Driving Enterprise Transformation: Insights from SAP NOW AI Tour London

The hushed anticipation in the Excel London exhibition hall, the murmur of conversations over coffee, the tangible buzz when a speaker unveils a truly innovative solution—these are the moments that define a pivotal industry event.

For businesses navigating the intricate dance of digital transformation, particularly in the realm of procurement, such gatherings are more than just conferences; they are crucibles of insight, places where strategies crystallize and partnerships deepen.

This was the essence of the SAP NOW AI Tour, an event designed to pull back the curtain on how enterprise AI is not just a futuristic concept, but a present-day reality actively streamlining operations and unlocking new sources of value across the end-to-end procurement function.

At the heart of the UK and Ireland stop, Procurement Magazine caught up with Stephan de Barse, President, Global Business Suite at SAP.

His perspective offered a grounded, yet expansive view of the tours purpose and, more critically, how organizations should strategically approach AI implementation.

This is not merely about adopting new technology; it is about fundamentally rethinking business processes, driving innovation, and achieving measurable impact on the balance sheet.

The discussions were rich, the demonstrations compelling, and the message clear: the journey to intelligent procurement is collaborative, data-driven, and deeply embedded in core business applications.

In short: Stephan de Barse of SAP discusses the SAP NOW AI Tour’s purpose in educating customers on delivering business value through embedded AI in procurement and best practices for AI implementation, emphasizing clear use cases and native integration.

The Purpose of the SAP NOW AI Tour: Beyond the Pitch

Stephan de Barse articulated the core mission of the SAP NOW AI Tour with refreshing clarity:

Ultimately, what we want to do first and foremost is get our customers exposed to other customers to learn and understand how you can actually deliver business value from the solutions that we provide (Stephan de Barse, SAP).

This underscores a philosophy centered on peer-to-peer learning and practical application, moving beyond theoretical discussions of SAP AI strategy to tangible outcomes.

The tour aimed to address the myriad questions businesses have regarding AIs impact on productivity, profitability (P&L), and the overall balance sheet.

It was a platform for SAP to demonstrate its latest innovations, including next-gen Ariba and new AI agents, and to showcase how apps, data, and AI converge as a flywheel to deliver maximum customer value.

This focus on education, networking, and sharing best practices is crucial in an era where AI implementation can feel both exciting and overwhelming.

The goal was to demystify AI, presenting it not as a standalone solution, but as an integrated layer designed to enhance existing processes and create new efficiencies.

Key Takeaways from the London Event: Embedding AI for Real Value

The London event provided several resonant insights, particularly concerning the true source of AIs value.

Stephan de Barse highlighted a critical shift in perspective:

What stands out to me is that companies truly understand that the value is not necessarily just in the app layer.

Its about how you access the data, combine the data with other data sources and then make sure there is an an AI layer on top.

That should not be a disconnected layer somewhere; it has to be embedded back in the core application to drive value and adoption (Stephan de Barse, SAP).

This emphasizes the need for deep, native integration rather than superficial add-ons.

Furthermore, attendees recognized that successful AI user adoption goes beyond mere technology.

It hinges on embracing industry best practices and prioritizing user adoption.

Discussions around SAPs tool chain—including Signavio, LeanIX, and WalkMe—resonated strongly, indicating a clear demand for solutions that support the entire implementation journey.

Perhaps most inspiring was the presence of early adopting customers who offered real-world testimonials, moving innovations from PowerPoint slides to verified business successes.

Their experiences serve as powerful motivators, demonstrating that the future of intelligent applications is already here and making a tangible difference.

The Importance of Clear AI Use Cases for Business Value

Implementing AI without a clear business problem in mind is akin to setting sail without a destination.

Stephan de Barse stressed this point emphatically:

Having that in mind is extremely important.

Ultimately, with any software implementation, its about the business problem youre trying to solve.

When you solve that business problem, how much value should that deliver to the business?

I should see it in my P&L – either costs down, revenue up or working capital (Stephan de Barse, SAP).

This statement underscores the need for a results-oriented approach to AI implementation, where every initiative is tied to measurable financial impact and contributes to business value AI.

Customers are increasingly recognizing that for AI to deliver on this promise, core applications must reside in the cloud and be natively integrated.

