April 30, 2026
How Managed Cloud and AI Services Turn Complexity Into Business Advantage
Managed services help organizations address challenges by enabling operational continuity, strong governance and cost optimization.
Enterprise IT has undergone a dramatic shift as organizations have moved from legacy on-premises infrastructure to cloud-centric and artificial intelligence-enabled architectures. The complexity of managing these environments has grown significantly, outpacing the capacity of most internal IT teams. Many organizations face three common challenges: skill gaps, the inherent complexity of hybrid and multicloud environments, and difficulty aligning technology investments with business objectives. Often, these challenges make managed cloud and AI services a strategic necessity.
Managed service providers address these challenges by embedding expertise, proactive monitoring, intelligent automation and governance directly into IT operations. The result is a shift from reactive, overburdened IT teams struggling to keep pace to a proactive, resilient model that optimizes costs and enables innovation.
CDW provides flexible partnerships for end-to-end managed cloud and AI services across Amazon Web Services, Microsoft Azure and Google Cloud Platform, providing the expertise and operational continuity organizations need to successfully leverage AI.
Amazing things happen when cloud and artificial intelligence work together — and your teams are free to focus on what’s next.
Enterprise IT has undergone a dramatic shift as organizations have moved from legacy on-premises infrastructure to cloud-centric and artificial intelligence-enabled architectures. The complexity of managing these environments has grown significantly, outpacing the capacity of most internal IT teams. Many organizations face three common challenges: skill gaps, the inherent complexity of hybrid and multicloud environments, and difficulty aligning technology investments with business objectives. Often, these challenges make managed cloud and AI services a strategic necessity.
Managed service providers address these challenges by embedding expertise, proactive monitoring, intelligent automation and governance directly into IT operations. The result is a shift from reactive, overburdened IT teams struggling to keep pace to a proactive, resilient model that optimizes costs and enables innovation.
CDW provides flexible partnerships for end-to-end managed cloud and AI services across Amazon Web Services, Microsoft Azure and Google Cloud Platform, providing the expertise and operational continuity organizations need to successfully leverage AI.
Amazing things happen when cloud and artificial intelligence work together — and your teams are free to focus on what’s next.
Enterprise IT has undergone a dramatic shift as organizations have moved from on-premises systems to cloud-centric architectures. Organizations are adopting fully managed, artificial intelligence-enabled operational models. While the integration of AI and cloud unlocks powerful capabilities, it also introduces significant complexity.
Many organizations moved to the cloud to manage costs and then discovered that specialized expertise is essential to optimize spending, usage and security. Over time, organizations have calibrated their approach, keeping certain workloads on-premises while migrating others to the cloud. Increasingly, the latter group includes AI workloads that benefit from cloud-enabled access to advanced compute and scalability. However, relying on in-house teams to handle provisioning, maintenance and security patching often leads to resource strain, unpredictable costs and operational delays.
Organizations today face three challenges in managing cloud and AI deployments: skill gaps, the complexity of modern environments and difficulty aligning technology with business objectives. For many, a managed service provider offers the fastest and most cost-effective path forward. MSPs help organizations reduce complexity by handling day-to-day infrastructure and application management. When organizations offload repetitive and resource-intensive tasks, they can focus instead on innovation and strategic IT goals. The integration of AI into managed services represents its next evolution, embedding intelligent automation, predictive analytics and optimization directly into operational workflows.
For many organizations, the MSP model has become indispensable, providing certified expertise, proactive monitoring and continuous optimization across cloud environments. Together, managed cloud and AI services help organizations improve reliability and performance while reducing downtime and risk, effectively transforming IT operations from a cost center to an enabler of business agility.
Whether an organization is running applications in a single cloud or a hybrid stack, managed cloud and AI services provide the foundation for resilient, scalable operations that drive digital transformation.
48%
The percentage of IT leaders and decision-makers who believe AI can help them achieve faster innovation
Source: CDW, “CDW Artificial Intelligence Research Report,” April 2025
CDW’s managed cloud and artificial intelligence services can help organizations optimize their IT operations and focus on innovation.
Enterprise IT has undergone a dramatic shift as organizations have moved from on-premises systems to cloud-centric architectures. Organizations are adopting fully managed, artificial intelligence-enabled operational models. While the integration of AI and cloud unlocks powerful capabilities, it also introduces significant complexity.
