Thomas Saueressig, SAP’s Executive Board Member for Product Engineering, began the Sapphire Customer Keynote saying that this was not going to be a one-sided presentation. Instead, the session would be interactive, narrative-led, and centered on SAP customers navigating transformation in an unpredictable world.
Saueressig drew a direct connection between global volatility, elections, tariffs, ongoing geopolitical tensions, and the mounting pressure on SAP users to modernize, reduce costs, and deliver faster outcomes.
The overarching theme was that adaptability is now a prerequisite for survival.
SAP’s own response to this, as he framed it, was a push toward more usable, faster-delivering tooling, embodied in the evolving AI portfolio, the RISE with SAP model, and its integrated tool chain.
In this article IgniteSAP will cover the content of the Day 2 Keynote, SAP’s strategic development, and what these examples of customer transformation indicate about the current state of the ecosystem, and the future for SAP consulting.
In Saueressig’s early discussion of RISE with SAP he revealed that over 8,500 customers had already adopted RISE, and these organizations now represent an estimated 40% of global GDP. In other words, it’s becoming the new standard for SAP-led transformation.
That shift is supported by operational scale as well.
SAP now manages over 146,000 customer systems with an SLA adherence rate of 99.996%, an achievement framed as a baseline expectation in a high-risk, always-on business landscape.
This was also the first formal unveiling of RISE’s methodological expansion from a “fit-to-standard” model to a broader “fit-to-suite” approach: subtle in phrasing, but indicative of SAP’s broader ambition to handle full-suite transformation through consistent tooling and lifecycle visibility.
This expansion and strategic adjustment suggests that we are likely to see corresponding changes in consulting delivery models, scoping frameworks, and how consultants will be expected to engage with future projects.
The customer stories began with Mercedes-Benz, and CIO Katrin Lehmann brought the discussion back to the lived reality for SAP customers.
Even among professionals who have worked consistently in large-scale transformations the numbers involved in the Mercedes-Benz project that was related were daunting: over 10,000 applications, including 1,200 SAP systems, most still running ECC.
Mercedes’ use of LeanIX as a sorting mechanism: classifying systems by priority and mapping actions to categories like migrate, transform, invest, or eliminate, offered a methodical counterpoint to the scale of their legacy.
The message was about the importance of sustained architectural clarity. And their decision to apply RISE with SAP to only the most essential systems first was a reminder that transformation, even in large enterprises, must always prioritize.
For SAP consultants involved in pre-implementation roadmapping or legacy landscape assessments, this was an instructive view into how tools like LeanIX are becoming operationally essential to make sense of complexity.
Mercedes’ transformation story naturally progressed into its AI strategy.
Lehmann’s description of their existing use of GitHub Copilot, ChatGPT-style internal interfaces, and embedded AI across the supply chain painted a picture of an organization already comfortable with applied AI. But what she made clear was that the real value still lay ahead, with SAP Joule expected to augment and structure the broader use of AI in enterprise scenarios.
One of the more resonant examples was Mercedes’ deployment of conversational AI for plant workers: natural-language quality checks powered by internal chatbots. This wasn’t presented as an AI revolution, it was grounded, specific, and outcome-focused.
This showed how AI conversations in SAP are shifting from boardroom strategy to operational deployment, and this needs a new level of readiness across implementation partners, especially in defining, building, and supporting cross-functional AI use cases.
Next on stage was Jan Gilg, SAP’s Chief Revenue Officer for the Americas and Business Suite, who brought a long view on business systems proliferation.
He used a simple contrast: in 2000, a typical $10B company ran 10 applications. By 2025, that number is 600, but while the complexity of the IT landscape has increased, it is clear there has not been a 60x increase in productivity, demonstrating that more tools does not necessarily mean better businesses, if they are not mutually supportive.
This narrative shift toward harmonized, data-driven business suites, is especially relevant for SAP consultants focused on integration, modular architectures, and process orchestration. Gilg’s framing suggests a new frontier for productivity isn’t in individual apps or even in AI alone, but in the connective tissue that binds them into integrated outcomes.
Geoff Scott, CEO of Americas’ SAP User Group (ASUG), took the discussion further by offering the customer community’s perspective.
Scott’s points were familiar, but vital. Simplicity in the face of uncertainty and complexity. Collaboration over isolated innovation, and pilot projects that scale.
Scott’s comments reinforced a truth that every consultant has experienced: the challenges with AI in SAP aren’t purely technological, they are also very much human and structural.
Data quality, change management, governance, and trust are the main friction points.
Saueressig pointed out SAP’s reliance on structured feedback channels, through executive exchanges, user experience tracking, and customer influence pods, and also hinted at a deeper trend. SAP is increasingly building mechanisms to listen, as the founders of SAP also listened to their customers in order to improve. For internal SAP teams and SAP partners, that means the value of structured customer feedback will only grow in how product features and consulting strategies are defined.
The narrative shifted next to Phoenix Global, where CIO Jeff Suellentrop described one of the more striking turnaround stories presented on stage.
Unlike the high-profile, long-established names that typically feature in SAP case studies, Phoenix represented a company recovering from over-expansion during a period of intense economic pressure.
