HR leaders often worry about moving too fast—embracing new trends, over-investing in new technology, or introducing more change than the organization can absorb. But a new business value study from IDC sponsored by SAP*, based on organizations using SAP SuccessFactors solutions to run core HR, time, and payroll, points to a different risk altogether: fragmentation. And not only as an operational inefficiency, but as a fundamental barrier to realizing the full potential of AI in HR.

Across many enterprises, HR, time, and payroll systems have evolved through years of growth, acquisitions, and regional customization. The result is a patchwork of disconnected tools, duplicated data, and manual handoffs that quietly slow decision-making and increase operational risk. These systems may still “work,” but they carry a hidden cost on productivity, accuracy, and confidence, as expectations on HR continue to rise and AI becomes central to how work gets done.

Fragmentation is the hidden bottleneck behind “slow” decisions

The impact of fragmentation isn’t always visible, but it shows up clearly in how decisions get made.

When decisions stall, leaders often point to approvals, governance, or external constraints. In reality, much of the friction happens earlier, when teams reconcile data across systems before decisions can even begin.

According to the research, organizations with unified HR foundations gained faster access to trusted workforce information, generating insights 60% faster and creating new position listings 53% faster. Rather than adding tools, these organizations removed friction by eliminating manual validation, shadow spreadsheets, and repeated checks to confirm data accuracy.

As organizations look to AI to accelerate workforce planning, surface risks, and guide decisions, this foundation becomes even more critical. AI is only as effective as the data it can access and trust. In disconnected environments, AI inherits the same inconsistencies, delays, and gaps, limiting its ability to generate reliable insights and recommendations.

Consider a simple workforce planning decision like headcount approval. In a fragmented environment, HR pulls data from one system, finance validates it in another, and managers reconcile discrepancies in spreadsheets. What should take hours stretches into days—not because the decision is complex, but because the data is.

With real-time, consistent workforce information, leaders can act faster and with greater confidence in their decisions. More importantly, unified data allows AI to move beyond reactive reporting to deliver proactive, decision-ready intelligence.

Most payroll errors aren’t human—they’re structural

Disconnected systems don’t just slow work; they also increase errors.

When employee data, time records, and payroll information live in different places, every handoff becomes an opportunity for mistakes. Manual reconciliation and corrective actions become routine, especially during high-pressure cycles like payroll close.

Organizations with unified platforms see a clear shift. Payroll error rates drop by 64% and payroll cycles are completed 44% faster by eliminating data gaps and automating validation across connected processes.

This is where AI begins to shift from reactive to preventative. With unified data, AI can identify anomalies before payroll runs, flag potential compliance risks, and continuously learn from patterns across the organization. Instead of fixing errors after the fact, HR and payroll teams can prevent them altogether.

That structural shift changes the nature of work for HR and payroll teams. Payroll teams saw a 21% productivity increase, while HR teams improved productivity by 14%, as time previously spent tracking down discrepancies, correcting entries, and responding to escalations was redirected toward oversight, compliance, and continuous improvement.

Fragmentation quietly erodes trust and limits AI adoption

When systems are fragmented, trust erodes quietly. Employees lose confidence when pay errors occur or self-service tools don’t reflect their reality. Managers hesitate to act when dashboards conflict. HR teams become intermediaries between systems rather than strategic partners to the business.

Integrated HR, time, and payroll systems reverse this dynamic. Employees gain easier access to self-service tools, with 28% more employees able to directly access HR and time entry platforms. Managers benefit from real-time visibility into approvals and team data. And HR teams regain credibility as the source of accurate, timely workforce information.

Over time, this trust compounds. When people trust the system, they use it. Increased usage improves data quality, and better data strengthens decision-making.

This foundation becomes even more important as organizations scale AI across HR. Employees and managers are far more likely to rely on AI-driven recommendations—whether for career growth, scheduling, or compensation—when they trust the underlying data. Without that trust, even the most advanced AI capabilities remain underutilized.

Fragmentation doesn’t just slow execution—it narrows what leaders believe is possible, forcing decisions to be shaped by system constraints rather than business needs.

The cost of standing still

The cost of fragmentation isn’t just operational; it’s financial, and it compounds over time.