Many organizations moved to the cloud to manage costs and then discovered that specialized expertise is essential to optimize spending, usage and security. Over time, organizations have calibrated their approach, keeping certain workloads on-premises while migrating others to the cloud. Increasingly, the latter group includes AI workloads that benefit from cloud-enabled access to advanced compute and scalability. However, relying on in-house teams to handle provisioning, maintenance and security patching often leads to resource strain, unpredictable costs and operational delays.
Organizations today face three challenges in managing cloud and AI deployments: skill gaps, the complexity of modern environments and difficulty aligning technology with business objectives. For many, a managed service provider offers the fastest and most cost-effective path forward. MSPs help organizations reduce complexity by handling day-to-day infrastructure and application management. When organizations offload repetitive and resource-intensive tasks, they can focus instead on innovation and strategic IT goals. The integration of AI into managed services represents its next evolution, embedding intelligent automation, predictive analytics and optimization directly into operational workflows.
For many organizations, the MSP model has become indispensable, providing certified expertise, proactive monitoring and continuous optimization across cloud environments. Together, managed cloud and AI services help organizations improve reliability and performance while reducing downtime and risk, effectively transforming IT operations from a cost center to an enabler of business agility.
Whether an organization is running applications in a single cloud or a hybrid stack, managed cloud and AI services provide the foundation for resilient, scalable operations that drive digital transformation.
CDW’s managed cloud and artificial intelligence services can help organizations optimize their IT operations and focus on innovation.
Challenges in AI Adoption
62%
The percentage of IT leaders and decision-makers who said their organization has good ideas for AI but runs into trouble executing those ideas
26%
The percentage of IT leaders and decision-makers who cited challenges around talent and training as among the biggest pain points their organization has faced when planning, implementing and completing AI projects
34%
The percentage of IT leaders and decision-makers who have achieved full deployment of their highest-priority AI projects
Challenges in AI Adoption
62%
The percentage of IT leaders and decision-makers who said their organization has good ideas for AI but runs into trouble executing those ideas
26%
The percentage of IT leaders and decision-makers who cited challenges around talent and training as among the biggest pain points their organization has faced when planning, implementing and completing AI projects
34%
The percentage of IT leaders and decision-makers who have achieved full deployment of their highest-priority AI projects
- CLOUD AND AI: OPERATIONAL CHALLENGES
- MANAGED CLOUD AND AI SERVICES
- THE ARTIFICIAL INTELLIGENCE STAKES
- WHAT MANAGED CLOUD AND AI ENABLE
Enterprises often face significant hurdles related to skills, complexity and alignment between IT and business goals. Closing these gaps is essential for organizations that want to leverage AI competitively while managing the risks associated with poorly executed AI, including hallucinations, data breaches and compliance failures.
CLOUD SKILLS GAPS: Many organizations struggle to recruit and retain talent with deep expertise in cloud operations, hybrid environments, security and AI integration. Managed services help by embedding certified professionals into operational workflows to provide strategic guidance and hands-on support. Internal teams can then focus on high-value work rather than firefighting day-to-day issues.
MULTICLOUD/AI COMPLEXITY: Cloud environments often span multiple providers and legacy systems, which can add complexity to integration, governance and compliance efforts. Many organizations also employ multiple AI tools from different providers. Managed cloud services offer unified oversight and best-practice frameworks that help organizations tame this complexity, bringing coherence to disparate cloud usage and reducing architectural sprawl.
IT-TO-BUSINESS ALIGNMENT: As strategic partners, MSPs can help leaders map technology capabilities to business priorities such as accelerating digital product delivery, improving customer experience, reducing risk and ensuring compliance. This collaborative model fosters shared accountability and better resource planning, ensuring that cloud and AI services enable enterprise goals while streamlining IT operations.
Click Below To Continue Reading
Due to the cost and difficulty of retaining employees with experience in machine learning and AI operations, many organizations in a Day 2+ production environment lack sufficient resources and expertise to manage AI workloads. Lack of oversight creates risks that can quickly snowball, such as model drift and improper change controls. CDW provides expert capabilities on a business-day or 24/7 basis to manage, monitor, and optimize AI models and handle incident response.
