Many wondered “Is there anything AI can’t do?” But as we began to test the limits of the technology, it became clear that different AI tools are required for certain tasks.
Generative AI on its own may have its limitations, but as artificial intelligence technology advances, we’re unlocking new ways to use AI, particularly for business communications. These developments build on Natural Language Processing (NLP), Large Language Models (LLMs) and speech recognition, enabling greater efficiency across organizations and departments.
If, for instance, an organization wanted to build a solution that uses AI to summarize meetings and calls, ChatGPT alone wouldn’t be able to do that without adding a separate transcription tool since ChatGPT only analyzes text inputs. However, with technology like LeMUR, it becomes possible to create solutions that summarize and analyze meetings from audio and video streams without any additional steps.
Getting Data from Your Meetings
AI summarization models can analyze large bodies of text from conversations, identify the vital takeaways, and provide summaries with the key information. This makes them powerful tools for reviewing sales calls, taking meeting notes, coaching agents, and more.
When you leverage AI to summarize, analyze, and report on a meeting or conversation, using the original source of the meeting data makes a significant difference between high-quality and low-quality results. (Many AI tools like ChatGPT can’t transcribe meetings and summarize them on their own; they need text input or the transcription from somewhere else first, so it’s best to leverage an all-in-one AI system or platform that offers transcription and summarization.)
Voice-to-text technology has grown faster and more accurate in recent years, making it easy to transcribe meetings in real time during a call. However, transcriptions alone only tell half the story. Factors like the speaker’s tone of voice play a role in the overall conversation, and any inaccuracies in the transcript will carry over into the analysis.
The most efficient and effective way to get meeting summaries is directly from the recording. This method is accurate and eliminates the extra step of requiring a separate transcription to run through the Generative AI model, making it a preferable option for anyone building a solution with AI-powered summaries.
