Dreamforce 2023 is not your ordinary neighborhood gathering—but then again, Salesforce is not your typical company. It’s a realm where terms like “Triggered Flow,” “Copilot Studio,” “Einstein,” and “AI” serve as rallying calls that spark fervor among the Salesforce Trailblazers who gathered at this year’s event. But as a business owner competing in the high-tech industry, where over half of employers are concerned that a lack of critical skills hampers innovations within their infrastructures, what do Salesforce Skills Builder, Pardot, and CPQ have to do with helping your operations to flow better, employees to perform better, and customers to remain fiercely loyal to your brand? In a word, everything.
Imagine taking your operations up a notch by adding real-time data analytics and Generative AI technology. Utilizing premier AI-supported Salesforce CRM, core platforms like Sales Cloud and Service Cloud empower organizations to orchestrate end-to-end revenue-generating leads while orchestrating positive CX touchpoints throughout the customer journey.
With a centralized Customer 360 view, teams can deliver excellent customer service and resolve issues before they become a problem. In addition, Marketing Cloud and Einstein 1 will equip teams with the automated, AI-supported innovations they need to gain a deeper understanding of real-time data-driven customer personalization throughout the customer experience. Some say the anticipation of how Salesforce intends to leverage GPT was rivaled only by FooFighters fans’ arguably morbid fixation on the band’s new drummer. (Neither disappointed, by the way.) But is it safe?
It’s no accident that “Trust” messaging was displayed prominently throughout the Dreamforce campus. These days, companies that hype their mad generative AI implementation skills are as commonplace as a venti-sized pumpkin spice Frappuccino. The rocket-propelled ascension of applications like ChatGPT has forced businesses to address the far-reaching impact of this tool. Salesforce understands the concern.
“Due to the need for GenAI technology to be grounded in security, ethics, and human oversight, when bringing any GenAI innovations to the market, Salesforce have been thoughtful in their design,” Lucy Mazalon, a Salesforce marketing expert and founder of The Drip, explains. “The challenge has been to keep GenAI outputs contextual to your organization’s data, without sending that data outside of your trusted boundary – whether that’s your Salesforce org, or through secure gateways with other large language model (LLM) providers your organization wishes to leverage.”
Mazalon points out that for Salesforce to remain compliant at every turn, it has built a Generative AI Gateway, which channels inputs through before going out to other LLM providers.
“When a user writes a prompt from the Salesforce UI that’s intended for an external LLM your organization has connected, it’s passed via the Connect API to the gateway. Here, pre-processing occurs (the Einstein Trust Layer), including PII masking so that sensitive information doesn’t leave the boundaries of your Salesforce org. Only then is the request routed to the appropriate handler,” Mazalon says.
Almost every company (99 percent of those polled) understands it must take measures to use generative AI responsibly. However, most IT leaders admit that their organizations aren’t prepared to deploy it yet. Providing a secure platform lies at the core of the Einstein 1 platform to ensure secure user connectivity. Einstein Copilot Studio offers process retention for generative AI deployment and integration and Data Cloud-triggered flow. This resource leverages real-time data with enhanced collaborative data systems. Let’s discuss briefly how these new features successfully navigate generative AI and elevate the functionality of Salesforce Cloud systems for the rapidly evolving high-tech industry.
Salesforce introduced the Einstein 1 Platform, an AI platform that offers secure connectivity for AI-driven application development, allowing the integration of diverse data sources, and includes both legacy and contemporary systems. It incorporates functionalities from Salesforce Data Cloud, Einstein AI, and the foundational Salesforce metadata framework, as detailed by the vendor. Einstein 1 accommodates many metadata-enabled objects per customer, each capable of containing many rows. Customers have the flexibility to import data from external systems and present it as actionable Salesforce objects. They can activate flows via Data Cloud in response to any changes across various objects, whether from an internet of things (IoT) device, a computed insight, or an AI prediction, all at a substantial scale.
It’s a big deal because customer data is highly fragmented, which also begets vulnerability. Salesforce found that the average organization uses around 1,061 different applications, yet only 29 percent are integrated. Another study found that only 32 percent of companies use a “single source of truth” for customer data. Enterprise data infrastructure has become increasingly intricate, and previous technology revolutions—such as cloud computing, social media, and mobile devices—have created extensive, isolated customer data repositories.
When companies rely on a collection of siloed systems to house data, a complete customer profile is improbable. This sensitive information depends on the security of that software or device for protection, which can vary depending on the system. The key to efficient operations and better CX isn’t piling up more data. Instead, it is leveraging your database with tools that enable secured access and provide complete profile information to understand their customers better and channel resources where they will create the most impact.
The Einstein Copilot Studio platform allows administrators and other Salesforce experts to deploy potent generative AI solutions to enhance user productivity while maintaining control over the selection of processes for generative AI implementation and the depth to which prompts are integrated. Three components work collectively in these processes:
Construct prompt templates, define their connection to Salesforce data, and swiftly and effortlessly enable them for users. In simpler terms, design, assess, and implement generative AI prompts for your users.
Authorize access to generative AI within the Salesforce platform using “skills.” For instance, you could specify that for process A, user X should possess specific generative AI capabilities, while user Y should not have the same privileges. An administrator or a similar professional can incorporate a “skill” into a Salesforce flow.
This component allows users the freedom to choose the AI models of their preference, whether it’s Salesforce’s proprietary large language models—which Salesforce has diligently trained over the years—or one of their recommended collaborators, such as Anthropic, Cohere, Databricks, Google Cloud’s Vertex IX, or OpenAI. Einstein Copilot seamlessly integrates with every Salesforce application, allowing users to inquire using natural language and receive dependable answers derived from secure proprietary company data within the Salesforce Data Cloud.
An automated system is only as good as its data. The right technology empowers users to gain valuable insight from real-time data. For instance, by segmenting desired data points or processes into customized categories, Salesforce Flow enables users to assess product performance, browsing behavior, purchasing history, product inventory, and channel preferences for customer support, then trigger an appropriate response and automated action. The three-pronged Dreamforce 2023 formula for success is Data+AI+CRM. However, the possibilities this robust AI-backed data-driven platform presents to users are limitless. To learn how these Salesforce innovations can elevate your business, let’s chat.