Data Before Deployment: What the PwC and Palantir Alliance Signals for SAP Transformation

PwC US and Palantir expanded their strategic alliance on September 3, 2026, to target three priority areas: scaling enterprise AI, transforming mergers and acquisitions, and modernizing ERP. For the SAP community, the latter deserves the closest reading. PwC and Palantir describe their ERP work as addressing “one of the biggest sources of risk in ERP transformation: getting the data right before implementation.”

That framing matters because it inverts the traditional sequence. Data cleansing has long been treated as a workstream inside the migration, but the alliance positions it as the gate before the migration starts.

Why Data Readiness Is Now the ERP Risk That Counts

The alliance combines PwC’s SAP expertise with Palantir’s AI Platform to identify process inefficiencies, improve data quality, and assess transformation decisions earlier, with telecommunications, utilities, and consumer products named as early focus industries. The stated goal is a faster, more predictable path to SAP transformation and a stronger foundation for AI-driven innovation.

SAPinsider’s own data supports the emphasis. In the ERP Migration and Transformation 2026 benchmark, 75% of respondents rated cleansed and harmonized operational data across systems as important to their SAP S/4HANA plans. The report also singles out data cleansing tools as a growing priority as organizations prepare to run AI inside ERP. Additionally, the research exposes how far execution lags intent: 55% of organizations report having deployed SAP S/4HANA or SAP S/4HANA Cloud, yet only 34% have fully transitioned. Parallel landscapes and unresolved data are a large part of that gap.

Jennifer Colapietro, US Digital Core Modernization Platform Leader at PwC, put the underlying discipline plainly when she spoke with SAPinsider at SAP Sapphire 2026: “Organizations struggle the most when they try to preserve legacy processes instead of simplifying and standardizing them.” Bringing dirty data and fragmented processes into a new platform is the same mistake in a different form.

AI Is Now the Reason to Migrate, and Why Migrations Must Not Break

For years, the 2027 end-of-maintenance deadline drove SAP S/4HANA decisions. However, in the 2026 SAPinsider benchmark, 43% of organizations cited SAP’s AI announcements as the primary external factor shaping ERP strategy, ahead of the deadline at 39%.

Yet ambition is outrunning readiness. SAPinsider’s June 2026 research on AI-driven process transformation found that 74% of SAP customers still have AI-enabled SAP use cases in the identification, experimentation, or no-plans phase, while 63% name accuracy and reliability of AI outputs in critical processes as their top concern and 59% worry about data leakage through AI services. Earlier SAPinsider research on AI adoption and maturity found that 79% of respondents rank access to high-quality, trusted data as a top requirement for scaling AI, tied with executive sponsorship.

The alliance expansion between Palantir and PwC argues that AI’s greatest opportunity isn’t in isolated use cases; the real value lies in changing how enterprises operate. Colapietro made the SAP-specific version of that case: “The companies getting the most value from SAP S/4HANA are treating it as the foundation for an intelligent, AI-enabled enterprise, not simply a modernization project, because clean processes, trusted data, and that concept of simplified operations are what really ultimately unlock automation and AI at scale.”

An Ecosystem Model, Not a Two-Player Deal

The Palantir expansion is also a concrete example of a shift Patrick Pugh, Global & US Alliances Leader at PwC, described to SAPinsider in June. “The world has evolved beyond a model where PwC and SAP alone can tackle these challenges,” he said. “Our ability to orchestrate across hyperscalers, other ISVs, data partners, and frontier players is the only way to solve the complex problems that, candidly, no single organization can address on its own anymore.”

The alliance points to measurable outcomes from earlier joint work, including up to 10% supply chain operating efficiency for a food manufacturer and 90% to 95% forecasting accuracy for a grocery retailer. While those are credible proof points, the harder question for SAP customers is architectural. When a third-party data platform sits alongside SAP Business Data Cloud and SAP BTP, who owns the semantic layer, the authorizations, and the audit trail? SAPinsider’s research shows 49% of respondents rank role-based access control aligned with SAP authorizations as the single most important AI security control. Any external platform touching SAP data will be judged against that standard.

Colapietro’s warning is the right closing frame: “Technology alone is not going to create the transformation. It’s really the operational discipline that will.”

What This Means for SAPinsiders

Move data readiness ahead of the migration gate. With 75% of organizations rating harmonized data as critical and only 34% fully transitioned, according to SAPinsider research, ERP program managers should fund data profiling, cleansing, and process discovery as a distinct pre-implementation phase with its own exit criteria, whatever tooling delivers it.

Write the business case around AI outcomes, then test whether the data can support them. Since AI announcements now outrank the 2027 deadline as a migration driver, CIOs should name the specific AI use cases the program must enable and verify, before go-live, that the underlying data meets the accuracy bar.

Pressure-test every ecosystem partner on SAP governance. Following Pugh’s orchestration model, enterprise architects should ask how any non-SAP data or AI platform inherits SAP authorizations, where the governed semantic layer lives relative to SAP Business Data Cloud, and how decisions made outside the core will be audited inside it.