Issues can also arise when boards and regulators want to see mature AI governance and ownership strategies, which the majority of organizations do not yet have. CDW’s premium services address this concern through continuous Day 2+ monitoring, policy enforcement and audit-ready evidence.
A third area of risk is system downtime for AI-powered workloads and internal processes. Restoring operations can be costly, requiring specialized services that are difficult to secure quickly. MSPs provide ongoing monitoring, enhanced by automation and AI, to enable faster detection and resolution of issues. CDW’s service level objective-backed response and root-cause analysis minimize disruption so that organizations can resume operations more quickly — directly mitigating downtime risks and costs.
Managed cloud and AI services help organizations reduce complexity, close skills gaps and align technology with business outcomes — shifts that ultimately increase agility and accelerate innovation. With the right managed services partner, enterprises can shift from reactive management to strategic execution, confident they have a solid foundation for AI initiatives.
OPERATIONAL EFFICIENCY: MSPs shift organizations from reactive support to proactive operations by providing continuous monitoring and optimization and enforcing consistent governance and security. Services such as cost tracking, incident management, architectural consultations and on-demand engineering expertise help organizations increase ROI on existing investments while allowing internal teams to focus on strategy.
BUSINESS AGILITY: The operational efficiencies generated by managed cloud services extend beyond IT. Business leaders gain enhanced visibility into performance metrics and cloud usage, enabling data-driven decisions that support scaling, modernization and strategic innovation. MSPs also enhance flexibility, enabling organizations to leverage and adapt to emerging technologies with greater speed and confidence.
ACCELERATED INNOVATION: AI evolves so quickly that IT teams can stay stuck in research and development mode. By creating a stable foundation for innovation, MSPs often accelerate initiatives by allowing teams to focus on execution. With partners handling day-to-day maintenance and operations, IT teams can prioritize moving AI solutions from pilot to production.
THE CDW ADVANTAGE: As an all-in-one managed cloud and AI services provider, CDW supports enterprises across the full IT lifecycle, providing custom solutions designed to meet specific customer needs. CDW’s experts are platform-agnostic and certified across Amazon Web Services (AWS), Microsoft Azure and Google Cloud Platform, eliminating the need to engage multiple partners for multicloud environments.
Organizations are adopting AI quickly, yet many are finding that the technology is outpacing their strategic, risk management and skills capabilities.
AI COMPLEXITY AND RISK: As IT departments expand their use of AI for process automation, cloud monitoring, troubleshooting and other aspects of infrastructure management, they often employ tools residing in multicloud or hybrid environments. To use these tools effectively, IT teams need expertise in AI and cloud management, which can present a steep learning curve for staffers supporting multiple environments. AI integration also compounds security concerns, as teams must address vulnerabilities at the cloud and AI resources level.
The gap between AI adoption speed and guardrail development increases risk. Leaders forecast a rapid expansion in agentic AI usage, with roughly three-quarters expecting to use it at least moderately in two years, up from 23% in 2026. However, many organizations lack the expertise to deploy these tools effectively.
AI AND MANAGED SERVICES: MSPs augment internal capabilities, enabling organizations to leverage AI without having to continually choose between mastering new skills or tackling existing workloads. Managed services are themselves increasingly AI-enabled, combining machine learning, predictive analytics and automation to streamline workflows at scale. For example, automated governance capabilities enforce compliance frameworks and security policies across hybrid environments, leading to a stronger risk posture with less operational overhead.
For businesses embracing AI across broader workflows, managed AI services integrate model deployment and lifecycle management into the operational fabric, ensuring models run securely, efficiently and with measurable performance. Overall, AI transforms the traditional MSP model, enabling continuous learning systems that improve over time — accelerating operational excellence and driving measurable value with minimal manual intervention.
CHOOSING THE RIGHT MSP: The rapid evolution of AI makes it imperative to engage highly qualified MSPs that can guide organizations effectively. Interest in AI is driving demand for managed services; however, a growing number of MSPs recognize that they lack the AI maturity to meet these needs. For instance, only about half of MSPs feel prepared to deliver AI-related security services to small to medium-sized businesses, down from 90% in 2024.