This foundation allows for the seamless connection of different data sources, paving the way for the development of intelligent applications SAP.

In procurement, specifically, AI is not just optimizing existing steps but is driving a complete rethinking of the entire procure-to-pay AI process.

Areas such as contract intelligence, AI for negotiations, third-party risk factors, autonomous buying, and issuing RFPs are all being transformed, evolving from a traditional 15-step process to a more streamlined, AI-enabled function.

This shift represents a journey, and many SAP customers are already well on their way in procurement transformation.

SAPs Evolving Role: From Vendor to Business Partner

The SAP NOW AI Tour also highlighted a significant evolution in SAPs relationship with its customers.

Historically viewed primarily as a technology vendor, SAP is now positioning itself as a strategic business partner, journeying alongside its clients in their AI transformation.

This collaborative approach emphasizes shared challenges and mutual growth, reinforcing the enterprise AI procurement strategy.

The value derived from face-to-face interactions, coffee chats, and direct exchanges on challenges and solutions cannot be overstated.

These conversations foster a deeper understanding of AI user adoption dynamics and complex data problems, which are vital for successful AI implementation.

This commitment to partnership and continuous engagement is a cornerstone of SAPs strategy, with plans to double down on these interactive events and return next year.

This shift signals a move toward a more consultative and supportive role, reflecting the complex, ongoing nature of digital transformation with enterprise AI procurement.

Your Playbook: Navigating AI Implementation in Procurement

• Prioritize Business Problems, Not Just Technology: Before investing in any AI solution, clearly define the specific business problem you aim to solve.

  Quantify the expected value—whether it is reduced costs, increased revenue, or improved working capital—and ensure it aligns with your P&L objectives (Stephan de Barse, SAP).

  This ensures your AI initiatives drive tangible business value AI.

• Embrace Cloud-Native, Integrated Core Applications: Recognize that core applications need to be in the cloud and natively integrated.

  This foundational step is crucial for connecting disparate data sources and building intelligent applications efficiently.

  This ensures seamless data integration AI.

• Embed AI Directly into Core Processes: Do not treat AI as a disconnected layer.

  For maximum value and AI user adoption, AI capabilities should be embedded directly back into your core applications and procurement transformation processes (Stephan de Barse, SAP).

  This ensures AI enhances existing workflows rather than creating new silos.

• Focus on User Adoption and Best Practices: Technology alone is insufficient.

  Actively plan for user adoption by incorporating industry best practices and leveraging tools that facilitate change management.

  Tools like Signavio, LeanIX, and WalkMe can support this aspect of AI user adoption.

• Seek Specialist Partnership: Look beyond traditional vendor relationships.

  Engage with partners like SAP who demonstrate a commitment to understanding your specific business challenges and offer collaborative support throughout your AI implementation journey, aligning with SAP AI strategy.

• Explore Specific Procurement Use Cases: Consider how AI can fundamentally rethink your procure-to-pay process.

  This includes applications in contract intelligence, AI for negotiations, managing third-party risk factors, autonomous buying, and streamlining RFP issuance.

  This drives enterprise AI procurement.

Risks, Trade-offs, and Ethical Considerations

While the promise of AI in procurement is significant, organizations must navigate potential risks and trade-offs.

One primary risk involves data quality and security; AI systems are only as good as the data they consume, and vulnerabilities in data integrity or privacy can lead to significant operational and reputational damage.

A trade-off might involve the initial investment required for cloud migration and native integration versus the long-term cost savings and efficiency gains.

Mitigation strategies include implementing robust data governance frameworks, investing in cybersecurity measures, and conducting thorough pilot programs to test AI solutions in controlled environments before full-scale deployment.

Ethically, organizations must ensure AI procurement solutions are fair, transparent, and do not inadvertently introduce biases into supplier selection or contract negotiations.

This requires continuous monitoring and a commitment to responsible AI practices.

Tools, Metrics, and Cadence for Success

Key Tools:

The strategic implementation of AI in procurement leverages several key tools.

These include SAPs Ariba for next-gen AI-powered procurement solutions, SAP Signavio for process intelligence and optimization, LeanIX for enterprise architecture and technology landscape management, and WalkMe for digital adoption and user guidance.

