Trusted sustainability data is becoming one of the most valuable assets an enterprise holds. It shapes investor confidence, influences access to capital, and increasingly steers the decisions that determine long-term resilience. That shift is being accelerated globally by the IFRS® Sustainability Disclosure Standards, IFRS S1 and IFRS S2, now being adopted across more than 40 jurisdictions representing roughly 60% of global GDP.

As they take hold, organizations are expected to produce sustainability information that is as accurate, traceable, and decision-useful as their financial information. Sustainability reporting, in short, is becoming finance-grade, and the organizations that treat it that way will be the ones that turn disclosure into an advantage.

The challenge: establishing trusted sustainability data

The pressure to disclose has not eased. According to PwC’s Global Investor Survey, more than 70% of investors say sustainability must be integrated into corporate strategy. Sustainability data, in other words, is now central to safeguarding enterprise value.

For most organizations, the challenge is establishing a trusted data foundation that can support reporting, assurance, performance management, and decision-making at enterprise scale.

Too often, sustainability data remains fragmented across systems, functions, and geographies. Many companies still rely on disconnected processes and manual reporting, even as assurance expectations rise. EY’s 2024 Global Corporate Reporting Survey found that 96% of finance leaders have concerns about the integrity and reliability of their organization’s non-financial data.

Reporting can no longer sit within a single function. Finance, sustainability, operations, procurement, and risk teams must work from a common, governed foundation. And with some organizations reporting against IFRS S1 and S2 for the first time, while others must now map IFRS S1 and S2 requirements onto existing European Sustainability Reporting Standards (ESRS) or Global Reporting Initiative (GRI) disclosures, building a separate process for every framework only multiplies effort, cost, and complexity.

This is a data foundation problem, and it is where SAP is positioned to help.

How SAP helps organizations meet IFRS S1 and IFRS S2

SAP provides a sustainability suite that helps take organizations from compliance obligation to business value, spanning ESG frameworks and regulatory requirements while embedding sustainability insight into operations and business models.

At its center, SAP Sustainability Control Tower can serve as the single-entry point for audit-ready ESG reporting and sustainability performance management. It helps organizations manage disclosures across IFRS S1 and IFRS S2, ESRS, and other frameworks from one governed foundation that connects sustainability, financial, and operational data. With SAP-provided IFRS S1 and IFRS S2 metrics available within the solution, organizations can reduce manual effort and strengthen reporting confidence. 

SAP Sustainability Footprint Management complements this by helping to calculate the emissions, energy, and environmental data relevant to IFRS S2 climate disclosures and other ESG reporting frameworks. Crucially, it draws on the same ERP data that runs finance, supply chain, and operations, grounding footprint calculations in verified business transactions rather than estimates or manual inputs.

The principle is configure once, report across frameworks. Emissions and energy data calculated in SAP Sustainability Footprint Management, together with master data configured once in SAP Sustainability Control Tower, can serve multiple disclosure obligations. Because IFRS S2 and ESRS E1 are highly interoperable for climate disclosures, a single data-collection scope can serve both. And as reporting requirements expand globally, SAP continuously evaluates regulatory developments and makes the most relevant frameworks available out of the box, so organizations can scale as requirements grow and stay focused on performance and outcomes. For IFRS S1/S2 jurisdiction-specific requirements, SAP’s partner ecosystem is well positioned to extend these capabilities to address local reporting needs.

AI extends this further. The Sustainability Regulatory Readiness Agent helps translate materiality assessment outcomes into reporting-scope decisions, while the SAP Sustainability Control Tower AI-assisted ESG report generation capability can generate structured, complete report drafts from validated metrics already in the system. Teams retain full control to review, refine, and finalize before publication, so organizations can scale efficiently while maintaining governance, transparency, traceability, and human oversight.

