Scaling enterprise AI with managed services

Insight

Orchestrating AI‑driven transformation with managed services

The 2026 KPMG Managed Services Outlook highlights a major shift in managed services industry trends in the US. The report shows how AI‑enabled managed services are driving transformation by helping organizations orchestrate complexity, manage risk, and move faster.

Read the 2026 KPMG Managed Services Outlook

The accelerated progress of artificial intelligence (AI) is dialing up pressure on chief information officers (CIOs) to deliver enterprise-wide AI impact while stabilizing complex architectures, modernizing legacy portfolios, and managing risk—all within constrained budgets and rising stakeholder expectations. The result is a widening execution gap: While business demands accelerate, many information technology (IT) foundations were not originally built for the speed of autonomous workflows, generative AI, or continuous cross-system orchestration.

While pilot programs are proliferating, true enterprise readiness remains elusive. Fragmented data, inconsistent integration patterns, and significant tool sprawl can overwhelm even the most ambitious AI initiatives. Furthermore, foundational technical debt often competes for funding with front-office innovation, leaving IT leaders to address modernization and transformation simultaneously without a dedicated operating structure to advance either goal.

Consequently, forward-thinking IT leaders are evaluating a strategic shift toward a new generation of managed services that can deliver viable, trusted implementation and governance of AI systems and applications.

Modern managed services bear little resemblance to the transactional outsourcing of the past; instead, it is emerging as a critical operating model designed to resolve the structural barriers that stall AI maturity and impede modernization. According to the 2026 KPMG Global Managed Services Outlook survey, AI management is now the single largest area of planned investment for managed services in the next two years, and 98 percent of senior leaders cite AI implementation as a critical capability they demand from managed services providers.¹

The shifting CIO mandate: How should CIOs align the IT operating model to successfully scale AI?

To realize the full potential of AI, the underlying IT operating model must evolve in three critical areas:

Transitioning from legacy workflows to AI-ready foundations

Many IT environments still rely on manual workflows and fragile integrations that may struggle under the nonlinear compute demands of AI. A modern managed services approach helps stabilize this foundation through centralized control, proactive monitoring, and automated operations—enabling internal teams to pivot their focus toward high-value modernization and AI enablement.

Overcoming fragmentation and tool sprawl

Siloed AI initiatives can lead to redundant costs and inconsistent security standards. When teams are forced to reinvent compliance and data integration for every new use case, momentum is lost. Modern managed services provide unified observability and integrated risk controls, helping ensure the environment remains governed and secure as it scales.

Addressing the talent and organizational gap

AI transformation is as much a workforce challenge as a technical one. KPMG research shows that deep AI, platform, and data expertise are all paramount criteria for senior leaders when selecting a managed services partner.¹ Leading providers embed Centers of Excellence to provide the necessary architectural guardrails, delivery discipline, and strategic higher-order skills to accelerate innovation and adoption, while also upskilling and elevating internal teams, rather than eliminating them.

A significant portion of the fragmentation challenge lies in the cloud platforms—such as Oracle, Workday, ServiceNow, SAP, and Coupa—that underpin modern enterprise functions. As these software-as-a-service (SaaS) platforms mature, organizations often fall behind on updates and the rapidly evolving AI capabilities embedded within them, resulting in unused features and untapped value.

Without continuous management, today’s cloud investments risk becoming tomorrow’s legacy constraints. To prevent this, foundational platforms can be continually optimized through a unified operating model. Modern cloud platform management—characterized by structured release cycles, integration automation, and analytics-driven insights—reinforces the capabilities you need to scale AI safely:

Version currency

Keeping core systems current so embedded AI features can be activated responsibly

Business alignment

Ensuring platforms remain connected and governed as business needs evolve

Operational excellence

Applying predictive analytics to reduce manual effort and improve reliability

Specialized expertise

Leveraging platform specialists to drive continuous improvement across the entire SaaS landscape.