Across organizations studied, the average annual quantified benefit totaled US$649,400 per 1,000 employees supported, driven by productivity gains, reduced errors, faster cycles, and better business decisions. Over three years,organizations achieved a 284% return on investment, with a payback period of approximately 15 months.

Beyond these quantified gains, there is a growing competitive gap. Organizations operating on unified platforms are not only more efficient, but they are also better positioned to embed AI across the entire employee lifecycle, from hiring and onboarding to development and workforce planning. Those still operating with disconnected systems risk falling behind—not just operationally, but strategically.

The real risk isn’t innovation

Innovation draws attention because it’s new, visible, and often disruptive. Fragmentation, by contrast, builds quietly in the background until it starts to limit how the organization operates. But as organizations ask HR to deliver more—better insights, faster planning, stronger compliance, and improved employee experiences—the limits of disconnected systems become harder to ignore.

Modern HR outcomes don’t come from layering new tools on top of outdated foundations. They come from reducing complexity, unifying data, and creating consistency across the most essential people processes. This is where platforms like SAP SuccessFactors are evolving—not just to unify core HR, time, and payroll, but to embed AI directly into the flow of work. By combining a trusted data foundation with AI-driven insights and automation, organizations can move from reactive operations to predictive, insight-led workforce management.

The question isn’t whether organizations can afford to modernize HR. It’s whether they can afford to limit the impact of AI by building on fragmented foundations.

AI doesn’t transform HR on its own; it amplifies what’s already there. And without a unified, trusted core, even the most advanced AI will struggle to deliver on its promise.

Learn how leading organizations are reducing fragmentation and building a strong foundation for AI by unifying core HR, time, and payroll with SAP SuccessFactors.

*IDC Business Value White Paper Sponsored by SAP, The Business Value of SAP SuccessFactors Core HR, Time, and Payroll Solutions, #US53971225-BVWP, January 2026.

Lara Albert is chief marketing officer for SAP SuccessFactors.

NEW ORLEANS — SAP SE (NYSE: SAP) today announced new AI-enabled capabilities, travel and expense management enhancements, and new and expanded partnerships at SAP Concur Fusion 2026, the flagship conference for SAP Concur solutions users and experts.

SAP is expanding the Joule solution across SAP Concur solutions and introducing new automation capabilities:

• A new integration between Joule and Microsoft 365 Copilot, now available, embeds travel and expense tasks into everyday productivity tools. Employees can create and submit expense reports, upload receipts, book travel and receive policy guidance in SAP Concur solutions without leaving Microsoft applications.
• Two new Joule Agents further streamline expense compliance and reporting.
  • Expense Automation Agent automatically creates and populates expense reports for employees so all they have to do is review, refine and submit.
  • Expense Pre-Submit Audit Agent validates receipts and flags discrepancies before submission to reduce report rejection and reimbursement delays.
  • Both agents are currently available through the SAP Early Adopter Care program with general availability expected later this year.
• New AI-based rule creation tools simplify the complex task of managing policy rules in the Complete by SAP Concur and Amex GBT, Concur Travel and Concur Expense solutions.
• The SAP Sales Cloud solution now integrates with Booking Agent to streamline workflows and enhance productivity for sales teams.

SAP Concur and American Express Global Business Travel (Amex GBT) announced new innovations to Complete, an AI-enabled codeveloped solution for booking, servicing, payments and expensing. New capabilities include AI-enabled travel support with handoff to a live travel counselor and a specialized home page for travel managers. Concur Expense also integrates with Amex GBT Egencia for customers worldwide.

Joint customers of SAP Concur solutions and American Express can now create and manage American Express Virtual Cards in Concur Expense, supporting employee spending with controls and added security. The virtual cards can also be used in Concur Travel. This capability is available now to select U.S.-based American Express® Corporate and Business customers using Concur Expense with availability for all such customers planned for Q3 2026.

SAP Concur teams up with Visa to integrate Concur Expense and Visa through the Visa Commercial Integrated Partner program. Initially, real-time notifications (RTN) from Visa card swipes will automatically create expenses in Concur Expense. This capability is planned to be available through SAP Early Adopter Care in Q3 2026. SAP Concur solutions will now support RTN from all major credit card networks.