We see this in what our customers are doing. KNAPP AG, a value chain technology leader based in Austria, transformed its sustainability reporting with SAP Sustainability Control Tower and SAP Sustainability Footprint Management, implemented with KPMG Austria. Integrating about 200 to 250 metrics, the company completed its first round of CSRD reporting well ahead of the 2027/2028 mandate. 

As Bernhard Bischof, solution reporting architect at KNAPP AG, put it: “Through our collaboration with SAP and KPMG, we are able to realize a resource-efficient and automated approach to sustainability reporting. We rely on innovative software solutions, in particular SAP Sustainability Control Tower and SAP Sustainability Footprint Management, to make our reporting efficient and sustainable.”

As organizations expand reporting beyond CSRD to include IFRS S1 and S2, the same trusted sustainability data foundation can help reduce duplication, improve consistency, and support more efficient reporting across frameworks.

From audit-ready reporting to performance management

With audit-ready ESG reporting as the starting point, the best value is derived from what trusted data enables beyond disclosure: understanding actual performance, identifying where action is needed, and making sustainability a genuine input to business decisions.

That value shows up across the organization. Trusted sustainability data strengthens governance and risk management, supports investor confidence and transparency, improves business steering, and shapes access to finance, cost of capital, and long-term resilience. KPMG’s ESG Assurance Maturity Index 2025 found that 60% of CSRD Wave 1 companies expect ESG assurance to expand their market share or client base.

SAP Sustainability solutions help move organizations from reactive reporting to proactive performance management. Embedded initiatives can turn strategy from a set of intentions into a portfolio of tracked, measured, and accountable actions, each linked to the metrics and targets that define an organization’s ESG commitments. With that foundation in place, sustainability becomes embedded in enterprise processes rather than a stand-alone reporting activity, applied where decisions are made rather than as a downstream task. This is the foundation of SAP’s vision for the Autonomous Enterprise, where sustainability is embedded in the decisions that run the business.

What organizations should do now

Two priorities stand out for leaders today. First, build a trusted sustainability data foundation, with governance, traceability, and auditability established from the start. Second, prepare to report across multiple frameworks and jurisdictions from one common foundation, rather than building parallel processes for each.

Organizations that establish trusted sustainability data foundations today will be better positioned to meet IFRS Sustainability Disclosure Standards, strengthen governance, support investor confidence and access to capital, and create long-term business value.

For more information, visit: www.sap.com/products/scm/sustainability-control-tower

Gunther Rothermel is SAP Sustainability chief product officer.

Today, most companies are experimenting with AI. Many of them can point to demos that impressed, pilots that worked, and tools that saved time in narrow tasks. Far fewer can say AI has changed their business across functions, processes, and teams. 

The difference is not the model. It is context: the ability for AI to understand how a business actually runs. 

Much of today’s AI discussion centers on agents, along with models and benchmarks. Which model performs best? Which system completes the most tasks? Which interface feels most natural? These factors matter, but they do not solve the central enterprise challenge.

Companies run workflows that cut across teams, policies, approvals, authorizations, and data. They plan, source, produce, hire, pay, and serve through systems that carry real business consequences. AI only creates durable value at scale when it operates inside this reality.

Models generate answers. An agent can complete a task. But running a business requires something more. It requires an understanding of how work gets done, who is authorized to act, which rules apply, and how decisions connect across functions. Without that context, AI simply can’t deliver on its promise.

That is one reason I believe AI raises the premium on software with deep business context. It allows companies to fundamentally reinvent how work gets done. When AI agents understand end‑to‑end processes, they can operate across functions, execute workflows autonomously, and coordinate actions in real time. Instead of automating individual steps, AI can run processes end to end, freeing employees from repetitive coordination and enabling them to focus on higher‑value judgment, oversight, and strategy.

This is what we describe as the Autonomous Enterprise, a fundamental shift from systems of execution to systems that can reason, decide, and act. A vision where SAP is poised to lead. 

