This week at SAP TechEd, SAP introduced a range of solutions focused on AI governance. While the solutions address different dimensions of governance in the era of AI, they all reflect the same basic principles:

• Build on proven business controls: You already have governance standards and practices in place. AI governance should connect to and extend these controls.
• Adopt innovation with confidence: The approach to governance we advocate is the same publicly available and documented approach we use to develop, deploy, and govern the solutions and services we deliver.
• Stay in control as your business grows: The controls and standards you have in place should not only promote AI adoption, but also enable you to assess costs, risks, and value as adoption increases.

Since the advent of this new world of autonomous technology, people have endeavored to identify the most impactful application of it. As the path to value realization has become clearer, a new challenge has emerged: ensuring both that AI usage does not lead to unintended and potentially harmful consequences and that this usage remains compliant with emerging regulatory regimes.

By adhering to the principles outlined above, SAP makes it possible accomplish both ends. More importantly, as we showed at SAP TechEd, SAP also provides the solutions necessary to govern, control, and innovate now and into the future. 

AI governance announcements from SAP TechEd

Here’s what we talked about at SAP TechEd on the AI governance front.

True AI governance isn’t about figuring out if policies and rules have been followed after the fact; it should be about making sure governance is applied when it matters. SAP Enterprise AI Gateway ensures this kind of proactive governance by consolidating authentication, policy enforcement, and routing at runtime, while also allowing for continuous monitoring, usage tracking, and auditing. The gateway thus controls traffic across MCPs, APIs, agent-to-agent connections and LLMs. Building on SAP Integration Suite, the gateway consolidates and streamlines real-time oversight and control over AI in action.

As a compliment to the gateway, we also announced customer access to curated SAP Sovereign Cloud LLMs directly through  SAP AI Core. This allows customers to use these LLMs in critical processes while adhering to established governance standards. What’s more, by allowing direct access on SAP Sovereign Cloud, customers can reduce both cost and complexity in AI operations.

Being able to provide agents with the architecture context they need to operate effectively is also essential to the control of agent behavior. At SAP TechEd, we described new features in the SAP LeanIX portfolio enabling enterprise architects to control the architecture data Joule Agents use to make and execute decisions.

This architecture context feature relies on a knowledge intake agent to extract relevant information from security and architecture decision documents, as well as propose connections to the SAP LeanIX knowledge graph, and submit all data for human approval before making it available to agents.

Finally, to support EU AI Act assessments directly in SAP AI Agent Hub, we also introduced our new AI Governance Assistant. The assistant audits and flags incomplete documentation in the agent inventory, pre-fills fields from completed assessments, identifies systems that appear high-risk but lack classification, and triggers reassessment when a fact sheet changes materially.

And just as the architecture context feature depends on human approval, all outputs from the AI Governance Assistant appear as drafts for legal and compliance review.

SAP and AI governance in depth

The solutions and innovations around AI governance we discussed at SAP TechEd are part of a much broader story. That story is, to a degree, historical. SAP has long played a key role in the governance of core operational and financial functions. Our approach to AI governance is built on—and a logical extension of—this legacy.

Of course, SAP is hardly new to this, having long ago established clear internal standards for AI governance while continuously introducing features and solutions devoted to AI governance. Among these solutions is SAP AI Agent Hub, itself an outgrowth of AI governance capabilities in SAP LeanIX. By allowing companies to quickly create and maintain a reliable inventory of agents, regardless of platform, MCP servers, and LLMs, the hub’s powerful discovery features are essential to comprehensive AI governance.

The other part of the story is value. While governance of AI is crucial for myriad reasons, companies invest in AI to achieve measurable business goals. As it turns out,t he observability necessary for effective governance can be leveraged and augmented to serve the purpose of performance management and evaluation.

With SAP Signavio agent mining capabilities, for example, you can monitor agent behavior within the context of your business processes. In this way, you can ensure agent compliance while capturing the business impact agents deliver.