Additionally, SAP Concur solutions are advancing corporate travel with enhanced booking, expanded global access and intelligent traveler support. The new experience in Concur Travel supports guest bookings, expanded Cleartrip content in India and additional airline options. TripIt Pro adds Image to Plan with Apple Intelligence and expanded Risk Alerts to help travelers organize itineraries and monitor disruptions.

Learn about these announcements at SAP Concur Fusion or join the virtual event. 

Visit the SAP News Center. Get SAP news via LinkedIn and Bluesky.

Media Contact:
Kelly Sheldon Murray, +1 (978) 708-6821, kelly.murray@sap.com, ET

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SAP introduces SAP Cloud ERP Private 2025 FPS01. Designed to turn complexity into clarity, FPS01 builds on the landmark 2025 release from October, advancing AI innovations, delivering industry-ready data products, and further strengthening the core to help enterprises navigate today’s global operations.  

A modern foundation for growth at global scale 

In an era defined by global volatility and ambitious growth targets, businesses require a system that doesn’t just record data but actively anticipates needs and simplifies complexity. SAP Cloud ERP Private is evolving into a truly AI-enabled ERP, serving as the critical core foundation that can allow organizations to navigate the realities of global operations while maintaining total control over their footprint. 

To achieve this, innovations in FPS01 are strategically delivered across three key dimensions: AI, data, and applications. 

AI in action: from assistants to agents 

The shift toward an AI-enabled ERP is highlighted by two key advancements in FPS01: 

1. AI assistants and specialized agents: A standout in this release is the Change Record Management Agent for R&D. Previously a manual, high-friction process, this agent can now autonomously analyze change impacts and propose next steps, helping to free R&D teams to focus on innovation. 
2. Process embedded AI: SAP is making the system more intuitive through Joule. Instead of navigating complex menus, users can now use conversational shortcuts, for example, to instantly search service contracts or extend expiring prices in sales, turning multi-minute tasks into five-second interactions. 

Looking at the road ahead, SAP is building toward agent-to-agent collaboration, where specialized agents across functions like R&D and procurement “talk” to one another to resolve bottlenecks before they even reach a human user. FPS01 is a critical step toward that future. 

Data: industry-ready insights 

On the data front, SAP is introducing specialized data products for key industries, like retail, and functional areas, such as asset management and services. These are not just tables; they are pre-configured, business-ready data sets that align with our SAP Business Data Cloud (SAP BDC) roadmap. This helps ensure your data is “AI-ready,” allowing you to move from raw data to industry-specific insights with zero friction. 

Application: strengthening the global core 

On the application side, SAP continues to deliver deep functional enhancements based on direct customer feedback to help ensure your business backbone remains agile. A key highlight is the new Multistage Intercompany Sales and Stock Transfer. Following our commitment at the RISE with SAP moment in November, SAP is further expanding the scope to cover two-entity transfers, enabling automated orchestration across multiple legal entities. This can ensure even the most complex global supply chains remain transparent and compliant. 

A full collection of deep-dive articles on the new FPS01 is available on SAP Community. 

Looking ahead: your catalyst for transformation 

FPS01 reflects a core SAP principle: innovation should be both a foundation for today and a catalyst for what’s next. With enterprise AI, industry-ready data, and a stronger application core, organizations can run smarter and transform at their own pace. 

To see these innovations in person, register for SAP Sapphire to experience the future of the autonomous enterprise. 

Maura Hameroff is chief marketing officer for SAP Cloud ERP Private and RISE with SAP.

The clear message for retailers attending National Retail Federation’s 2026 Big Show in New York last week was that they need to urgently address the challenge brought about by the rapid adoption of generative AI tools by consumers and update their back-office and data systems if they are to thrive in the agentic commerce era.

Agentic AI was everywhere at NRF, emblazoned across the booths of technology exhibitors and the focus of many of the daily conference sessions. The message was simple: retailers face a major upheaval as consumers switch from traditional browser-based search to AI-enabled product discovery.

Consumers are rapidly adopting AI agents to help them find, compare, and, increasingly, buy products—this while many brands are still optimizing for search engines and are quietly disappearing from the models driving the next generation of product discovery.

