At this year’s SAP Sapphire conference, I had the opportunity to sit down with Jared Coyle, the Chief AI Officer for Americas at SAP, for a candid conversation about the state of AI, the strategic vision behind SAP’s latest announcements and what business leaders need to consider as they step into a future powered by artificial intelligence and automation.
Breaking down the buzz about AI agents and Joule Studio
Jared kicked off the discussion by addressing the most headline-worthy AI developments announced at Sapphire: A deep focus on AI agents and the introduction of SAP’s Joule Studio. These “agents” go beyond generic automation. They’re designed to integrate deeply with existing business processes and data structures, creating a bridge between structured enterprise data and the intuitive interfaces of generative AI.
“What’s magical is that these agents are grounded in 52 years of business data across finance, supply chain, HR and more. When you deploy AI in that context, it can drive consistent, end-to-end business processes with reliability, and with a human in the loop where needed,” Jared explained.
The promise here isn’t just about flashy tech. It’s about enabling practical, responsible automation at scale. Agents like those in Joule can be tuned for roles such as collections, billing or inventory management, allowing organisations to streamline operations in a way that aligns with how they already work.
Who’s coming to Sapphire, and why
While AI was front and centre, Jared was quick to point out that Sapphire attracts a wide swath of business leadership, not just technologists. “It’s not just the CTOs and CIOs,” he said. “It’s CFOs, heads of supply chain, HR leaders, operations officers. These are business leaders looking to drive top and bottom-line efficiencies through technology.”
This mix reflects the broader enterprise appetite for transformation. Leaders aren’t just looking for the next shiny object. They want tangible ROI and solutions that align with strategic goals.
And while there is much enthusiasm surrounding AI, the excitement is tempered by hesitation. Jared outlined the three primary concerns he hears repeatedly:
Human Impact: “When you introduce AI into a workflow, it changes people’s roles,” he noted. Leaders want to understand how to bring their workforce along with the transformation, not displace them.
Data Privacy and Protection: Safeguarding proprietary information remains a critical concern, especially with generative AI models that could introduce risk.
Governance and Risk: From regulatory compliance to industry-specific risk factors, organisations want frameworks that support AI innovation without adding operational uncertainty.
Jared emphasised that addressing these concerns starts with engineering trust into the system itself. “You need grounded data,” he said. SAP’s approach includes a knowledge graph built on hundreds of thousands of business objects. Think about purchase orders, sales records and financial data, giving AI models structure and context to avoid hallucinations and drive reliable outcomes.
Common roadblocks to integration
One key challenge Jared identified is the readiness of legacy systems. “If an organisation hasn’t modernised its stack, the path to AI is harder,” he said. Cloud-native infrastructure is a major enabler, and so is having a strategic mindset.
“Organisations need to stop throwing darts at a board with random use cases. They need a coordinated strategy that targets business value.”
That includes empowering more people within the organisation to explore AI, turning curiosity and experimentation into innovation at scale.
Advice for starting smart with AI
When asked for step-one guidance, Jared offered this perspective: “Don’t think your end goal is the final goal.”
In a space where technology evolves every six weeks, static roadmaps won’t cut it. Businesses must be adaptable and ready to adjust, reassess and reimagine as new capabilities emerge.
He recommends working backwards from tangible business problems. “Let’s say you have too much inventory. Work back from that. Imagine the future where it’s optimised. Then identify how AI can support that outcome.”
A look into SAP’s own AI journey
SAP itself is walking the talk. Internally, the company has applied AI to improve legal and quoting workflows, streamline operations, and even build smarter conference experiences, like the AI-powered agenda builder at Sapphire.
Their goal, according to Jared, is to make AI “the software itself,” and not just a bolt-on solution but an integrated fabric running through every business function.
What’s next is orchestration and collaboration
Looking ahead, Jared sees orchestration across complex tech stacks as the next big milestone. “Organisations aren’t just running SAP,” he acknowledged. “Our agents need to work with others across platforms.”
That means the focus will shift from isolated automation to end-to-end processes where multiple AI agents communicate and adapt together, ushering in a new era of enterprise intelligence.
Final takeaway: Start with the boring stuff
In a closing thought that defied the hype, Jared said, “The best AI is boring.”
His advice is to focus on foundational tasks. Solve the simple, high-impact problems first. Look at those that drive real value today.
“The science projects will eventually yield results, but it’s the basics that move the needle now,” he said.
Enterprise Times: What does this mean?
Jared’s insights serve as both inspiration and a roadmap. AI isn’t just for tech giants or experimental labs. It’s for any business ready to modernise, align around clear goals and empower its people. To move forward with AI and other emerging technologies in a more seamless way, organisations should ground AI initiatives in trusted enterprise data and start with real, high-value business problems.
Rather than pursuing hype-driven pilots, it’s smarter to build a strategy around business needs and let the tech serve that purpose. It’s also important to include your people. Offer education, create a culture of exploration and make change approachable. Adaptability is key. Technology will continue to evolve quickly, so don’t get stuck on rigid roadmaps.
Stay flexible, be prepared to pivot and keep your mission focused on outcomes. And while SAP offers a robust framework for AI adoption, leaders should look holistically at their tech ecosystem to determine what orchestration and tooling will best support their goals.
link