CDW’s AI managed services team includes certified engineers with extensive experience across all three hyperscale cloud providers and AI infrastructure from all major vendors. With emphasis on compliance, governance and security, CDW provides operational stability and strategic guidance to support organizations throughout the AI development lifecycle.
Managed cloud and AI services provide the stability, governance and scalability organizations need to move forward with confidence.
RUN RELIABLY: Operational efficiency is essential for enterprise IT. Managed cloud services deliver centralized oversight across complex environments, preventing resource sprawl and reducing wasteful cloud spending. Expert providers use cloud-native tools, automation frameworks and best practices to handle tasks such as performance tuning, patching, compliance monitoring and governance. Typically, these activities require a significant investment of in-house resources. Offloading them to a partner frees internal teams from performing this work and from continually upskilling as technologies and business strategies shift. Operational continuity is another key outcome of managed services. MSPs allow for continuous, proactive monitoring and rapid incident response, capabilities that are critical for minimizing unplanned downtime and maintaining business continuity.
GOVERN RESPONSIBLY: MSPs ensure that security and compliance are consistent by continuously monitoring environments and enforcing policy standards, further reducing operational risk. This area of expertise is essential, as 73% of companies are concerned about data privacy and security in relation to AI, yet only 21% have a mature model for governing autonomous agents.
Managed services teams also strengthen cost management, which historically has been a top challenge with cloud deployments. Partners can analyze cloud usage patterns, optimize provisioning and help teams adopt a FinOps mindset that aligns technical performance with fiscal responsibility. This often results in more predictable budgets and higher ROI from cloud investments.
SCALE INTELLIGENTLY: AI and automation enable predictive operations so that organizations can shift from reactive to proactive management. Instead of waiting for issues to occur, AI models continuously monitor cloud infrastructure to detect unusual patterns and then alert teams or take action automatically. Timely detection helps to resolve small issues before they escalate into major incidents.
Automation improves mean time to resolution and minimizes human error by reducing manual, repeatable tasks such as patching, configuration and routine diagnostics. AI-enabled management dynamically optimizes resource allocation, adjusting capacity for variable workloads and scaling infrastructure based on real-time demand to avoid under- and overprovisioning. Predictive insights help organizations anticipate future demand so they can plan upgrades or scaling efforts ahead of time.
STREAMLINED SUPPORT: In multicloud or hybrid environments, there are distinct advantages to engaging a single partner with the expertise to manage integration across all of the major cloud providers and AI environments. In addition to eliminating silos and simplifying administration across workloads, consolidating cloud and AI support under a single partner increases consistency and improves the overall coordination of these resources.
Click Below To Continue Reading
CDW simplifies the complexity of cloud and AI management by serving as a single partner across cloud, on-premises and hybrid environments. With certified experts across AWS, Microsoft Azure and Google Cloud Platform, as well as deep expertise in AI governance frameworks, CDW brings the technical depth and breadth most organizations cannot build in-house.
Engagement options range from targeted operational support to full ownership of AI operations, giving organizations the flexibility to scale partnership as their needs evolve. CDW’s proven track record of managing complex, multicloud environments at scale makes it a trusted partner at every stage of the AI journey.
- CLOUD AND AI: OPERATIONAL CHALLENGES
- MANAGED CLOUD AND AI SERVICES
- THE ARTIFICIAL INTELLIGENCE STAKES
- WHAT MANAGED CLOUD AND AI ENABLE
Enterprises often face significant hurdles related to skills, complexity and alignment between IT and business goals. Closing these gaps is essential for organizations that want to leverage AI competitively while managing the risks associated with poorly executed AI, including hallucinations, data breaches and compliance failures.
CLOUD SKILLS GAPS: Many organizations struggle to recruit and retain talent with deep expertise in cloud operations, hybrid environments, security and AI integration. Managed services help by embedding certified professionals into operational workflows to provide strategic guidance and hands-on support. Internal teams can then focus on high-value work rather than firefighting day-to-day issues.
MULTICLOUD/AI COMPLEXITY: Cloud environments often span multiple providers and legacy systems, which can add complexity to integration, governance and compliance efforts. Many organizations also employ multiple AI tools from different providers. Managed cloud services offer unified oversight and best-practice frameworks that help organizations tame this complexity, bringing coherence to disparate cloud usage and reducing architectural sprawl.