“Agentic commerce—shopping powered by AI agents acting on our behalf—represents a seismic shift in the marketplace,” McKinsey, the strategic management consultancy, noted in a report published late last year. “It moves us toward a world in which AI anticipates consumer needs, navigates shopping options, negotiates deals, and executes transactions, all in alignment with human intent yet acting independently via multistep chains of actions enabled by reasoning models.”

This, as speakers and panelists at the NRF conference acknowledged, isn’t just an evolution of e-commerce; it’s a rethinking of shopping itself, in which the boundaries between platforms, services, and experiences give way to an integrated, intent-driven flow through highly personalized consumer journeys that deliver a fast, frictionless outcome.

As the McKinsey report noted, the stakes are high. By 2030, the U.S. B2C retail market alone could see up to US$1 trillion in orchestrated revenue from agentic commerce, with global projections reaching as high as $3 trillion to $5 trillion.

This means all the participants in the retail chain, from brands and retailers to logistics and payment service providers, will need to adapt to the new paradigm and successfully navigate the challenges of trust, risk, and innovation.

To help retailers address the immediate challenges posed by the shift to agentic commerce, SAP argues that three steps are necessary: first, restructuring web-page product data to be machine-readable; second, adding semantic summaries for LLM reasoning; and third, tagging products by the problems they solve, not just their attributes.

SAP announced a series of AI-enhanced retail innovations at NRF 2026, including a new storefront model context protocol (MCP) server that enables retailers to make their digital storefronts intelligible to AI and the new AI-native Retail Intelligence solution in SAP Business Data Cloud that leverages data from across SAP software and third-party systems to help provide accurate demand planning, improved forecast accuracy, and lower inventory costs to drive more seamless omnichannel engagements.

SAP Customer Experience has also unveiled a Digital Service Agent recently that can be combined with the Shopping Agent, creating one conversational AI that can handle the entire journey from product discovery and transaction to post-sales support.

These moves reflect a recognition that that LLMs have become a legitimate shopping channel, and that product discovery is moving from search engines to AI recommendations.

This shift challenges years of SEO and brand building. To stay relevant, SAP believes retailers must take an AI-first approach and have strong, connected data that helps agents understand products, predict demand, and respond quickly. Without this strong data foundation, brands will be at risk because if customers get poor recommendations and errors in pricing, trust can disappear fast.

Although some early agentic AI adopters in the retail sector are already seeing the benefits of agentic commerce, many global retailers are still ill-prepared for the holistic transformation they need to succeed in this new retail environment.

As McKinsey noted in a separate report published to coincide with NRF, “while most retail merchandising teams have invested in automation tools and experimented with AI, 71% of merchants say that AI merchandising tools have had limited to no effect on their business so far.”

“The challenge,” McKinsey said, “often lies less in the technology than in how it’s integrated and used. Systems remain fragmented, data is too messy to use to deliver useful recommendations, and adoption is uneven: 61% of respondents say that their organization isn’t at all or is only slightly prepared to scale AI across merchandising.”

Onstage at NRF, Andre Bechtold, president for SAP Industries & Experience, also emphasized that retailers should prepare now for agentic commerce and noted that simply “bolting on” AI tools to existing systems is not enough.

“Retailers are operating in an environment defined by volatility—tariffs, margin pressure, supply chain disruption, and customers that expect real-time, hyper-personalized experiences everywhere,” Bechtold said during a discussion with Gymshark, the workout apparel retailer. “At the same time, boards and investors are asking a tougher question than ever before: what outcomes are we actually getting?”

“The challenge,” he said, “isn’t a lack of innovation. In fact, most retailers have plenty of tools, pilots, and point solutions. The real issue is that disconnected technology doesn’t translate into resilient growth. That’s why the conversation is shifting. It’s no longer about isolated AI use cases or shiny new features. It’s about whether AI and data are embedded across the business—connecting supply chains, finance, merchandising, and customer engagement—in ways leaders can trust.”

Echoing the same point, Thomas Saueressig, member of the Executive Board of SAP SE, Customer Services & Delivery, commenting in a Handelsblatt article this week about a PwC survey of global CEOs that found that companies rarely achieve lower costs or higher sales through the use of AI, emphasized that AI only contributes value when consistently embedded in business processes.  “As long as AI runs alongside the core business as an isolated project, the effects remain limited,” he said.