The Future of MSPs: A Practical AI and Cloud Roadmap

No one can predict the MSP market through 2036 with precision. What providers can do is build adaptable operating capabilities: secure remote management, clear customer responsibilities, cloud governance, human-supervised automation, measurable outcomes, and a workforce that can validate increasingly automated systems.

Build around durable customer outcomes

Customers buy availability, security, support, recovery, cost control, and accountable advice—not tool count. Define service levels and evidence for those outcomes. Track detection, response, restoration, change success, configuration drift, user experience, and unresolved risk instead of presenting automation volume as value.

Adopt AI through governed workflows

Use the NIST AI Risk Management Framework to organize governance, mapping, measurement, and management. Start with bounded tasks such as summarization, classification, evidence assembly, and draft remediation. Keep approvals for production changes, customer communication, security response, and other consequential actions.

Modernize cloud and platform operations

• Standard tenant and identity baselines with documented exceptions.
• Infrastructure and policy as code with review and rollback.
• Central telemetry with customer separation and retention.
• FinOps and license governance tied to business owners.
• Portable documentation, credentials, and exit procedures.
• Recovery testing across SaaS, endpoints, servers, and cloud dependencies.

Plan three scenarios

Test a base case of steady automation, an accelerated case with agentic operations, and a constrained case shaped by regulation, incidents, customer skepticism, or vendor concentration. For each, identify workforce skills, controls, investments, customer communication, and indicators that would cause the roadmap to change.

Next step for your environment

Build a three-year roadmap with quarterly indicators and scenario triggers rather than promising a fixed 2036 endpoint. If you need a documented baseline before changing production systems, start with an ITECS technology and security assessment.

Record the accountable owner, current baseline, source date, decision, exceptions, acceptance evidence, and review trigger. Test consequential changes in a bounded environment, maintain a rollback path, and verify the real result before closing the work. Product names, model availability, pricing, legal requirements, and security guidance can change; recheck the primary sources whenever the decision is renewed or the environment changes.

Sources and update trigger

• CISA — Protecting MSPs and their customers
• NIST — AI Risk Management Framework

Review trigger: Review quarterly and after major vendor, regulation, threat, customer, workforce, or automation changes.