The News: Salesforce has announced that it is integrating Einstein GPT into its Flow workflow automation suite and tightening the integration between its CRM data platform Data Cloud and Flow, the company’s automation toolbox. The Einstein GPT, Data Cloud, Flow integration should make it possible for users to be able to create and modify automated workflows using conversational instructions. Read more from Salesforce.
Salesforce to Integrate Einstein GPT and Data Cloud Capabilities into Workforce Automation Suite Flow
Analyst Take: Salesforce’s announcement of the coming integration of Einstein GPT, the company’s generative AI CRM technology, and Data Cloud, which is intended to be a single source of truth for data and interactions for all customers across all channels — into Flow, its workforce automation toolbox — is great news for customers. From my perspective, it’s yet another move evidencing that pretty much all the Big Tech players are laser-focused on all things generative AI and exploring ways to integrate this technology into their solutions and are wasting no time doing just that. We’ve got Microsoft and its Dynamics 365 Copilot, Pega’s integration of gen AI tools into its Pega Infinity solution, and Adobe’s launch of Firefly, to name just a few.
As it relates to Salesforce and the integration of Einstein GPT and Data Cloud into Flow, it’s all about providing a solution that’s easy for non-technical users to quickly and easily use by way of an interface for automation that’s conversational rather than technical. The ultimate goal is simple, and all about helping customers more quickly adapt to their customers’ online behavior and provide them with the ability to create more personalized experiences more rapidly — all without burdening IT to make it happen.
Einstein GPT for Flow — How it Works
By integrating Einstein GPT, launched in March into Salesforce’s Flow workflow automation suite, users will be able to create and modify automated workflows in a super easy way, which should facilitate even more rapid adoption throughout an organization. For example, users can simply describe what they want from a workflow, and Einstein GPT for Flow will build it for them, in no time. The same is true with formulas and searchability, with users having the ability to describe what they want and/or what they’re looking for, and Einstein GPT will build and/or find what they’re looking for. At a time when generative AI can seem a little intimidating to many in the workforce, this kind of functionality is easy to get excited about and should no doubt spur adoption.
Einstein GPT can also be trained with a company’s own data from its existing customer relationship management system and other sources.
Salesforce Data Cloud for Flow — How it Works
Salesforce Data Cloud, which maintains real-time customer data profiles, is an equally important part of the equation for customers. Data Cloud for Flow links the customer’s workflow automation with structured and unstructured data stored in a lakehouse, a cross between a data lake and a data warehouse. Since the goal of an organization when it comes to data is being able to gather, store, manage, and glean insights from data to drive decision-making, that’s where the integration of Data Cloud and Flow is significant.
Using Data Cloud and Flow, Customers can combine data from Salesforce’s databases — and other sources — to bring in-line customer views and apply low-code tools to create automated processes and workflows. Prior to the integration, customers could get data out, but it required the services of a developer and the writing of a fair amount of code to make that happen. With this move, Salesforce can support non-technical users, of which there are many, who will be able to automate based on triggers in data from Data Cloud and other places.
As a use case example: think about e-commerce and abandoned carts. This functionality will allow the automation of a triggered, personalized response, reminding customers about unfinished business and helping to close interrupted sales. This kind of functionality isn’t new, but Salesforce claims that with Einstein GPT and Data Cloud, this process becomes more speedy and more personalized, and is specifically tailored to the customer. Some additional use cases include manufacturers using Data Cloud for Flow to monitor machine performance in real-time, financial services customers using it to automate fraud detection and identify anomalies quickly, and marketers and e-commerce pros can use the data at their fingertips to serve up discounts, adjust inventory information in real-time, and optimize every part of the retail experience, whether in-store or online.
Salesforce also announced new Data Cloud partner apps and experts including Apisero, an NTT DATA Company, Atrium, DeciZone, Infosys, Persistent, smrtr, and Wipro among some of the new partners. The pre-built apps and consulting expertise offered by these Data Cloud partners will help companies with their real-time data strategies to deliver an enriched customer experience.
Wrapping up, Salesforce’s integration of Einstein GPT and Data Cloud capabilities into Flow is not only a smart move, I see it as a table stakes move today — especially for a company with arguably one of the largest CRM customer bases. Providing the ability to help customers easily leverage AI, data, and CRM by simplifying the process, taking the reliance on IT out of the equation, and democratizing the use of the power of AI throughout the organization is the path to speeding adoption and use.
When can we expect to see this in market? Salesforce shared that these features will be available as a pilot in the winter 2024 release, which seems somewhat far off, all things considered. Salesforce says the Data Cloud integration will probably be offered as part of a standard Salesforce subscription. Einstein GPT for Flow may carry an additional charge, but details have not been determined. Here’s hoping the team at Salesforce can get this into overdrive and customers can start seeing the benefits these capabilities will serve up.
Disclosure: The Futurum Group is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article.
Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of The Futurum Group as a whole.
Other insights from The Futurum Group:
Microsoft Copilot: Unlocking Productivity in Microsoft 365
Adobe Announces Generative AI Solutions Across Adobe Experience Cloud at Adobe Summit
The Power of the CDP: How to Maximize Insights for Better Customer Experiences
Author Information
Shelly Kramer is a Principal Analyst and Founding Partner at Futurum Research. A serial entrepreneur with a technology centric focus, she has worked alongside some of the world’s largest brands to embrace disruption and spur innovation, understand and address the realities of the connected customer, and help navigate the process of digital transformation. She brings 20 years' experience as a brand strategist to her work at Futurum, and has deep experience helping global companies with marketing challenges, GTM strategies, messaging development, and driving strategy and digital transformation for B2B brands across multiple verticals. Shelly's coverage areas include Collaboration/CX/SaaS, platforms, ESG, and Cybersecurity, as well as topics and trends related to the Future of Work, the transformation of the workplace and how people and technology are driving that transformation. A transplanted New Yorker, she has learned to love life in the Midwest, and has firsthand experience that some of the most innovative minds and most successful companies in the world also happen to live in “flyover country.”