A modern managed services model for SaaS is not just about maintenance, but about preparing the very foundation on which AI will operate. This is why leading organizations are increasingly focusing on managed services that optimize their SaaS ecosystem. Research shows that 40 percent of managed services buyers are specifically seeking AI-powered optimization of their cloud applications, recognizing that AI agents are only as effective as the platforms they orchestrate.¹

A modern managed services model provides the duality CIOs require: stability coupled with speed, and predictability paired with innovation. This approach offers:

A unified structure to reduce architectural fragility: A single operating model across applications and cloud environments prevents integration hurdles from becoming a bottleneck.

Embedded automation and AI-enabled operations: Smart analytics and automated workflows eliminate manual effort and identify potential issues before they impact the business.

Governance tied to business outcomes: Key performance indicators and compliance loops provide the transparency and accountability that boards and stakeholders now demand.

Cost predictability amid volatile demand: As AI workloads fluctuate, a unified model creates predictable run-costs and mitigates budget volatility. In fact, cost savings and efficiency are top goal for managed services, according to KPMG research.¹ And performance is strong: Among leaders who cite predictable costs and lower up-front capital investment as top three goals, 91 percent say managed services have met or exceeded expectations.¹

A shift from maintenance to innovation: Managed services providers bring leading-edge technology to bear, invest in continuous innovation to keep pace with advancements, and reduce the operational burden to liberate internal talent to focus on strategic initiatives. These capabilities are increasingly resulting in transformational outcomes: Three of the top four managed services goals of business leaders are access to new tech (27 percent), faster speed to market for new products and services (25.5 percent), and accelerated innovation (25 percent).¹

Managed services should no longer be viewed through the lens of tactical cost-containment. Instead, they represent a strategic platform decision—the most effective way to build the predictable, integrated, and insight-driven environment required for enterprise AI. By shifting the operational burden to a modern managed services model, CIOs can bridge the execution gap and turn “legacy” cloud investments into engines of continuous innovation.

The strategic value of a managed IT service model centers on three critical outcomes that directly impact AI maturity:

1 | Maximizing platform potential and feature adoption

Cloud platforms—from enterprise resource planning and customer relationship management to IT and human resources systems—power the modern enterprise. However, many organizations are leaving significant value on the table. A modern managed services model helps ensure you are not only “running” a platform but also evolving it. By activating embedded AI capabilities and staying current with rapid release cycles, you ensure today’s cloud investments do not become tomorrow’s legacy constraints.

2 | Delivering measurable operational excellence

To earn the right to lead AI transformation, IT must first demonstrate foundational excellence. Modern managed services utilize AI-enabled tools, automated workflows, and predictive analytics to move from reactive troubleshooting to proactive optimization. For example, a Forrester Total Economic Impact™ (TEI) study commissioned by KPMG found that organizations using KPMG Powered Evolution for SaaS management experienced a 236 percent return on investment (ROI) over three years. This included tangible outcomes like the elimination of 80 percent of end-user downtime and significant efficiency gains that one CIO estimated would have required “another five to ten people” to achieve internally.² These results, from cost predictability to operational resilience, are what give IT the credibility and capacity to lead AI transformation.

3 | Cultivating a high-velocity innovation engine

AI transformation is hindered when elite internal talent is mired in “keep-the-lights-on” maintenance. Modern managed services provide access to skilled platform specialists across Oracle, Workday, ServiceNow, SAP, Coupa, and more. This specialized support allows your internal teams to stop fighting architectural fires and start focusing on high-value AI use cases and strategic business alignment.

When managed operations are transformational rather than transactional, they provide the stability and speed necessary to scale AI with confidence. The organizations that gain a competitive advantage will be those that treat managed services as the strategic engine behind modernization, AI scalability, and a renewed confidence in the IT function.

¹KPMG Global Managed Services Outlook Survey 2026
²Forrester Total Economic Impact™ (TEI) study that evaluated KPMG Powered Evolution for SaaS management

Dive deeper into shifts in the market's approach to managed services and actionable advice for succeeding with AI-enabled managed services.

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How KPMG can help: Accelerating IT’s AI-driven evolution

KPMG helps organizations bridge the gap between fragmented technology and integrated, AI-ready operations. We provide the strategic operating model required to help optimize your current platforms while simultaneously building the foundation for future innovation.

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