Salesforce Spreads NLP-Enabled Einstein AI over Most of Its Apps
SAN FRANCISCO — Salesforce’s Dreamforce conference, the largest tech show in Northern California in terms of attendees each year, this week was billed as the “largest AI show in the world.” How a designation like that is determined is unclear, but most products showcased and seminars staged did, in fact, touch on AI in one aspect or another.
Interesting sidebar: The term “AI” was questioned by a guest speaker, Williams-Sonoma CEO Laura Alber, who claims that “artificial” is a misnomer, because the intelligence in AI apps is real and based on data.
“I’ve been thinking about this a lot and I actually was pretty inspired by Parker (Salesforce co-founder Parker Harris) and his resetting of what artificial intelligence really means,” Alber said. “And the truth is that when it comes to customers, there can be nothing artificial about the experience. So as we use AI, we use it to inspire and improve the experience. We need to make sure that it’s completely authentic.
“So I wonder about a name change today. I wonder if it’s just called ‘intelligence,’ or as Parker said, ‘data intelligence.’ And I think we should stop thinking about the definition as artificial when it comes to the customer experience.”
So there you have it. We may be calling this phenomenal software running bots and “copilots” — as Salesforce describes its intelligence agents — something completely different in the near future if “AI” is generally found to be too limiting a term.
Salesforce’s Einstein AI had plenty of news in its orbit this week at the Dreamforce event that ended Thursday and was expected to have attracted 40,000-plus humans to downtown San Francisco — not to mention upward of 150,000 more online.
Einstein Copilot
This is Salesforce’s newly minted AI-powered application that enables line-of-business users to talk to their CRMs — literally. Its NLP-enabled interface prompts the assistant, which then uses AI to generate trusted and accurate recommendations and guidance based on the customer’s database of information in the CRM.
Einstein Copilot works alongside employees to accomplish tasks of all types. “It’s very good at drafting emails,” Salesforce CEO/co-founder Marc Benioff said. “But it also does a lot more than that.” Copilot also can create PowerPoint presentations, marketing materials and pitch letters. It also can be queried on things such as:
- “Give me tips for reducing average customer service call time”
- “Calculate the best discounts to move old merchandise fast”
- “Help me prepare for this meeting with all the right details”
- “Create personalized product promotions”
With a tireless automated assistant like this, who needs a regular assistant? (Yes, that is a legitimate question now being asked all over the enterprise world.)
Copilot Builder
Copilot Builder empowers developers and line-of-business employees to customize their Copilots with prompts, unique skills and models. Users can build specific Copilots for individual customers and tasks. The platform enables admins, developers and IT teams to build a secure conversational AI assistant that answers questions, reasons and takes action to accomplish specific tasks for employees, Benioff said. Copilots are pre-trained on proprietary and secure CRM data to deliver relevant and trustworthy content, tailored to a brand’s unique identity and needs, Benioff said.
Einstein Trust Layer
This new security attribute provides configurability for managing sensitive data in addition to a compliance-ready audit trail to keep companies in control of their data. CFOs and CISOs alike will like those features.
The new Einstein Trust Layer is integrated into every Einstein Copilot by default. It is compliance-ready to allow companies to retain control and gain visibility of how their data is being used with their chosen AI models.
PII is protected by default, and the Trust Layer is fine-tuned to score and record every AI response for employees to understand whether a response is safe to use.
Defining ‘Decision Science’
“Decision Science” is a term that was brought up in presentations at Dreamforce, mostly in connection with the company’s new Data Cloud — which is a kind of home plate for all the company’s applications. Salesforce exec Janani Narayanan described this new sector of IT as focusing on using data and AI to drive decisions across an organization to maximize sales pipelines and ACV (annual contract value).
“Whether we are making a strategic decision with analytics or an automated decision with marketing automation, we strive to use data and AI responsibly to grow our business and improve the customer experience,” Narayanan told The New Stack.
Narayanan, whose full title is Salesforce Senior Director of Product Management in Digital Intelligence Automation, said that “before Data Cloud, Salesforce’s suite of products were built to deal with mostly transactional data. The addition of Data Cloud allowed us to complement our existing transactional database with the ability to take in massive volumes of data from across CRM, web, mobile and APIs.”
Last Dreamforce in San Francisco?
Dreamforce has been staged at Moscone Center since its inception in 2003 — except in 2020, the first year of COVID-19 (2021 and 2022 were hybrid in-person/online events). This year’s event may turn out to be the last one to be held in San Francisco’s largest convention facility; the jury is currently out on that topic. Salesforce will make a decision in the next few weeks as to where the huge conference will be held in the future.
This is because Benioff has been unhappy with his native city’s approach to finding additional housing for its average of 4,400 homeless people sleeping on the streets each day. San Francisco Mayor London Breed was in the first row for the opening keynote and was introduced by Benioff to the audience.
OpenAI Founder on ChatGPT Success
OpenAI CEO/co-founder Sam Altman had some stage time on Day 1. When asked by Benioff in a 1:1 interview at a packed Yerba Buena Theater what was “the biggest surprise” he saw out of all the hoopla around ChatGPT, Altman replied simply: “That it’s all working.”
During his 37-minute session, Altman said “When you start off on a scientific endeavor, you hope it will work; you let yourself dream it will work. We knew we had a lot to figure out, and figuring out any new science is always hard. We had conviction and a path laid out by our chief scientist, but how do you have conviction and then actually get it to work? There was pretty much a consensus in the outside world that it wasn’t going to work, but we secured the effort and made it work. That probably was the biggest surprise.”