CONTRIBUTOR
Chief Content Officer,
Techstrong Group

The ability to employ a natural language to create a business process may seem like a work of science fiction, but starting today Salesforce is making it a reality. A Flow platform that Salesforce makes available is now infused with generative artificial intelligence (AI) capabilities that makes it possible for any user to describe a business process that the Flow platform will automatically generate.

That capability eliminates the need to use a low-code or no-code tool to craft a workflows process, says Liam Doyle, senior vice president for MuleSoft automation at Salesforce. Instead, the scaffolding for that process is now automatically generated by the Einstein AI platform developed by Salesforce, he notes.

Organizations should also expect AI to play a role in process mining to enable organizations to more easily discover how a process might have evolved before using Einstein to revamp it, adds Doyle.

“It’s only chapter one,” says Doyle. “It gives everyone superpowers.”

Generative AI has captured popular imagination since Microsoft began making a platform developed by OpenAI widely available. Salesforce, however, has developed its own generative AI platform that it now embeds within Einstein.

Salesforce previously announced embedding Einstein GPT across its application portfolio, including its customer service and marketing platforms in addition to its Slack messaging platforms.

Fundamentally, generative AI changes the way humans interact with machines. Instead of requiring a developer to create a level of abstraction to communicate with a machine, it’s now possible for machines to understand the language humans use to communicate with each other. That makes it possible for anyone to make use of the large language models used to create generative AI platforms to, for example, create a workflow by merely describing it in natural language. Best of all, the person who is the subject matter expert for that process can iterate on the results provided by a generative AI platform to continually fine tune it.

The impact that capability is going to have on productivity should be profound. Despite the trillions of dollars that have been invested in IT over the last five decades there have now been major gains in productivity since the PC was first introduced. Generative AI should enable individuals to perform a much wider range of tasks without having to rely on a specialist to, for example, construct a website.

It may be a while before those gains are reflected in gross domestic product (GDP), however, because of the level of disruption that might ensue as many tasks that once required a specialist can now be performed by just about anyone.

It’s too early to say how many jobs will be impacted by generative AI but as William Gibson noted, the future is already here; it’s just unevenly distributed. In the meantime, organizations would be well-advised to build a strategic plan now that thoroughly examines how each function within their organization will be impacted by generative AI both today and tomorrow. After all, the number of generative AI platforms that are designed to automate specific tasks is only going to increase in the weeks and months ahead.