Governance should not be an afterthought

The evolution of AI is not going to slow down, and neither will AI adoption. Unfortunately, while the focus here rightly falls on continuously discovering new ways to leverage AI for operational excellence and competitive advantage, this focus should not mean that governance takes a back seat.

Governance, on the contrary, is the key to successful AI adoption.

It is important to remember that governance in the era of AI is not simply a question of regulatory or corporate compliance. Because this technology involves varying degrees of autonomy, governance must be applied to the behavior of the technology itself, not just to the behavior of the humans managing it. This is one reason that we emphasize runtime enforcement of governance policies.

The challenge we see today, however, is that no one has yet established clear industry benchmarks and standard practices for AI governance. There also seems to be a general lack of established platforms focused on governance.

We say a “general lack” because, in point of fact, SAP offers precisely such a platform, one built on decades of governance expertise and experience.

Governance has never been an afterthought for us. And when it comes to AI governance today, as the many innovations outline here show, it is absolutely top of mind.

Dominik Rose is chief product officer for SAP LeanIX at SAP.

SAP has been positioned in the Leader Category of the 2026 IDC MarketScape for AI-Enabled Direct Spend Vendor Assessment.*

We believe this recognition reflects SAP’s long-term investment in helping manufacturers connect sourcing, engineering, planning, and supplier collaboration on a single foundation.

Direct materials procurement doesn’t get enough credit for how hard it actually is. Unlike indirect spend, direct materials sit at the intersection of engineering, planning, finance, and supplier relationships—often all at once. A design change triggers a sourcing event. A commodity price spike ripples into contract terms. A supplier quality issue lands on the production floor before procurement even knows it happened.

The organizations that manage this well don’t just have good sourcing tools. They have connected systems, trusted data, and the ability to act quickly when conditions change. Solving for that complexity is what SAP’s direct spend portfolio is built to do.

Connecting design, sourcing, and execution

SAP’s direct spend offering is built with an industry-specific lens. A cookie-cutter approach to procurement business processes does not work for direct materials.

An engineering-oriented industry like automotive or aerospace, where a design change can trigger a sourcing event, has fundamentally different needs than a brand- or asset-oriented industry such as consumer goods or chemicals, where commodity exposure and supplier scale dominate. SAP builds for both, with purpose-built offerings tuned to how each actually works.

What our offerings share is a single, unbroken data model running from new product introduction through sourcing, contract award, and purchase order execution, all within SAP Business Suite: no bolt-on connectors, no manual handoffs between systems.

This matters more than it might seem. Data fragmentation across the design-to-source-to-settle workflow remains one of the biggest barriers to AI delivering real value in direct spend. When procurement decisions are connected to engineering, planning, supplier, and financial data on a shared foundation, AI has meaningful context to work with.

A network and ecosystem that extends the core

The sourcing suites are the center of gravity, but what surrounds them is equally important for manufacturers managing complex, multi-tier supply chains.

SAP Business Network connects millions of trading partners across roughly 190 countries, with more than US$7.7 trillion in annual commerce flowing through it. The network supports forecast collaboration, purchase order execution, inventory management, logistics visibility, quality processes, and supplier communication. For global manufacturers managing complex supply chains, that scale can be operationally significant.

Customers are already seeing the benefits of a more integrated approach to direct spend. For example, global automotive supplier Multimatic selected SAP’s direct materials sourcing solution because of its close integration with core ERP processes, including bill of materials management, production planning, and cost calculation. By connecting sourcing more closely to product development and manufacturing workflows, the company is helping procurement, engineering, and suppliers work from the same foundation throughout the product life cycle.

Additional SAP capabilities extend the process further across product development, commodity management, supply planning, supplier collaboration, financing, and analytics. Together, these capabilities help organizations manage direct spend as part of an integrated process that spans from early design collaboration through supplier payment, supported by a unified data foundation.

Taken together, these capabilities span a much broader scope than traditional sourcing software, from early design collaboration through supplier payment, all governed on SAP Business Data Cloud as a unified analytics foundation.