Cloud-Native Platforms are also fundamental, providing the necessary foundation for integrated data sources and intelligent applications.

Key Performance Indicators (KPIs) for AI Procurement:

Monitoring the success of AI in procurement involves tracking several key metrics.

These include Cost Reduction from AI, measured as a percentage decrease in procurement costs due to AI automation or optimization, aiming for measurable improvement such as 5-15%.

Cycle Time Reduction tracks the decrease in average time for procure-to-pay or specific processes, with a target of significant reduction, for example, 20% or more.

Innovation Impact quantifies the number of new value sources unlocked or business problems solved by AI, targeting quantifiable new opportunities.

User Adoption Rate measures the percentage of the procurement team actively using new AI tools, with a goal of high adoption, typically 80% or more.

Finally, P&L Contribution assesses the quantifiable impact on profit and loss, whether through costs down or revenue up, aiming for a positive and measurable impact (OpenAI).

Review Cadence:

AI implementation is an ongoing journey, not a one-time project.

Regular reviews should occur:

• Quarterly: To assess performance against KPIs, gather user feedback, and make necessary adjustments.
• Annually: For a comprehensive strategic review, evaluating alignment with evolving business objectives and technological advancements.
• After major upgrades or new AI agent deployments: To ensure seamless integration and optimal performance.

FAQs: Your Quick Answers for Implementation

Q: What is the primary purpose of the SAP NOW AI Tour?

A: The primary purpose is to expose customers to other customers to learn and understand how to deliver business value from SAPs solutions, focusing on AI strategy, latest innovations, and how apps, data, and AI integrate to maximize value (Stephan de Barse, SAP).

Q: What were the key insights from the SAP NOW AI Tour in London?

A: Key insights included companies realizing that AI value comes from accessing and combining data with other sources, embedding AI into core applications, and the importance of industry best practices and user adoption.

Early adopting customers confirmed the real-world impact of innovations (Stephan de Barse, SAP).

Q: Why are clear use cases important before implementing AI?

A: Clear use cases are crucial because AI implementation should always focus on solving a specific business problem and delivering measurable value, such as reduced costs, increased revenue, or improved working capital, which should be reflected in the P&L (Stephan de Barse, SAP).

Conclusion: Partnering for an Intelligent Future

The journey towards intelligent applications and AI-driven procurement is complex, but the path is becoming clearer.

As Stephan de Barse underscored at the SAP NOW AI Tour, the real value of AI emerges when it is deeply integrated, solving concrete business problems, and supported by a commitment to user adoption and industry best practices.

SAPs evolving role as a business partner, rather than just a technology vendor, highlights the collaborative spirit needed for this transformation.

It is more than just deploying software; it is about rethinking processes, unlocking new efficiencies, and securing measurable gains for your organization.

By embracing AI with clear objectives and strategic partnerships, businesses can transform their procurement functions, moving from a multi-step process to a truly intelligent, value-generating engine.

The future of enterprise AI is not just coming; it is being built together, one successful implementation at a time.

Glossary

• Artificial Intelligence (AI): The simulation of human intelligence processes by machines, especially computer systems, that exhibit attributes such as learning, reasoning, and problem-solving.
• Enterprise AI: The application of AI technologies across an entire organization to automate processes, gain insights, and enhance decision-making at scale.
• Procurement Function: The overarching process of acquiring goods, services, or works from an external source, often involving strategic planning, supplier selection, contracting, and payment.
• Procure-to-Pay Process: The end-to-end process in procurement, from initiating a purchase requisition to issuing a purchase order, receiving goods, and finally processing supplier invoices and payments.
• User Adoption: The process by which users embrace and regularly use new technology or system features, crucial for realizing the intended benefits of software implementation.
• P&L (Profit & Loss): A financial statement that summarizes the revenues, costs, and expenses incurred during a specific period, indicating the companys financial performance.
• Native Integration: The seamless connection of different software applications or systems at a deep level, allowing them to work together cohesively without requiring extensive custom coding or middleware.

References

Procurement Magazine, SAP NOW AI Tour, London: Stephan de Barse, SAP.