How GenAI Speeds an SAP S/4HANA Transformation and Scales What Comes Next

SAP S/4HANA transformations remain among the highest-stakes investments enterprises make. ERP programs have followed a familiar and expensive script for the past two decades: multi-year timelines, vendor ecosystems consuming 40% to 60% of program costs, and business cases that dissolve once go-live takes over. Based on global consulting firm BCG’s experience, between 50% and 70% of ERP modernization programs fall short of their goals, even when AI is involved.

The programs that beat those odds treat SAP S/4HANA as a business transformation built around value, and they use AI to carry it out. In a program run this way, AI plays two roles. During delivery, it is the engine that speeds the transformation. Embedded across the SAP Activate phases, generative AI compresses timelines, keeps the business case visible, and strengthens oversight of system integrators. After go-live, AI becomes the dividend that scales across the enterprise. The clean core, fit-to-standard design, and governed data built during the program are the foundation on which Joule agents and agentic AI drive business value.

The two roles share a single through line: value-led governance. The value levers, ownership model, and architectural discipline that let GenAI accelerate delivery are the same assets that let enterprise AI scale safely after go-live.

The Foundation: Value Comes Before AI

AI does not create value by itself. It amplifies disciplined, value-led transformation, which means the foundation has to be in place before either of AI’s roles can pay off.

Successful transformations begin with strategic choices about how the company wants to compete. Rather than an IT project delegated downward, the program is treated as a generational inflection point: the foundation for how the business will run, compete, and grow for the next decade. Those choices cascade into a Business Target Picture that defines how each end-to-end process will operate.

That vision is then translated into execution discipline. A value-lever approach maps value creation across processes such as Source-to-Pay and Lead-to-Cash, assigns Executive Committee ownership to each lever, and links metrics such as DSO, OEE, and OTIF to the business case. The results can include:

• Up to 20% reductions in operational costs
• A 0.8 to 1.2 percentage-point EBITDA uplift when strategic objectives stay front and center

This foundation shapes what AI can do in both roles. During delivery, value levers with named owners give GenAI something concrete to track, simulate, and report against. Without them, AI-enabled delivery accelerates a program that has no clear destination. After go-live, the same levers and ownership model become the governance that enterprise AI depends on to scale safely.

Role One: GenAI as the Engine of Delivery

With the value foundation in place, the next question is how GenAI is embedded across the delivery lifecycle. BCG identifies six dimensions that decide whether SAP S/4HANA programs fail or deliver:

• Scope and objectives
• Business value and economics
• Governance and organization
• Solution and deliverables
• Planning and execution
• Supplier and partner management

BCG applies an AI-first approach to each dimension across every SAP Activate phase, from Discover through Run & Value Capture. The approach replaces fragmented, manual delivery with integrated, AI-enabled execution. It compresses timelines, reduces risk and cost, and accelerates ROI, while keeping investment tied to measurable business outcomes throughout the program.

The impact shows up across several of these dimensions. On business value, CFOs gain real-time value cockpits that simulate the financial impact of scope changes before they are approved, which keeps the business case in view during delivery. On governance, GenAI produces board-ready status reporting in minutes. On the solution itself, it flags unnecessary customizations that would erode the clean core and compresses testing cycles. On supplier and partner management, it benchmarks system integrator proposals, a critical lever given that vendor ecosystems consume 40% to 60% of total program costs.

Taken together, BCG research indicates that GenAI can reduce the effort of an organization-wide ERP implementation by 20% to 40%. That is the first role for AI: the mechanism that moves the program toward its Business Target Picture faster and with less risk. Along the way, it also builds the clean core and governance habits that the second role depends on.

Role Two: The Transformation as the Launchpad for Enterprise AI

The second role begins at go-live, when Joule agents and agentic AI start driving business value across the enterprise. How far they can go depends on what the program built: a clean core, fit-to-standard design, governed data, and value levers with executive owners. BCG’s NextGen ERP x GenAI series argues that organizations must align strategy, value governance, and enterprise architecture before the platform pays off.

Most SAP customers have not reached that point. SAPinsider’s AI Adoption and Maturity in the SAP Ecosystem benchmark finds that AI adoption among SAP customers is accelerating in tandem with initiatives such as SAP S/4HANA migration, cloud modernization, and business process automation. Yet while 91% of organizations report some AI use, only 18% have integrated it across several processes, and just 14% operate at an optimized stage. SAPinsider’s study, Orchestrating AI-Driven Process Transformation in SAP-Centric Enterprises, finds that even with SAP’s announcements about the SAP Business AI Platform and SAP Autonomous Suite, only a small proportion of SAP customers use AI across multiple departments or enterprise-wide processes. Where they do use AI today, it delivers value mainly in workflow automation, conversational interfaces, and decision support.

The benchmark finds that success is driven primarily by the technologies utilized and the governance frameworks in place. That puts governance and clean core architecture at the center of what separates AI Leaders from laggards among SAP customers, and both are built during delivery. A program that uses GenAI to flag unnecessary customizations is building the clean core that the second role requires. A program that keeps CFOs in a real-time value cockpit is building the governance habit that enterprise AI will depend on. The work done in the first role becomes the base for the second.

The BCG and SAP Partnership, From Value Foundation to Enterprise AI

BCG’s partnership with SAP spans every stage of the transformation, from the value foundation through delivery to enterprise AI after go-live.

Powertrain by BCG anchors the value foundation, drawing on a library of more than 250 proven value levers and tracking benefits throughout the journey. During delivery, Powertrain integrates SAP Signavio and SAP LeanIX to accelerate the transformation, backed by the execution strength of BCG Platinion and the technology expertise of BCG X. After go-live, SAP S/4HANA, SAP Business Data Cloud, SAP Joule, and the SAP Generative AI Hub provide the platform for the second role. BCG orchestrates value across the full program, and the partnership delivers a streamlined core that gives organizations the flexibility to adapt as business needs change.

An organization weighing its SAP S/4HANA move should plan the program with both roles in view. The transformation is a chance to redesign how the enterprise captures value, governs its data, and deploys AI, and a partner’s job is to help it do all three well.

What This Means for SAPinsiders

• Define the value direction before bringing in AI. The programs that beat the 50% to 70% failure rate start with strategic choices about how the company competes, cascade them into a Business Target Picture, and assign quantified value levers to CFOs and COOs. CIOs and ERP program managers who put this in place first give GenAI a clear destination to accelerate toward.
• Build GenAI into delivery governance from Discover onward. Real-time value cockpits keep the business case in view during delivery, GenAI-generated status reporting gives leaders board-ready updates in minutes, and SI proposal benchmarking targets the 40% to 60% of program cost tied up in vendor ecosystems. ERP program managers who embed these controls early position the program to capture the 20% to 40% effort reduction BCG research identifies and to reach go-live with the business case intact.
• Protect the assets enterprise AI needs after go-live. SAPinsider research shows only 18% of SAP customers have integrated AI across several processes, and governance frameworks separate AI Leaders from the rest. Enterprise architects who protect the clean core, fit-to-standard design, and governed data during delivery give Joule agents and agentic AI the base they need to scale safely and drive business value after go-live.