For more than five decades, we have powered the core processes that run the world’s leading organizations. Our systems don’t just store data; they encode how businesses actually operate: their processes, rules, and decisions. Our ERP is the institutional memory and the brain of many companies across industries and around the globe. Our new SAP Business AI Platform brings together enterprise data, processes, and governance into a unified context for AI.

Building on this foundation, Joule is the interaction layer that connects people with AI and redefines how they interact with software. Joule Assistants collaborate with users, while Joule Agents execute business workflows end to end. This is how intelligence becomes embedded directly into operations, not added on top. We call this the SAP Autonomous Suite.

“Show me how my financial forecast for the year could change based on the latest pipeline and supply chain data.” On the surface, this looks like a simple prompt directed to a large language model. But disconnected from enterprise systems, the answer is mere speculation.

Grounded in the full context of the business, the system first identifies the correct business process from hundreds of mission‑critical processes and understands the specific configuration that governs how this process runs in your organization. It then selects exactly the right data from millions of data fields stored across the ERP landscape. Finally, every step is checked against identity, authorization, and access controls, ensuring the result is accurate, compliant, and trustworthy. This is how enterprises move beyond generic, probabilistic answers toward decisions they can rely on.

Reaching this state requires more than adding a chatbot or layering AI on top of existing systems. Many enterprises still operate with fragmented landscapes, data spread across systems, and processes shaped by years of incremental change. In this environment, AI cannot simply be “bolted on” or layered onto fragmented, outdated systems. It does not accelerate progress. It amplifies inefficiency and risk. Companies must rethink how their processes, data, and infrastructure work together and how humans and AI share responsibility. This is not only a technical shift. It is a change‑management challenge. 

New technology only creates value when it is accompanied by real change. AI does not replace transformation. It raises the return on transformation done well. And it comes to life only when every element of the system—the agent, the process, and the human—works together by design. People need to understand how to work with AI agents, and processes must be intentionally shaped to embed intelligence where decisions and execution happen.

This is why change management is foundational. It means reskilling employees, re‑engineering processes to connect them directly with data and AI, and modernizing the underlying landscape. 

That is why we are introducing new AI-led RISE with SAP and SAP GROW offerings and fundamentally resetting our services model: to help companies modernize, navigate change, and turn AI from potential into sustained business value at their own pace. 

This marks the beginning of a new era of enterprise software: where intelligence is not separate from operations but embedded within them. The companies that lead will not be those with the most advanced models in isolation, but those that connect AI to the way their business actually runs—with context, governance, and trust. 

This is the dawn of the Autonomous Enterprise, and SAP is uniquely positioned to help the world’s leading organizations realize its full potential. 

Christian Klein is CEO of SAP SE.

Finance leaders are under mounting pressure to make faster, smarter decisions, but the environments they operate in no longer move in predictable cycles.

Market volatility, liquidity pressures, and currency fluctuations are exposing the limits of traditional planning models built around fixed timelines and after-the-fact analysis. To keep pace, finance teams need the ability to continuously sense change, understand its impact, and steer performance with confidence.

The challenge is that many organizations are still planning with processes designed for a different era. Siloed data, manual workflows, and episodic planning cycles make real-time decision-making difficult, limiting visibility across the entire business. IDC research reinforces the urgency: 72% of organizations still find financial planning, budgeting, and forecasting too time-consuming.* In a volatile environment, that lag translates directly into slower responses to risk, missed opportunities, and diminished confidence in the decisions that shape performance.

This is why finance needs a new operating model, one that moves beyond periodic exercises and toward continuous steering. At SAP Sapphire, we are introducing SAP Enterprise Planning, a new flagship offering designed to close the gap between insight and action, enabling planning to continuously drive business performance.

The shift from periodic planning to continuous steering

Traditional financial planning has always provided structure, but too often that structure comes at the expense of agility. Planning occurs in fixed windows. Teams work from historical snapshots, static assumptions, and fragmented inputs. By the time a variance is understood or a scenario is modeled, the business may already be operating in a fundamentally different environment.

