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AI is unlikely to make managed service providers (MSPs) obsolete, but it will change which work they do and how they grow. Automation can take on parts of routine service operations; clients still need expertise to govern AI, manage risk, integrate it with existing systems and support adoption. That creates an opportunity for MSPs able to turn technical capability into reliable, clearly scoped client outcomes—not a guarantee that every provider or role will be protected.
Will AI replace MSPs?
Not as a whole, according to Gartner’s July 2026 analysis of agentic AI: organizations still need expertise to govern AI, manage risk, integrate systems and scale adoption. That is an analyst assessment of the provider role, not proof that AI will never displace a particular task, job or MSP. The more useful expectation is a shift in the work mix: more automation for repeatable operations, alongside continuing demand for judgment, oversight and integration.
Many clients also operate across hybrid environments of legacy on-premises systems and cloud platforms, which can make integration and management complex. KPMG International’s Global Head of Managed Services, Ron Walker, described this as a continuing challenge even as companies seek to accelerate AI.
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How can MSPs use AI to grow?
One route is internal efficiency: use AI and automation for suitable parts of ticketing, patching and monitoring so staff can spend less time on repetitive work. Kaseya’s 2026 vendor-published survey found that 53% of respondents used AI for those activities, but more than half had automated only about a quarter of their workload. Adoption was underway, but broad automation was not the norm among those respondents.
If automation lets a team handle more work with existing capacity, it may support growth without hiring at the same pace. That is a potential capacity benefit, not evidence of guaranteed headcount reductions, higher margins or revenue. Human review still matters where a decision depends on client context, creates material risk or requires approval and escalation.
Growth also means choosing whether to improve internal operations first or sell a client-facing service. The two are related, but they require different delivery plans: internal automation changes how the MSP works; a paid client offer needs a defined scope, support model and accountable owner.
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Survey results indicate interest in AI and automation, but interest has not automatically become revenue. In Kaseya’s 2026 survey, 48% of respondents ranked AI and automation as the top client need for 2026, while 13% said they earned meaningful revenue from those services. The gap suggests a need for a clear, supportable offer; that is an interpretation of the results, not a separate survey finding.
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KPMG’s 2026 survey offers a buyer-side signal. Among 1,224 business leaders at large global organizations, 56% named AI management as their top managed-services investment priority over the next two years; 33% cited cybersecurity. These are large-enterprise buyer responses, not a poll of small businesses or MSP owners. KPMG also conducted 10 interviews as part of its research.
Potential offers can range from AI adoption and integration to ongoing governance, security and support. An MSP should distinguish a one-time implementation from recurring management: clients may need help long after an AI tool is connected, particularly when it must work across legacy systems and cloud services.
How can an MSP grow without hiring at the same pace?
Start with a service that is repeatable and operationally safe, then determine what can be automated and where people remain accountable. The point is not to remove human involvement everywhere; it is to reserve specialist time for exceptions, risk decisions and work that needs client knowledge.
- Choose a bounded workflow. Identify repetitive work such as ticket triage, monitoring or patching where the process and escalation conditions are clear.
- Define oversight. Specify which actions can run automatically, which need approval, who reviews exceptions and how a client can escalate an issue.
- Measure delivery readiness. Track whether automation improves service capacity and consistency without creating a support burden that outweighs the benefit.
- Package client-facing work separately. If offering AI implementation or management, state what is included, what ongoing support covers and where responsibility sits.
This approach addresses the difference between deploying a tool and delivering a dependable service. MSP Global’s July 2025 survey of more than 300 MSP professionals identified automation as a primary growth focus, while also highlighting trust, pricing competition, lead generation and customer experience as practical frictions. Those responses reflect survey participants, not every provider’s experience.
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Which growth areas have evidence of demand?
Security and continuity remain concrete areas where providers report growth. In Kaseya’s 2026 survey, 71% of respondents reported year-over-year revenue growth in cybersecurity and 50% in business continuity and disaster recovery. Separately, KPMG’s large-organization survey found cybersecurity was a managed-services investment priority for 33% of respondents. The two surveys have different populations and should not be treated as directly comparable.
UK government research describes security provision and compliance support among MSP activities, and identifies technology shifts such as AI, edge and cloud as both opportunities for integration and strategic support and challenges involving cost, scale and optimization. Its estimates are specific to the UK and indicative: the sector lacks a formal Standard Industrial Classification code, and the study used an experimental method to identify providers. It estimated 11,492 UK MSPs and a 12% compound annual growth rate through 2027; these are dated market-study estimates, not current global figures.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Why is MSP growth getting harder?
Kaseya’s 2026 survey release reported that 71% of respondents named acquiring new customers as their top challenge. The share reporting typical annual customer spending above $25,000 was 41%, down from 75% in the prior year. The same release said the share reporting difficulty hiring skilled technicians rose from 9% to 16% year over year. These are vendor-published survey findings, not universal market statistics.
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That backdrop makes it risky to assume AI interest will solve growth on its own. Kaseya’s channel executive Dan Tomaszewski said, “The MSP market is maturing, and rising competition is forcing providers to rethink how they grow,” in the company’s April 14, 2026 release. His comment is a vendor executive’s perspective; the survey figures provide the separate reported evidence of acquisition and spending pressures.
What should an MSP decide before expanding its AI offer?
- Internal efficiency or a client service: Decide whether the first objective is improving the service desk and operations or creating a paid offer for customers.
- Implementation or ongoing management: A rollout may be a project; governance, integration, security and support can require an ongoing service model.
- Automation or human oversight: Keep people responsible for risk review, client-specific decisions, approvals and escalation.
- Broad portfolio or focused expertise: Expand only where the MSP can deliver credibly; a narrower offer with suitable partners may be more supportable than claiming expertise across every AI need.
These are decision aids, not a universally ranked formula. OpenText reported in a 2025 vendor-sponsored global survey that 92% of surveyed MSPs saw business growth from AI interest and 96% expected that trend to continue that year. Because the result is self-reported and vendor-sponsored, it signals optimism among respondents rather than proving that AI interest converts into durable revenue for all MSPs.
Sources: Gartner, July 2026; Kaseya, April 2026; KPMG International, April 2026; MSP Global, July 2025 survey; OpenText, September 2025; UK Department for Science, Innovation and Technology, published approximately 2024.
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