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1Repair Windows errors before they cause bigger problems2Scan for outdated or missing drivers - takes under a minute3Clear out junk files and repair common Windows errorsManaged cloud services are shifting from migration and infrastructure upkeep toward a broader operating challenge: coordinating AI workloads, hybrid estates, spending, security, compliance, and measurable business value. For business and IT leaders, the decision is no longer simply whether to use an outside provider. It is which responsibilities to keep, which to delegate, and how to make cloud choices answerable to business outcomes.
What is changing in managed cloud services?
Cloud operations now span more than the infrastructure team. AI adoption raises new questions about compute demand, data quality, security, and cost forecasts. Hybrid and multicloud estates require coordination across identities, governance, data movement, and operating practices. At the same time, finance and business teams are expected to connect cloud spending to results rather than treat a lower bill as the only sign of success.
These pressures are changing what organizations ask managed service providers (MSPs) to do. Security and compliance support, migration, and FinOps remain prominent needs among SMBs that use MSPs, while providers are also considering AI consulting. A service partner can add capacity and expertise, but it does not take away the organization’s responsibility for architecture, risk acceptance, access decisions, or business outcomes.
How are AI workloads changing cloud operations?
AI affects cloud planning in two ways: it can change the scale and shape of compute demand, and it introduces dependencies on data quality, security, and compliance. Gartner’s May 2025 forecast says AI workloads will use 50% of cloud compute resources by 2029, up from less than 10% at the time of its announcement. This is a projection, not a measurement of current cloud usage.
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Flexera’s 2026 State of the Cloud report says generative AI was the third most widely used public cloud service among respondents, at 58%, compared with 50% in its 2025 report. It also reports that 45% use GenAI extensively, up from 36% in 2025. In Flexera’s 2026 survey, 53% of cloud leaders identified security and compliance as a top challenge for cloud-based AI initiatives, while 40% cited training-data quality. These are respondents’ reported concerns, not counts of security incidents or a universal assessment of data quality.
What AI changes in the operating model
- Workload visibility: Track which teams and applications use AI services and what resources they consume, so new demand is visible in operational and financial planning.
- Data ownership: Establish who is responsible for training and input data quality, access, and permitted use before workloads scale.
- Security and compliance: Assign accountable owners for controls and risk decisions. An MSP may operate controls or advise on them, but the organization still needs to define its requirements and accept residual risk.
- Cost planning: Forecast AI-related usage as a distinct workload where possible, then compare its cost with the service or business outcome it supports.
Gartner’s forecast is a reason to plan for growing AI demand, not evidence that every organization should build its own AI platform or that AI automatically reduces operating costs.
Why do hybrid and multicloud environments need more coordination?
Flexera’s 2026 survey of 753 cloud decision-makers and users worldwide reports that 73% of surveyed organizations operate hybrid cloud environments. Mixed estates can reflect deliberate architecture, acquisitions, SaaS sprawl, or decisions made by decentralized teams; having multiple environments does not by itself show that an organization has a coherent multicloud strategy.
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Each additional environment can add work around identity, policy, integration, data movement, and cost governance. Gartner’s May 2025 outlook identifies interoperability as a challenge and recommends choosing specific use cases for cross-cloud deployment. It forecasts that more than 50% of organizations will fail to achieve their expected results from multicloud implementations by 2029. That is a future projection, not a current failure rate.
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When multiple environments are justified
- A specific workload has a clear technical or business fit that is not met as well by the existing environment.
- A resilience or regulatory requirement calls for a defined separation or deployment pattern.
- The organization can support the integration, identity, data-transfer, and governance work that comes with the design.
Do not treat multicloud as an automatic resilience strategy. Resilience depends on the architecture, dependencies, and ability to operate and recover the services—not simply on using more than one provider.
How should organizations manage cloud spend?
Cloud financial management is becoming a shared practice across finance, engineering, procurement, and product or business teams. Flexera’s 2026 findings say 85% of organizations identify managing cloud spend as a challenge, 63% have established FinOps teams, and 64% report that cloud delivers value to business units. The figures show that cost pressure and business-value expectations coexist; reducing spend without regard to service outcomes is not the same as managing value.
Rank #3
Flexera reports that 49% of respondents use unit economics to understand the cost per service and connect spending to outcomes, compared with 40% in its 2025 report. It also estimates that 29% of IaaS and PaaS spend was wasted in 2026, after five years of decline, attributing the increase to cost complexity from AI and newer cloud services. The waste figure is an estimate reported in Flexera’s survey, not an audited measure for every organization.
Metrics that connect cost to outcomes
- Forecast accuracy: How closely actual consumption and cost track the forecast, and whether teams can explain significant variances.
- Unit cost: Cost per relevant service, transaction, customer, or other business unit, interpreted alongside service quality and demand.
- Utilization and avoidable waste: Whether resources are being used as intended and which costs can be removed without harming the service.
- Business value: Whether cloud-supported services deliver the outcomes their teams and business owners expect.
