When the first spreadsheet program was released in 1979, it was hailed as the very first "killer application" for the nascent personal computing market. And while it was a boon for anyone who needed to track any sort of data, what made it transformative was the ability for office workers to run endless what-if scenarios—what happens if you put 25 percent of your portfolio in frozen concentrate orange juice futures? What would it look like if you were able to consolidate factories? How many accounts would you need to shuffle for that to be a viable option? The speed of business decision-making accelerated at an absolutely mind-boggling pace.
Today, generative AI is creating another disruptive leap forward. Large language models and foundational models are speeding up data analysis while gen AI coding tools allow teams to spin up ad hoc applications to solve incredibly specific problems. And all of the scenarios above? With the correct human oversight, that analysis can be performed—and decisions can be made—autonomously.
But to make this futuristic workflow operate seamlessly, the applications, agents, and data need to be playing in the same sandbox. That’s the principle driving SAP’s new role-based Joule Agents, which was announced at SAP Connect in October 2025. “We believe a seamless app, data, and AI flywheel creates the highest value,” said Muhammad Alam, member of the executive board of SAP SE, SAP Product & Engineering, from the keynote stage. “Otherwise, the costs—and the opportunity costs—of the alternative are very significant for the organization.”
The Rise of Agentic Implementation
Depending on their specialty, many of the tasks that knowledge workers handle in their day-to-day jobs equate to a series of highly specific digital repetitive motions that, with the right workflow, can be streamlined. Answering basic customer questions, digging through old requests for proposals, keeping tabs on product compliance—these are all tasks that, with the correct governance, can be automated by interconnected AI agents, freeing flesh-and-blood workers to think critically and move quickly.
These agents—autonomous software programs that can understand business intent, make decisions, and take action across multiple applications with or without human intervention—are being implemented across enterprise environments, and they’re at the core of SAP Business Suite. Drawing on the applications and data from across SAP Business Suite, Joule’s role-aware assistants are designed to partner with a human being in their specific job role, allowing the human to tap into the right agents for the job, set up the workflows, and manage the agents based on predefined rules and actions. On the human side of the human-computer partnership, when an analyst needs to shift vendors or check in on a client, they fire up a Joule chat window and use natural language to prompt the agentic workflow. “[It’s] a new emerging conversational AI-driven engagement layer; what we call gen UI,” said Alam. “That becomes the one place for users for almost everything. Things like information retrieval, deep insights, navigation, agent interaction, and many more things.”
Joule’s ability to retrieve information across silos and reason through complex ecosystems creates a sea change for both enterprise and small- to medium-sized businesses precisely for that reason: It is able to keep tabs on incredibly labyrinthine data and regulatory environments.
For example, in the first half of 2026, manufacturing firms will be able to use SAP Supply Chain Orchestration built on SAP Business Technology Platform. With access to data from SAP’s Business Network applications and the SAP Business Data Cloud solution, the agent will be able to predict and correct supply chain risk—notifying stakeholders when suppliers, materials, or orders are disrupted.
Once the agent has checked in with its human counterpart, it can take action autonomously, coordinating with planning, logistics, procurement, and other departments to resolve (or at least mitigate) the disruption, speeding up response times from days and weeks to hours. “When you’re a smaller, midsize organization, the impact is even greater,” said Jan Gilg, chief revenue officer, Americas and SAP Business Suite, from the stage at SAP Connect. “Every hour of time saved or productivity gained means you can spend more time focusing on the things that move the needle in growing your business.”
In SAP’s finance stack, Joule’s international trade classification agent can compare product materials with the relevant trade regulations to classify goods for international shipping—taking the guesswork out of a highly volatile customs environment. “To thrive when volatility is the new normal, businesses need more than a patchwork of disparate best-of-breed applications,” said Alam.
The Power of Integrated Data
None of these solutions would be possible without tight integration with an organization’s various applications and data layers, which is why SAP has aligned its products for a “global maxima”—the best holistic solution across the entire problem space—as opposed to optimizing each business function through a curated best-in-class strategy. The latter strategy consists of implementing solutions from several different vendors (the best in each category) for each team, app, or solution, and then pointing them at your various data sources. But according to Alam, “If you add in a separate AI layer on top of your applications layer, you would need to build and maintain integrations across it and every other application and data source within your landscape.”
Critically, integration of new AI tools from multiple vendors can account for 50 percent of a digital platform budget. Along with the architectural complexities of building necessary governance and enterprise-wide data systems, top-notch approaches create silos and flatten data nuances throughout knowledge graphs—potentially dropping critical business context. “And not just that,” Alam continued. “You’d have to build a completely new roles and permissions framework to keep the right security structure in place for accessing data.”
The Future of Autonomous Agents
Nearly 70% of enterprise organizations plan to implement AI agents in their resource planning processes within 18 months. These agents are designed to support human workers and provide operational efficiencies. But this is just the beginning. Over the next 10 to 12 years, agentic implementation will evolve from handy assistants to entirely replacing applications—in some cases, coding solutions autonomously and exponentially speeding up operations. But as we learned from the advent of the pivot table, every step in the automation journey since the Industrial Revolution has reshaped society around technological advancement. Now, for all of the excitement and scrutiny around how generative AI is already changing how we live, work, and create, it’s clear that we—society—are embarking on the next stages of AI workplace transformation.
Watch the keynote and learn more about SAP Business Intelligence Suite at SAP.com.
