Artificial intelligence (AI) is becoming an integral part of everyday work in learning and development (L&D). While it might seem like we’re entering an era where we’ll only need an AI tool or two to complete our learning ecosystem, this hasn’t been the case. The options for developing and delivering training are no longer limited to using an authoring tool to create courses and a learning management system (LMS) to deliver them. Organizations now use multiple technologies to solve a variety of needs and goals within an enterprise learning ecosystem.
Today, many learning technology vendors are integrating AI capabilities into their products to enhance the existing tool, not replace the entire ecosystem. There is high value in using specific tools to meet different goals. For example, your sales team uses an AI-powered role-playing tool to simulate real-world conversations; your cybersecurity team uses an AI agent to test knowledge; and your accounting team asks an AI chatbot for a regulatory refresher. While all use AI, they access a wide variety of content from different places.
Consequently, your ecosystem can quickly become complex. You may find yourself inundated with more tools, a growing pool of knowledge, and more data, but no way to see how these pieces work together. The key is organizing your ecosystem so technologies can “talk” to one another to gain a holistic understanding.
Align Your Architecture
For L&D, this means fundamentally rethinking how your organization approaches the development, delivery, and measurement of knowledge. It turns out eLearning standards such as SCORM, LTI, xAPI, and cmi5 serve as the foundation for AI-driven innovation and remain necessary for interoperability and data integrity. Ready to align your architecture for the future? Download our eBook, at: https://info.rusticisoftware.com/tm-ai-ecosystem-ebook/
