How Do You Deploy Conversational AI that You Can Trust? | Salesforce

How can you deploy conversational AI that you can trust? The promise of conversational AI assistants is that they'll help you work faster by allowing you to express your questions or instructions in natural language and giving you useful generative AI responses. But the question for any business attracted to this promise is can we actually trust these responses and trust that our data is protected and trust a deployment of these technologies in our business? And thankfully, Einstein Copilot gives us some answers, starting with how to get trusted responses. Generative AI's superpower is its ability to turn natural language prompts into imaginative content. But that power comes with a weakness for businesses, because these technologies are prone to hallucinate answers that have nothing to do with our businesses. And the solution to this is a technique called grounding, where we add context and guidance into the prompt, focusing generative AI's imaginative powers to get results that are much more relevant to our businesses. And Salesforce gives you the ability to do dynamic grounding with your CRM and business data, enabling you to harness generative AI's imaginative powers to get responses that are much more relevant to your business. But how does Einstein Copilot help you trust that your data is protected? Well, first, Salesforce has zero retention data agreements with all of our AI partners, which means none of your data is ever stored outside the Einstein Trust layer or used to enhance any other results other than your own. But beyond that, all of the data and actions that Einstein Copilot is using to generate these responses is being retrieved and executed with your users permissions, which is how Salesforce is applying a permissions layer to to large language models that are inherently permissions lists. But even with these protections, how can you trust a deployment of these technologies in your business? Well first, when getting started, you're probably not going to enable these technologies in your production environments. Instead you'll be working inside a sandbox, which is a partial or full clone of your Salesforce environment, where you can safely experiment with these technologies. Then you'll use Copilot Builder to test your copilot and inspect how it works, which includes the dynamic plans that it creates and executes for each input. And behind those plans are actions which give your Einstein Copilot its capabilities. And behind those actions are the flows, apex classes and prompt templates that give you complete control over how your Einstein Copilot works. And when you're ready to deploy, you can do a phased rollout, starting with a trusted group of beta testers before expanding to your entire organization. And even then, the journey is not over. Because you'll have built in analytics that help you measure and monitor your Einstein copilot and use that understanding to make continual improvements until finally you'll have a conversational AI assistant deployed that you can trust to help every employee in your organization work faster.