IT-TO-BUSINESS ALIGNMENT: As strategic partners, MSPs can help leaders map technology capabilities to business priorities such as accelerating digital product delivery, improving customer experience, reducing risk and ensuring compliance. This collaborative model fosters shared accountability and better resource planning, ensuring that cloud and AI services enable enterprise goals while streamlining IT operations.
Click Below To Continue Reading
Due to the cost and difficulty of retaining employees with experience in machine learning and AI operations, many organizations in a Day 2+ production environment lack sufficient resources and expertise to manage AI workloads. Lack of oversight creates risks that can quickly snowball, such as model drift and improper change controls. CDW provides expert capabilities on a business-day or 24/7 basis to manage, monitor, and optimize AI models and handle incident response.
Issues can also arise when boards and regulators want to see mature AI governance and ownership strategies, which the majority of organizations do not yet have. CDW’s premium services address this concern through continuous Day 2+ monitoring, policy enforcement and audit-ready evidence.
A third area of risk is system downtime for AI-powered workloads and internal processes. Restoring operations can be costly, requiring specialized services that are difficult to secure quickly. MSPs provide ongoing monitoring, enhanced by automation and AI, to enable faster detection and resolution of issues. CDW’s service level objective-backed response and root-cause analysis minimize disruption so that organizations can resume operations more quickly — directly mitigating downtime risks and costs.
Managed cloud and AI services help organizations reduce complexity, close skills gaps and align technology with business outcomes — shifts that ultimately increase agility and accelerate innovation. With the right managed services partner, enterprises can shift from reactive management to strategic execution, confident they have a solid foundation for AI initiatives.
OPERATIONAL EFFICIENCY: MSPs shift organizations from reactive support to proactive operations by providing continuous monitoring and optimization and enforcing consistent governance and security. Services such as cost tracking, incident management, architectural consultations and on-demand engineering expertise help organizations increase ROI on existing investments while allowing internal teams to focus on strategy.
BUSINESS AGILITY: The operational efficiencies generated by managed cloud services extend beyond IT. Business leaders gain enhanced visibility into performance metrics and cloud usage, enabling data-driven decisions that support scaling, modernization and strategic innovation. MSPs also enhance flexibility, enabling organizations to leverage and adapt to emerging technologies with greater speed and confidence.
ACCELERATED INNOVATION: AI evolves so quickly that IT teams can stay stuck in research and development mode. By creating a stable foundation for innovation, MSPs often accelerate initiatives by allowing teams to focus on execution. With partners handling day-to-day maintenance and operations, IT teams can prioritize moving AI solutions from pilot to production.
THE CDW ADVANTAGE: As an all-in-one managed cloud and AI services provider, CDW supports enterprises across the full IT lifecycle, providing custom solutions designed to meet specific customer needs. CDW’s experts are platform-agnostic and certified across Amazon Web Services (AWS), Microsoft Azure and Google Cloud Platform, eliminating the need to engage multiple partners for multicloud environments.
Organizations are adopting AI quickly, yet many are finding that the technology is outpacing their strategic, risk management and skills capabilities.
AI COMPLEXITY AND RISK: As IT departments expand their use of AI for process automation, cloud monitoring, troubleshooting and other aspects of infrastructure management, they often employ tools residing in multicloud or hybrid environments. To use these tools effectively, IT teams need expertise in AI and cloud management, which can present a steep learning curve for staffers supporting multiple environments. AI integration also compounds security concerns, as teams must address vulnerabilities at the cloud and AI resources level.
The gap between AI adoption speed and guardrail development increases risk. Leaders forecast a rapid expansion in agentic AI usage, with roughly three-quarters expecting to use it at least moderately in two years, up from 23% in 2026. However, many organizations lack the expertise to deploy these tools effectively.
AI AND MANAGED SERVICES: MSPs augment internal capabilities, enabling organizations to leverage AI without having to continually choose between mastering new skills or tackling existing workloads. Managed services are themselves increasingly AI-enabled, combining machine learning, predictive analytics and automation to streamline workflows at scale. For example, automated governance capabilities enforce compliance frameworks and security policies across hybrid environments, leading to a stronger risk posture with less operational overhead.
