AI Should Help You "Do" Things

The Union

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2y ago 22:40

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Generative AI possesses great abilities to craft impressive content. Its capacities in generating text, photos, and videos, and engaging in conversational interactions are remarkable, yet they represent only one step in a customer's or employee's quest to complete a process. Imagine a customer reaching out to an organization for assistance. Generative AI can answer this person if its model supports the request or it can suggest another method. However, its true potential can only be exploited when it transcends conversational limitations and takes definitive actions to help you actually "do" something.

We must view AI not just as an intelligent service that generates content, but as an operative tool that propels actions and leads to substantial business outcomes. AI should be more than an impressive chatbot; it must guide your customers and employees based on the next best actions for the outcome they are seeking. This is a fundamental concept in the realm of AI: operationalization and optimization. And, this AI shouldn't merely exist in the realm of conversations but rather connect to real-time systems, actively engage with multiple people, and most importantly, facilitate actions that drive positive business outcomes.

This journey of operationalizing AI starts with a simple, yet important, concept. Eventually, you will want customers and employees to have one-on-one, one-to-many, or many-to-many conversations with your real-time systems. Doing so provides them the capability to complete an outcome by themselves. In essence, what we are striving for is an AI automation system that does more than just chatter—it must "do" things. Chris and I delve into this intriguing aspect of AI in this second of three episodes, breaking down AI complexities and understanding its capacity to "do" things, which ultimately leads to measurable outcomes.

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