SAP Enterprise Planning is designed to move organizations beyond these constraints through a continuous approach to planning and execution built on speed, confidence, and control. Finance teams gain the ability to detect signals as they emerge, evaluate constraints in real time, and connect plans directly to execution.

This Sense-Reason-Act model represents a fundamental shift in how planning operates. Rather than waiting for a planning cycle to surface issues, agents continuously monitor for material changes and respond through guided, explainable decisions embedded in everyday processes. At the same time, SAP Analytics Cloud continues to support the iterative Plan-Do-Check-Act cycles that finance teams rely on for strategic and tactical planning across mid- to long-term horizons, including model creation, forecasting, variance analysis, and scenario simulation. Together, these two approaches create a planning ecosystem that is both responsive in the moment and disciplined over time.

The solution embeds Joule Agents directly into the planning process, helping connect strategy to operations in real time. Agents can interpret internal and external data signals, model their impact on KPIs, simulate scenarios, recommend actions, and orchestrate planning workflows with built-in governance and explainability. Planning shifts from a single point in time to continuous workflows. When decisions are made, Joule Agents can update plans to support downstream execution. General availability is planned for Q3 2026.

Built on SAP Analytics Cloud and SAP Business Data Cloud, these capabilities form a more connected, intelligent planning ecosystem that enables organizations to act decisively and with full transparency.

Why governed data and connected planning matter

Continuous planning is only as reliable as the data it is built on. Without a unified data foundation, even the most advanced analytics cannot produce trustworthy outcomes. As automation increases, this challenge becomes more acute: decisions execute faster, but errors can scale just as quickly.

That is why our approach is not AI in isolation. SAP Enterprise Planning is built using SAP Business Data Cloud data products and the SAP Analytics Cloud solution. SAP Analytics Cloud remains the foundation for strategic and tactical planning cycles, while SAP Business Data Cloud provides the governed data foundation underpinning the entire ecosystem. This helps ensure compliance, auditability, and enterprise-wide trust, which becomes even more critical as AI-driven automation expands.

Continuous planning in practice

What makes this vision tangible is how it shows up in real financial workflows. By continuously monitoring market signals and financial positions, these solutions help organizations reduce the lag between insight and action, improving both speed and decision quality. This is the Sense-Reason-Act model at work: sensing shifts in currency markets, reasoning through the impact on cash positions, and acting through guided decisions that keep the business aligned with its financial objectives.

More broadly, the Autonomous Finance domain brings together Joule Assistants and Joule Agents to provide CFOs and finance organizations with more insight, control, and support across their operations. Beyond planning, specialized Joule Assistants coordinate multiple agents to support key finance processes including financial closing, billing, governance, and tax and compliance. The result is a finance function where intelligence is embedded across the full operational scope, not confined to a single workflow.

Because these agents are delivered within SAP’s planning and finance solutions, they carry a native understanding of enterprise data, planning semantics, and mission-critical business processes. The goal is not to replace finance expertise, but to augment it. This gives teams the foresight needed to navigate complexity with greater confidence.

The Autonomous Finance capabilities run across our cloud ERP application portfolio, including SAP Cloud ERP Private, for end-to-end coverage across business processes and systems.

The future of finance is continuous

The future of finance will be defined by the ability to connect data, processes, and decisions across the enterprise in a continuous loop. Organizations that can sense change as it happens, reason through its impact using trusted and governed data, and act by connecting plans back to execution will be best positioned to navigate volatility with the agility and discipline that modern finance demands.

With SAP Enterprise Planning, organizations can move beyond static planning cycles and toward a more intelligent, continuous approach to steering performance.

For more details, refer to the SAP Sapphire Innovation News Guide and the Financial Planning and Analysis area of sap.com.

Lawrence Martin is chief product officer and head of Public Cloud Engineering at SAP.
David Imbert is head of Finance Product Marketing at SAP.

*IDC Spotlight, sponsored by SAP, The Rise of Dynamic Planning in the Agentic AI Era, #US54493826, April 2026