For businesses embracing AI across broader workflows, managed AI services integrate model deployment and lifecycle management into the operational fabric, ensuring models run securely, efficiently and with measurable performance. Overall, AI transforms the traditional MSP model, enabling continuous learning systems that improve over time — accelerating operational excellence and driving measurable value with minimal manual intervention.
CHOOSING THE RIGHT MSP: The rapid evolution of AI makes it imperative to engage highly qualified MSPs that can guide organizations effectively. Interest in AI is driving demand for managed services; however, a growing number of MSPs recognize that they lack the AI maturity to meet these needs. For instance, only about half of MSPs feel prepared to deliver AI-related security services to small to medium-sized businesses, down from 90% in 2024.
CDW’s AI managed services team includes certified engineers with extensive experience across all three hyperscale cloud providers and AI infrastructure from all major vendors. With emphasis on compliance, governance and security, CDW provides operational stability and strategic guidance to support organizations throughout the AI development lifecycle.
Managed cloud and AI services provide the stability, governance and scalability organizations need to move forward with confidence.
RUN RELIABLY: Operational efficiency is essential for enterprise IT. Managed cloud services deliver centralized oversight across complex environments, preventing resource sprawl and reducing wasteful cloud spending. Expert providers use cloud-native tools, automation frameworks and best practices to handle tasks such as performance tuning, patching, compliance monitoring and governance. Typically, these activities require a significant investment of in-house resources. Offloading them to a partner frees internal teams from performing this work and from continually upskilling as technologies and business strategies shift. Operational continuity is another key outcome of managed services. MSPs allow for continuous, proactive monitoring and rapid incident response, capabilities that are critical for minimizing unplanned downtime and maintaining business continuity.
GOVERN RESPONSIBLY: MSPs ensure that security and compliance are consistent by continuously monitoring environments and enforcing policy standards, further reducing operational risk. This area of expertise is essential, as 73% of companies are concerned about data privacy and security in relation to AI, yet only 21% have a mature model for governing autonomous agents.
Managed services teams also strengthen cost management, which historically has been a top challenge with cloud deployments. Partners can analyze cloud usage patterns, optimize provisioning and help teams adopt a FinOps mindset that aligns technical performance with fiscal responsibility. This often results in more predictable budgets and higher ROI from cloud investments.
SCALE INTELLIGENTLY: AI and automation enable predictive operations so that organizations can shift from reactive to proactive management. Instead of waiting for issues to occur, AI models continuously monitor cloud infrastructure to detect unusual patterns and then alert teams or take action automatically. Timely detection helps to resolve small issues before they escalate into major incidents.
Automation improves mean time to resolution and minimizes human error by reducing manual, repeatable tasks such as patching, configuration and routine diagnostics. AI-enabled management dynamically optimizes resource allocation, adjusting capacity for variable workloads and scaling infrastructure based on real-time demand to avoid under- and overprovisioning. Predictive insights help organizations anticipate future demand so they can plan upgrades or scaling efforts ahead of time.
STREAMLINED SUPPORT: In multicloud or hybrid environments, there are distinct advantages to engaging a single partner with the expertise to manage integration across all of the major cloud providers and AI environments. In addition to eliminating silos and simplifying administration across workloads, consolidating cloud and AI support under a single partner increases consistency and improves the overall coordination of these resources.
Click Below To Continue Reading
CDW simplifies the complexity of cloud and AI management by serving as a single partner across cloud, on-premises and hybrid environments. With certified experts across AWS, Microsoft Azure and Google Cloud Platform, as well as deep expertise in AI governance frameworks, CDW brings the technical depth and breadth most organizations cannot build in-house.
Engagement options range from targeted operational support to full ownership of AI operations, giving organizations the flexibility to scale partnership as their needs evolve. CDW’s proven track record of managing complex, multicloud environments at scale makes it a trusted partner at every stage of the AI journey.
CDW has the experience and expertise to simplify the complexity of artificial intelligence and the cloud.
Don DeHamer
Chief Technical Architect for CDW Managed Services Cloud Lifecycle Services
Santoshkumar Ravi
CDW Principal Consultant