Economic uncertainty, supply chain disruption, evolving regulations, and rising pressure on productivity are forcing enterprises to rethink how they operate. For organizations running SAP, the conversation has moved beyond system stability. AI is now expected to participate in core business execution: anticipating disruptions, recommending actions, and accelerating decisions across finance, supply chain, procurement, and operations. This shift raises an important question for enterprise leaders: How can the operational foundation supporting these processes keep pace with the demands of AI-driven execution?

The New Reality: SAP Operations are Under Growing Pressure

For years, SAP operations were measured primarily by system availability and issue resolution. A stable landscape, reliable performance, and strong governance were often considered indicators of operational success. Today, the expectations are significantly higher. Business leaders are navigating an environment where market conditions change rapidly, supply chains face ongoing disruption, and organizations are under constant pressure to improve productivity while controlling costs. In this environment, SAP operations are increasingly judged on resilience to keep critical processes running, agility to respond to changing priorities, and consistency in the data and governance the business depends on.

However, most SAP environments were not built for this bar. The obstacles are often not within the SAP platform itself, but within the way SAP environments are operated. Change requests can take weeks to move through testing and approval cycles. Meanwhile, critical expertise remains concentrated among a handful of specialists, creating operational bottlenecks and institutional dependencies. Over time, operational processes may also become fragmented across business units and geographic locations, reducing consistency and visibility across the enterprise. These challenges limit an organization's ability to adapt quickly while maintaining the governance and control that SAP environments require. As business expectations continue to rise, SAP operations are increasingly becoming a transformation bottleneck rather than a transformation enabler.

The impact extends far beyond operational efficiency. Gartner predicted that more than 80% of enterprises will have used generative AI APIs or deployed GenAI-enabled applications in production environments by 2026. However, a global study by FPT and Forrester found that only 39% of organizations have made meaningful progress in executing AI strategies, governance models, and operating frameworks. The gap highlights a growing reality: deploying AI is becoming easier, but embedding AI into mission-critical business processes remains significantly harder.

For many enterprises, the challenge is not access to AI technology, but whether their operating environment can provide the process consistency, institutional knowledge, trusted data, and governance needed for AI to learn, act, and improve at scale. AI can only act consistently when the processes it interacts with are consistent, the knowledge it relies on is accessible, and the data and controls surrounding those processes are trusted. As a result, the focus is beginning to shift from deploying AI within SAP environments to redesigning SAP operations as the foundation for enterprise-wide AI execution.

Building SAP Operations That Learn, Adapt, and Improve Over Time

Before AI can scale across SAP environments, organizations must first establish a common operational foundation that AI can learn from, interact with, and continuously improve.

Sharing the perspective on this challenge at the FPT Halong Sapphire Summit, Endo Akihiro, Executive Director of FPT Consulting Japan, outlined a vision for next-generation SAP operations “Global x AI,” built on the combination of global standardization and AI-driven continuous improvement. In his view, the objective is not simply to automate support activities, but to support AI to be deployed consistently across the SAP landscape, turning operational data, knowledge, and expertise into a continuous cycle of improvement.

Endo Akihiro shared his perspective on how SAP operations must evolve to support enterprise AI at scale.

One of the most important foundations is globalized process standardization. Many organizations run SAP through different procedures, support models, and operational practices across sites and regions. While these local approaches may address immediate business needs, they often create fragmented knowledge, duplicated effort, and inconsistent ways of working. In FPT's operating model, a single standardized process is established across all sites, allowing incidents, change requests, testing activities, and operational procedures to be managed consistently regardless of location. This creates a common operational language and transforms knowledge from a local asset into an enterprise asset.

Another critical component is the development of shared knowledge assets. Traditional SAP operations depend heavily on experienced specialists who hold institutional knowledge in their heads. While expertise remains essential, overreliance on individuals can create bottlenecks and operational risk. FPT's approach focuses on capturing operational insights, procedures, and lessons learned in reusable formats, which transforms expertise from an individual capability into an enterprise asset. This creates the conditions for AI systems to retrieve, contextualize, and apply operational knowledge consistently across teams, locations, and business functions.

Once operational data, procedures, and knowledge are standardized, AI-driven automation can begin working on top of that foundation. Within FPT's Global × AI model, AI assists with impact assessment, root-cause isolation, testing, knowledge retrieval, and procedural recommendations, AI can help reduce manual effort while shortening response times. It can also help management identify early signals such as profitability decline, cash-flow constraints, delivery risks, or control anomalies and evaluate potential responses more quickly. Over time, these capabilities contribute to a more intelligent operational model where knowledge becomes continuously available, improvements can be repeatedly applied, and operational signals are transformed into business insights.

Together, these capabilities create a progression from standardized operations to institutionalized knowledge and, ultimately, AI-enabled execution. The objective is not to replace human expertise, but to make that expertise more accessible, scalable, and actionable across the enterprise.

Enabling AI-Powered SAP Operations into Business Reality with FPT

Transforming SAP operations requires the right combination of platform expertise, industry knowledge, operational experience, and AI capabilities. It also demands the right partner with AI positioned as a core capability, and a strong SAP implementation and maintenance services.

Over more than two decades of collaboration with SAP, FPT has become the largest SAP service organization in the APAC region, supporting enterprises across manufacturing, energy, retail, financial services, logistics, and other industries. The company’s capabilities are reinforced by a series of recognitions, including its designation as an SAP Regional Strategic Services Partner. The company has also expanded its investment in innovation through initiatives such as FPT BTP Park, which was launched in Japan to accelerate SAP Business Technology Platform adoption and enterprise innovation.

FPT brings together more than 1,600 SAP consultants and specialists across SAP S/4HANA, SAP BTP, cloud transformation, and managed services.

Building on this foundation, FPT helps organizations modernize and operate SAP environments across the full transformation lifecycle, from consulting and implementation to modernization, migration, application management, and managed services. One example is a leading Japanese trading company that had operated a heavily customized SAP environment for more than 20 years. Working alongside the client, FPT supported a large-scale SAP S/4HANA transformation based on a Fit-to-Standard approach, helping remove more than 3,000 modified SAP objects and reduce add-ons by 90% across 50 locations. The transformation simplified operations, centralized business data, and created a more maintainable platform capable of supporting future business growth and digital initiatives.

Beyond traditional SAP services, FPT is helping organizations operationalize SAP Business AI through capabilities spanning SAP Business Data Cloud, SAP Business Technology Platform, Joule, SAP Knowledge Graph, and AI-powered workflow automation. These capabilities enable enterprises to move beyond transactional operations by applying AI to areas such as demand forecasting, operational optimization, process guidance, workflow orchestration, transaction automation, and business decision support.

Building the Operational Foundation for AI at Scale

The future of enterprise AI will be shaped not only by advances in models, but by the operational systems that allow AI to act with consistency, context, and control. For SAP-driven organizations, building that foundation begins with standardized processes, scalable knowledge, and a framework for continuous improvement. As AI moves closer to everyday business execution, the question is no longer whether enterprises can deploy AI, but whether their SAP operations are prepared to support it at scale.

By combining globally standardized operations with AI-driven continuous improvement, FPT helps enterprises build SAP environments that are not only more efficient to operate, but also better equipped to scale knowledge, accelerate decision-making, and adapt to future business demands.

Learn more about how FPT helps businesses run SAP with AI-driven transformation here.