Between 2021 and 2023, the firm had grown rapidly, opening eight new sites in just two years: too quickly to develop the digital backbone needed to sustain that growth. By the time Suellentrop joined in early 2023, the company was entering bankruptcy.
From that point Phoenix opted for SAP GROW, aiming to replace every subsystem and eliminate manual processes entirely. The commitment to best practices wasn’t about compliance, it was about making the business function again.
Phoenix’s implementation took just eight months. That pace, combined with a full rebuild of the data model and the deployment of SAP maintenance solutions across its equipment-intensive operations, allowed them to recapture millions in lost value.
Their approach showed what can happen when necessity drives radical simplification, and also showed how even highly capital-intensive industries are no longer waiting for perfect readiness. They are shifting away from old strategies and assumptions, fundamentally rethinking their operations, and expecting support models that can keep up.
From crisis recovery, the keynote moved to Mars: one of the world’s most recognizable private companies. What stood out in the presentation by CIO Will Beery and VP of Digital Platforms, Praveen Moturu, was their architectural discipline.
Mars operates in multiple segments, from confectionery and snacking to retail and acquisitions, and they’ve responded with a three-tier ERP strategy.
Public cloud supports fast-scaling units like TruFru and Nature’s Bakery. A retail-specific RISE instance serves flagship M&M’s stores and the newly acquired Hotel Chocolat. And for the core Mars-Wrigley business, a customized template is in development.
Moturu added depth by describing Mars’ model-driven architecture, built from business capabilities down to data and applications. What was particularly resonant was the way they used the SAP Business Suite to automate, but also to raise the bar. Automation replaced repetitive work, embedded analytics improved decision-making, and AI (particularly Joule) was deployed across both public and private cloud environments.
This was an admirable example of a complex, but sustainable, architecture-led reinvention that accommodated both large and small units. It was not a case for lifting and shifting processes, but about creating a data and process architecture that can support both scale and speed.
The conversation with Mars concluded with a discussion of Business Data Cloud (BDC), which was referenced as a central pillar in Mars’ future AI strategy.
Moturu and Beery described BDC as a tool for building a consistent data foundation across a sprawling enterprise. They were particularly focused on its potential for standardization, canonical modelling, and cross-unit integration.
But what made their advice relevant for a broader SAP audience was their emphasis on sequencing.
First, develop a clear roadmap. Second, build stakeholder engagement early. And third, focus on quick wins to maintain momentum and executive sponsorship.
Their message was that transformation is not linear, and the tools will keep changing. But a committed architecture strategy, reinforced by usable platforms and rapid results, can help large organizations remain adaptable.
Consultants working with similar global businesses will recognize the value of this blueprint, especially in multi-brand, multi-region SAP contexts.
Saueressig returned to outline four aims for the integrated tool chain: reducing transformation costs, shortening time to value, improving adaptability, and increasing innovation throughput.
Examples included BHP, which used Signavio to overhaul shared services and capture $500M in value; Nestlé, which employed WalkMe to save 1.5 million hours of employee time across 200+ applications, and First Abu Dhabi Bank, which cut its application footprint by 25%.
The audience was then taken through a detailed live demo by Mohan Jayarama, showcasing how Signavio, LeanIX, Cloud ALM, Joule, and third-party tools form a guided pathway from process diagnostics to go-live and post-launch optimization. The comprehensive walkthrough involved scenario simulation, application fit assessments, architecture redesign, project planning, clean core benchmarking, automated testing, and in-app guidance.
The intent was to make the point that transformation need not start with a blank sheet.
There is now a coherent, supported lifecycle, from assessment to execution to measurement, that can be orchestrated using SAP’s tools.
The final segment of the keynote introduced a restructured approach to services and support, moving toward a three-tier model (Foundational, Advanced, and Max). While the idea of tiers isn’t new, what made this noteworthy was the alignment of each level to specific AI capabilities.
Foundational support includes basic enablement like turning on Joule and providing learning journeys. Advanced includes embedded AI deployment across SAP’s cloud portfolio. Max is for organizations ready to define a custom AI strategy, including co-developed prototypes.
SAP is preparing its services to support customers at varying stages of AI maturity: something most implementation partners will need to reflect in their own offerings. Consultants who can translate between AI tooling, business process value, and executive-level strategy will be the ones best positioned to lead these engagements.
New data services were also introduced, focused on supporting Business Data Cloud adoption. These services include discovery workshops, assessments, and prescriptive guidance aimed at harmonizing enterprise data models.
The keynote closed on a note that combined inspiration and pragmatism.
The familiar proverb,”The best time to plant a tree was 20 years ago. The second-best time is now”, served as a metaphor for transformation readiness.
The message was that with the available tooling, customer examples, and evolving support models, the conditions for transformation are already available and rapidly maturing.
This keynote provided a window into how clients are actually working through transformation: through continuous, feedback-driven reconfiguration. It also clarified that SAP’s strategy is not to push AI for its own sake, but to embed it in a way that makes the existing landscape more navigable, more governable, and more productive: moving from complex and fragmented systems to clarity and coherence.
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