AI is all-pervasive. The penetration of Artificial Intelligence (AI) and Machine Learning (ML) is increasing the intelligence quotient in enterprise software applications in every sphere and across all industries.
The next wave of AI may very likely be characterized by its deployment into dedicated application types, with software engineering and algorithmic power aligned to serve more specifically segmented tasks – rather than it ‘just’ being data-driven smartness capable of collating and analyzing information of any general type.
Cloud-centric Customer Relationship Management (CRM) company Salesforce is following (the company would no doubt say leading) this trend with its launch of Einstein GPT, a generative AI CRM technology designed to deliver AI-created content across sales, service, marketing, commerce and IT interactions.
What GPT means
Employing the now-customary use of GPT from the deep learning human language training model of the same name (as in ChatGPT), the acronym itself stands for Generative Pretrained Transformer, with the generative aspect here being a statistical classification that denotes the nature of system behavior. Salesforce promises that Einstein GPT will transform every customer experience with generative AI.
But how does it work?
Einstein GPT infuses Salesforce’s own proprietary AI models with generative AI technology from a group of partners and real-time data from the Salesforce Data Cloud (a cloud computing service built to organize and unify data from a customer’s Salesforce use cases and third-party sources as well) to ingest and harmonize all of a company’s customer data.
Crucially then, at that point, with Einstein GPT, customers can then connect that data to advanced AI models operated by OpenAI, the US research laboratory behind ChatGPT. Customers can connect to OpenAI’s AI models out of the box (i.e. directly from this Salesforce service) or choose their own external model. They can then use natural-language prompts directly within their Salesforce CRM to generate content that continuously adapts to changing customer information and needs in real-time.
Specifically, to clarify what is happening here, Salesforce is combining OpenAI’s enterprise-grade ChatGPT technology with Salesforce’s own private AI models to deliver what it insists is both relevant and trusted AI-generated CRM content.
For example, says Salesforce, “Einstein GPT can generate personalized emails for salespeople to send to customers, generate specific responses for customer service professionals to more quickly answer customer questions, generate targeted content for marketing people to increase campaign response rates and auto-generate code.”
Einstein GPT in CRM
Created all the way back in 2014, Einstein GPT is the next generation Salesforce’s Einstein AI technology. The company measures Einstein’s processing workload and says that it is currently delivering more than 200 billion AI-powered predictions per day. By combining proprietary Einstein AI models with leading large language models, customers can use natural-language prompts on CRM data to trigger time-saving automations and create personalized AI-generated content.
In terms of the actual services now being launched, the product set breaks down as follows: Einstein GPT for Service – enables users to generate knowledge articles from past case notes and auto-generate personalized agent chat replies to (attempt to) increase customer satisfaction through personalized and expedited service interactions; Einstein GPT for Sales – auto-generate sales tasks like composing emails, scheduling meetings and preparing for the next interaction; plus additional Einstein GPT services for marketing, for Slack to deliver AI-power in Slack like smart summaries of sales opportunities and background research on accounts.
There’s also Einstein GPT for Developers to improve developer productivity with Salesforce, because software application development underpins the entire tale here, obviously.
Where will generative AI work?
It’s a burgeoning field, clearly. Not only is AI usage increasing its penetration in enterprise software, it is also widening its scope into industry- and use case-specific application models as we see here in CRM. Studies into generative AI suggest that most IT managers think this technology will improve customer service, enable their teams to work better with data and also be able to operate workflows more effectively.
Perhaps most importantly of all – because of the absolutely core and fundamental fact that we know that AI is only ever as smart as the datasets we expose it to and the data models upon which it runs – IT leaders already agree that generative AI should combine public and private data sources, as is the case here.
What would Albert Einstein himself make of all this?
He would remind us that it was he himself who said, “The only source of knowledge is experience.”