When staff resort to copying data between spreadsheets, keeping shadow systems in Excel, or doing repetitive tasks that feel like they should be automated, something is wrong. These workarounds creep in gradually; a quick fix here, a temporary solution there, until suddenly your operations depend on a patchwork of manual processes. Workarounds rarely stay small. What begins as a simple spreadsheet to track information your CRM cannot handle eventually becomes a document that multiple team members depend on.
When learning teams feel overwhelmed, the diagnosis is often predictable. There is too much content to create. Too many courses to manage. Too many programs to support. Too many learners to engage. As a result, organizations respond by investing in better authoring tools, richer content libraries, and more advanced learning platforms. While these investments improve delivery, they rarely reduce operational strain.
A MIT study last year showed that 95 percent of generative AI implementations fail. They generate little to no business value. There can be various reasons for this. Think of poor integration, little focus on solving real problems, and unrealistic expectations. As far as Appian CEO Matt Calkins is concerned, this is an absurd percentage for something that is seen as the breakthrough technology of this generation.
Before we dive into the details: Joule is SAP's AI co-pilot, a chat window that allows users to communicate with SAP software in natural language. Joule agents are specialized AI assistants that not only provide answers but also perform actual actions. They analyze data, make recommendations, and perform tasks that were previously done manually by the user. The difference with a traditional copilot is that an agent can independently reason about complex information and then take action without you having to intervene constantly.