Urelevant

Generative AI is going to fundamentally change how work gets done in this next quarter of the century. We're entering into the year 2025 in just a couple of months at the time of this recording, which I like to call Q2 of 2K. I'm seeing a lot of profound implications as we're now starting to get our hands on AI inside Salesforce. Salesforce has opened up access to their Einstein platform in various ways, including learning platforms and demos.

With this access and an understanding of the Salesforce platform—how work is done or has been done in the past—we can start to envision ways of doing things more efficiently in the future with the help of AI. The intended use case that Salesforce provides is to accentuate and augment our abilities, not to replace us entirely.

What's really interesting to me about this encroachment of AI into the workspace, especially on the front end of Salesforce, is that it is redefining how we do work. This will redefine our standard operating procedures and, at a very high level, some of the tried-and-true processes baked into Salesforce from the beginning, such as the lead conversion process and the management of opportunities. These processes can and will change more with AI integrated into the platform.

One example I've recently been experimenting with is the approach to the lead conversion process. If you've worked in Salesforce, especially on the marketing side and dealt with lead qualification, you know it can support multiple lead processes depending on the types of products and services you're selling. This includes different lead status designations as you go through the lead qualification journey. Certain data points must be captured along the way. At some point, when you want to hand the lead over to the sales department, you perform what is known as a lead conversion.

In the past, a lot of customizations were required, such as custom field-to-field mappings from the lead object to contact, account, and opportunity. Those of you who have studied with me for the administrator exam, for example, are highly familiar with that process. For those of you newer to this, the main point here is that the journey or lifecycle of a customer with a business typically starts as a lead inside Salesforce. At some point, it is converted into an account, contact, and opportunity.

All the data points captured on the lead record transform and carry over into the resulting object records. For example, the company name on the lead becomes the account name. Recently, I’ve been experimenting with Einstein-enabled tools to create a summary field as a hybrid prompt template. Currently, there are only a handful of prompt templates available on the platform, though I anticipate their number will grow significantly over time.

There are two prompt templates worth mentioning here at a high level. The first is the field generation template, which enables you to generate text inside a field using generative AI. The second is the summary template, which summarizes records. The latter is available out of the box on most object records. For example, you can prompt the AI to summarize an account or opportunity.

The summarization capability of generative AI is one of its strengths, which is why it’s one of the first prompt template types available on Salesforce. Imagine lead records with dozens, if not hundreds, of fields and data points. Mapping all these fields from lead to contact, account, and opportunity can be cumbersome. Salespeople, however, often need a summarized version of that data instead of searching through countless fields. A summarized lead record in just a few paragraphs could streamline the lead conversion process dramatically.

One practical implementation of this approach involves creating a custom long-text area field on the lead object and corresponding fields on contact, account, and opportunity objects. On the lead side, you could create a field generation template, update the lead page layout to a dynamic form, and enable generative AI through Einstein for that field. The AI could then generate a summary of the lead record and populate the field. This summary could be automatically mapped to the corresponding fields on the contact, account, and opportunity during the lead conversion process.

Additionally, you could set validation rules to ensure the summary field on the lead is not null before conversion. This would compel users to generate a lead record summary before conversion. Alternatively, you could enable generative AI on multiple fields for summarization purposes. At most, you’d need three AI-enabled fields—one each for contact, account, and opportunity summarization—populated on the lead side and mapped during conversion.

This high-level overview highlights how the lead conversion process can evolve with AI. I see this as a repeat of history: technology advancements prompting us to rethink our approaches. As we move into the second quarter of the 21st century—Q2 of 2K—AI will likely continue to transform how we work.

Recently, during a discovery call, I was reminded of how often we inherit Salesforce instances and wonder why things were done a certain way. Sometimes, the explanation is as simple as, "It was the only option available at the time." The advancements in the Salesforce platform—such as the shift from profiles to permission sets, the introduction of dynamic forms and pages, and now generative AI—force us to rethink our solutions. This virtuous cycle of technological progress, reimagined procedures, and new platform capabilities is what makes Salesforce so adaptable.

As generative AI continues to advance, it will impact not just the front-end user interface but also back-end processes. We'll save that discussion for a future episode. Thank you for joining me for this sneak peek into Q2 of 2K and the transformative potential of generative AI in the workplace. Please subscribe, like, and share this podcast so others can also find relevance in the economy of now and next.