You’re not seeing double. Microsoft launched its own generative AI assistant, Microsoft 365 Copilot, this past spring, but Salesforce just threw its own Gen AI assistant into the ring at its annual Dreamforce 2023 conference. The next-gen Einstein technology will be added to every CRM app experience. So, what is Salesforce Copilot all about and how will this drive the next wave of growth for the company? To learn more about the new Salesforce features, keep reading.
Einstein Copilot: An eye on ease and productivity
So far, so similar. Salesforce’s new Einstein Copilot – much like the other generative AI assistants popping up in the tech marketplace – is geared toward both ease and productivity. In this case, system administrators can even customize how Einstein Copilot will work within their own company, including what data the app can access and reference. For instance, Einstein Copilot can:
● Create automatic account updates and sales emails based on specific context
● Auto-generate appropriate replies for customer service teams
● Create email text and website landing pages according to customer preferences
● Help create digital storefronts and catalog management
● Convert natural language prompts (NLPs) to code
● Personalize actions based on industry-specific needs, be it finance, healthcare administration, college admissions or sales.
If that all sounds a little familiar, it’s because auto-generation has been the name of the game since ChatGPT took the entire world by storm this past November. In fact, this past May, Salesforce announced its own partnership with ChatGPT founder OpenAI and the creation of Einstein GPT. How much more efficiently or differently Salesforce will be able to capitalize on the generational AI trend moving through the everyday enterprise is still to be seen.
Einstein Copilot Studio: Empowering the creation of AI models
Along with the announcement regarding Einstein Copilot, Salesforce also announced Einstein Copilot Studio, a generative AI tool that can be used to create, test, and deploy even more individualized LLMs without intense tech knowledge by using the studio’s prompt, skills, and model builders. For instance, using the tool’s Prompt Builder, an employee could ask to create a personal message, discount, and product based on a specific customer’s history and location. According to Salesforce, the studio is low-code and can be used across any CRM app or workflow.
Model builder will be compatible with Amazon Bedrock, Amazon SageMaker, Vertex AI, OpenAI, Anthropic, Cohere, and Databricks, with more likely to be announced in the future.
Salesforce Einstein Copilot: Data and AI working together
Salesforce is no stranger to data integration, and that may be its angle in the ultra-competitive generative AI field right now. Parker Harris, Salesforce co-founder and CTO, went so far as to say that a company’s AI strategy is only as good as its data strategy. In that sense, Salesforce may have the upper hand. Reports show almost 90 percent of Fortune 100 companies use an app associated with Salesforce, with the company’s global CRM market share a whopping 23 percent. The next closest competitor, Microsoft, sat at just 5.7 percent. That’s a lot of experience handling data and enabling companies to create value from it.
In fact, another Salesforce announcement, Einstein 1 Platform, promises major new developments for the Salesforce Data Cloud, all of which are built on the Salesforce metadata framework. Einstein 1 Platform will give businesses the ability to use any data to build AI-powered apps. That includes data across an enterprise, no matter how that data may be structured. In other words: companies will finally be able to make use of all the data they have to create maximum value through things like unified customer profiles.
A few Einstein 1 Platform promises: data at scale, automation at scale, analytics at scale. For instance, Einstein 1 Platform has grown to support 1,000’s of meta-data enabled objects per customer – with each holding up to trillions of rows. Huge amounts of outside data can be brought in and made immediately available as actionable objects. Flows can be triggered by any change on any object, at scale. And, solutions like Tableau, CRM Analytics, Reports and Dashboards, and Marketing Cloud Reports can all work together on the same data at scale.
Salesforce Einstein solutions: a new gold standard?
At Salesforce’s recent AI launch in New York City, the company was both optimistic and ambitious about its Generative AI roadmap. With pricing set, it was clear how Salesforce could incrementally see revenue growth through upselling its current customers and potentially attracting net new business based upon a powerful set of generative AI features.
And while It’s too soon to ultimately tell how Einstein’s new AI Copilot will compare or compete with others offered by Microsoft and other competitors, it is immediately clear that the move toward a more automated office is already here. Generative AI is allowing us to move beyond simple processes to automate real, personalized work. And, this will invariably improve customer experience and user experience on myriad levels with tools that don’t only drive sales, but also tools for marketing, service, collaboration, and more.
Overall, I’m trending positively on Salesforce’s strategy from its Einstein 1 Platform to its transparency as it pertains to responsible AI. Dreamforce maintained the company’s AI momentum, and showed the type of continued innovation that Salesforce customers must demand in an era where pervasive data and AI come together to drive the next wave of enterprise growth.
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