the scale of what’s ahead. This blog explores how MSPs can capture that opportunity through governance, risk, and readiness.

Why Is the Traditional MSP Revenue Model Under Pressure?

For years, MSP growth was driven by familiar metrics:

• Per-device and per-user billing
• Help desk services
• Infrastructure management
• Licence resale
• Ticket-based operational support

The challenge is that customers are no longer allocating technology budgets in the same way. IT spending continues to grow, but the fastest-growing categories are software and data centre investments rather than traditional IT services.

Meanwhile, MSP operating costs continue to rise. Simply adding more endpoints or more tenants is becoming a linear growth model. The AI era rewards something different: outcome-based services that reduce risk, improve governance, and enable productivity.

Are MSPs Losing the AI Opportunity to Hyperscalers?

While significant AI investment is flowing directly towards hyperscalers and software providers, MSPs are not being excluded because customers don’t value them. They face a challenge because many organisations still lack trusted partners to help them deploy, govern, secure, and operationalise AI.

Organisations do not want solutions that don’t scale under pressure like traditional MSP software vendors have provided. Customers want robust enterprise technologies that have multitenant delivery on day one, are automated by default, and are billable from the very first client.

In short, AI adoption is creating a new business requirement: Trust at scale.

Why Is Trust the Real AI Product for MSPs?

Organisations increasingly recognize governance and readiness as the primary barriers to successful AI deployment. Ranking higher than data security, skills, or budget, 51% of MSPs say data governance and compliance challenges are the main obstacle to AI adoption.

This shift places MSPs in a more strategic role, helping customers navigate critical questions such as:

• What data can AI access?
• Where is sensitive information overshared?
• Which AI tools are being used without approval?
• How are AI agents making decisions?
• What evidence exists for compliance or audits?
• Who is accountable when AI acts incorrectly?

These aren’t helpdesk inquiries; they define the governance and risk frameworks that will underpin every AI deployment. By addressing them, MSPs can identify where value is shifting, expand margin opportunities, and cement their role as trusted advisors in the AI era.

What Are the 3 AI Service Lines for MSPs?

Here’s a framework for monetising the AI transition: data, infrastructure, and agent services.

1. Data Services: Revenue Available Today

Most MSPs can start here immediately. Data services include:

• Data classification
• Information governance
• Oversharing remediation
• Backup and recovery
• Identity protection
• Licence optimisation
• Storage governance

These services do not require customers to purchase new AI technologies. Instead, they prepare existing Microsoft 365 environments for safe AI adoption. This is why data readiness has become AI readiness.

2. Infrastructure Services: The Next Expansion Motion

AI requires resilient infrastructure. Partners can expand into:

• Security baselines
• Compliance assessments
• Cloud posture management
• Cyber resilience
• Disaster recovery
• Cloud cost management
• Operational governance

These are services customers increasingly need as AI workloads grow more complex and security requirements become stricter. The opportunity lies in helping customers maintain control over the environments where AI operates. Beyond providing the space for AI to run, MSPs create greater value by enabling customers to govern and protect the environments where AI operates.

3. Agent Services: The Emerging Category

The fastest-growing opportunity may be one that customers haven’t fully recognised yet.

AI agents are rapidly entering business workflows. This creates an entirely new service category:

• Discovery: Finding every agent running across a tenant.
• Observability: Understanding what agents access and how they act.
• Governance: Establishing policies, approvals, and controls.
• Cost optimisation: Managing token consumption and AI spend.

Shadow AI is the new shadow IT, except it has permissions, spends money, and makes decisions.

Why Are Existing Customers the Biggest AI Opportunity for MSPs?

Many MSPs assume growth requires new logos. However, the AI transition suggests otherwise.

The most profitable path may be to expand services for existing customers, where MSPs already have:

• Administrative access.
• Trusted relationships.
• Operational knowledge.
• Existing service agreements.
• Familiarity with customer data environments.

Being embedded within these accounts lowers the cost of growth and creates a natural foundation for scaling governed, compliant, and AI-ready services across every tenant. Adding governed, compliant, AI-ready services to tenants you already run is a compounding business model.

How Can MSPs Start Offering AI Services?

The opportunity feels large, but execution can begin with a simple sequence.

• Step 1: Start with data discovery. Run data classification and oversharing assessments. The findings often create immediate follow-on projects.
• Step 2: Package compliance and governance. Offer fixed-fee assessments and recurring governance reviews. Customers increasingly need evidence, not just technology.
• Step 3: Build an AI inventory practice. Help customers identify AI tools, copilots, and agents already operating inside their environment. The first partner to own the inventory conversation often becomes the strategic AI advisor.

This sequence requires no new customer acquisition, no major organisational restructuring, and no immediate expansion of headcount.

How Does Multitenant Management Help MSPs Scale AI Services?

As AI adoption grows, MSPs must manage AI across dozens or even hundreds of tenants, each with its own agents, policies, permissions, and compliance requirements. Scaling AI services profitably requires more than deployment. It requires operational control at scale. The following capabilities define what that control looks like in practice:

• Multitenant visibility. Monitor AI tools, copilots, and agents across all customers.
• Centralised governance. Apply policies and controls consistently across every tenant.
• Standardised operations. Reduce drift through common baselines and repeatable processes.
• Automated management. Streamline remediation, reporting, and compliance.

“MSPs positioned to win will be those that can govern and scale AI consistently across every customer. In the AI era, multitenant management becomes a competitive advantage, transforming operational complexity into scalable, profitable growth.”

The Future Belongs to the MSPs That Control the AI Layer

MSPs already own the three assets AI depends on:

• The data AI uses
• The infrastructure where AI runs
• The operational relationship with the customer

Add governance, visibility, compliance, and resilience to that equation, and the AI complexity becomes something much more valuable: a recurring revenue engine.

Frequently Asked Questions

How can MSPs make money from AI without selling new AI tools? 

They can offer data classification, oversharing remediation, and governance services. These prepare existing Microsoft 365 environments for safe AI adoption.

What are AI agent services for MSPs? 

AI agent services help customers find, monitor, govern, and control the cost of AI agents running across their tenants.

Why is data readiness important for AI readiness? 

AI can only be used safely when sensitive data is classified, permissions are correct, and oversharing is fixed before AI tools access it.

Related Questions

→  How can MSPs build an AI governance practice?
→  How can MSPs monetise AI readiness assessments?
→ How to discover and monitor AI agents across every Microsoft 365 Tenant?
→  How does multitenant management help MSPs scale operations?
→  Why doesn't AI governance scale like other MSP services?