Flexera’s 2025 release separately reported that 84% of respondents considered managing cloud spend a top challenge, that cloud budgets exceeded limits by 17%, that 60% used MSPs, and that 59% had FinOps teams. These are figures from a different annual release; without checking underlying methodology and question wording, they should not be treated as a directly comparable time series with the 2026 results.
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For SMB respondents who continue to use MSPs, Flexera’s 2026 report identifies security and compliance support (65%), cloud migration (64%), and FinOps (58%) as leading needs. The report says 49% of respondents expect providers to expand into AI consulting and strategy, while 44% of MSPs currently offer AI consulting. It also reports that two-thirds of MSPs are adopting AI for cybersecurity use cases. These are survey findings about service demand and provider activity, not evidence of any individual provider’s quality or results.
Use the figures to understand the kinds of support buyers are seeking, not to assume that every MSP offers the same capabilities. Flexera’s 2025 release reported MSP use by 60% of respondents. Its 2026 page says enterprise use rose 3 percentage points year over year, while SMB reliance declined from 48% to 39%; Flexera says the SMB decline was likely related to budget constraints. The enterprise and SMB observations refer to different populations and should not be collapsed into one adoption rate.
Define responsibilities before outsourcing
- Keep an internal owner for architecture, business priorities, access policy, and risk acceptance.
- Specify which operational tasks the MSP performs, which decisions it can make, and which require customer approval.
- Agree how security events are escalated, who leads incident response, and how responsibilities are divided.
- Set expectations for reporting, service levels, cost transparency, and evidence of compliance.
- Document portability, data access, transition support, and exit provisions before the service begins.
These are evaluation criteria, not a ranking of providers supplied by the survey. The right service boundary depends on internal skills, regulatory obligations, workload criticality, and the organization’s appetite for operational control.
How should buyers compare cloud providers and service partners?
Provider usage is not a recommendation or a market-share measure. Flexera’s 2026 survey reports that 83% of all respondents were running some or significant workloads on AWS and 79% on Azure. The report describes usage as close and says there is no clear indication that one will dominate in the near future. Google Cloud Platform ranked third in the report, but the reviewed report page did not state its all-organization percentage.
Best Value
Rather than choosing by popularity, compare viable providers and partners against the requirements of the workloads and the capabilities your organization can operate:
| Decision area | Questions to resolve |
|---|---|
| Workload fit | Does the environment support the application’s technical requirements and expected operating pattern? |
| Interoperability and dependencies | What integration, migration, identity, and data-movement work will the choice create? |
| Security, compliance, and jurisdiction | Which controls and legal or sovereignty requirements apply, and who is accountable for meeting them? |
| Cost visibility | Can the organization forecast and attribute costs, and measure unit economics where they matter? |
| Operating capability | Which skills exist internally, what support is needed, and where exactly does an MSP’s responsibility begin and end? |
| Portability and exit | How can data and workloads be moved or transitioned, and what support and obligations apply at exit? |
Gartner’s May 2025 forecast that 25% of organizations will have significant dissatisfaction with cloud adoption by 2028 is a warning about outcomes to come, not an observed dissatisfaction rate. Use it as a prompt to test assumptions, ownership, and operating costs during sourcing rather than as proof that a particular provider or model will fail.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.When do sovereignty, industry clouds, and sustainability matter?
These considerations are especially relevant when jurisdiction, sector-specific requirements, or environmental reporting shape the workload decision. Gartner’s May 2025 release forecasts that more than 50% of multinational organizations will have digital sovereignty strategies by 2029, compared with less than 10% at the time of publication. It also forecasts that more than 50% of organizations will use industry cloud platforms to accelerate business initiatives by 2029. Both are forecasts; neither establishes that a particular platform meets a given organization’s obligations.
Assess sovereignty in terms of the applicable jurisdiction and the controls required over data and operations. A “sovereign” label alone does not establish compliance. Industry-specific platforms likewise need to be checked against the organization’s actual workload and governance needs.
On sustainability, Flexera’s 2026 report page says defined initiatives that include cloud carbon-footprint tracking were reported by 47% of European respondents and 34% of North American respondents. These are regional survey findings about reported initiatives, not comparable emissions-per-workload results and not proof that moving a workload to cloud reduces its emissions.
Quick Recap
What should cloud leaders do next?
- Map the estate and its owners. Identify cloud and SaaS environments, business owners, critical workloads, dependencies, and the teams accountable for each.
- Make the operating model explicit. Decide which work stays in-house, where an MSP fills a capability gap, and who retains decision rights for architecture, security, and business outcomes.
- Set cost and value measures together. Use forecast accuracy, relevant unit costs, utilization, and service or business outcomes rather than treating a lower total bill as the sole measure of progress.
- Plan AI workloads as governed services. Establish visibility, data-quality ownership, security and compliance responsibilities, and cost forecasting before usage expands.
- Require a reason for each environment. Tie provider and cross-cloud choices to workload fit, resilience, or regulatory needs, and include the integration and exit costs in the decision.
- Review the assumptions regularly. Revisit service boundaries, cost forecasts, risk requirements, and business outcomes as workloads and organizational needs change.
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