Where AI stands today, and where it’s going

Today, SAP delivers AI-powered supplier and item recommendations, invoice data extraction, category strategy insights, supplier risk scoring, and Joule capabilities embedded throughout the suite. These are production capabilities already helping customers streamline procurement processes.

Looking ahead, SAP plans to expand its AI capabilities across the direct spend life cycle, with new agentic experiences focused on areas such as market intelligence, supplier discovery, RFx orchestration, negotiation support, contract authoring, and supply chain impact analysis. These innovations will be delivered through Joule Work and Joule Studio 2.0, a no-code/low-code environment built on SAP Business AI that enables organizations to create and manage agents grounded in live business data and end-to-end process context.

The foundation underneath this road map is what makes it credible. Agents are only as good as the data and process context they can access. When that foundation is fragmented across disconnected systems, AI adds noise as often as it adds value. When it’s unified, agents can execute with greater relevance and accuracy.

Who this is built for

The SAP Ariba offering foo direct spend works with any ERP backend, with the added benefit of integrating out of the box with SAP Cloud ERP. For aerospace and defense customers with data sovereignty requirements, SAP offers deployment options for sovereign cloud that few vendors in this space support. For brand- and asset-oriented enterprises, a consolidated source-to-pay platform spanning both direct and indirect spend can simplify governance while reducing complexity.

For manufacturers operating complex global supply chains, the value of a natively integrated approach is straightforward: fewer manual handoffs, better visibility across functions, faster response to disruptions, and AI that can draw on connected business data rather than isolated point solutions.

What this recognition means to us

We’re grateful to the customers and partners whose real-world feedback shapes how we build these products. We believe an IDC MarketScape recognition reflects their experiences as much as it reflects our road map, and we don’t take that lightly.

This recognition energizes us. For more than 50 years, SAP has helped organizations run their most critical business processes, and direct spend is one of the areas where that experience comes together most clearly. We’ll continue investing in deeper integration, broader network capabilities, trusted AI, and the industry expertise our customers rely on. We’re grateful to the customers and partners that continue to help shape these solutions and help us deliver meaningful innovation across the direct spend life cycle.

Fang Chang is executive vice president and chief product officer for SAP Procurement and External Workforce Solutions at SAP.
Baber Farooq is chief marketing officer for SAP Spend Management.

*IDC MarketScape: Worldwide AI-Enabled Direct Spend 2026 Vendor Assessment, IDC #US54900426, September 2026.

BETHESDA — SAP SE (NYSE: SAP) today announced that Lockheed Martin has successfully gone live with SAP SuccessFactors solutions, including SAP SuccessFactors Employee Central, SAP SuccessFactors Employee Central Payroll, SAP SuccessFactors Recruiting and SAP SuccessFactors Onboarding, marking a significant milestone in the company’s workforce transformation journey.

The deployment brings together core human resources (HR) processes on a flexible cloud foundation designed to simplify HR operations, enhance employee experience and support a global workforce. 

A leader in aerospace, defense and advanced technology solutions, Lockheed Martin is modernizing its HR landscape by moving from legacy systems to a unified platform. The new environment provides a more connected experience for employees and managers while supporting greater consistency and operational efficiency across the enterprise.  

With almost 60% of its 123,000 employees being engineers, scientists and technologists, attracting, developing and retaining highly skilled talent at scale is critical to Lockheed Martin’s continued success. By creating a single source of truth for workforce data, Lockheed Martin is gaining clearer insight into its workforce, enabling more informed talent decisions. 

This transformation allows Lockheed Martin to accelerate its robust applied AI strategy across the workforce to help employees and managers access information more efficiently and unlock new insights across the employee life cycle. 

“Lockheed Martin is advancing an enterprise-wide transformation of exceptional scale and complexity, while meeting the rigorous demands of a highly regulated industry,” said Thomas Saueressig, Member of the Executive Board and Chief Customer Officer of SAP SE. “This milestone reflects Lockheed Martin’s commitment to modernizing workforce operations and investing in technologies that support employees, strengthen organizational agility and position the company for future innovation.”

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Top image courtesy Lockheed Martin

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