8 Types of Salesforce GenAI Roles You Need to Know About

Businesses are eager to explore how AI can boost their productivity, innovation, and revenue. There’s been acute interest expressed in the C-Suite on how to best incorporate GenAI and sustain its adoption. This excitement is also seen at other levels of the org chart (with the exception of some raising concerns). 

We’ve heard a whole host of announcements about how GenAI is being infused into the Salesforce platform. Technology is one fraction of the whole picture; to support the real-life implementation and adoption of the technology, a range of professionals is required. To kick-start their wave of GenAI transformation, Salesforce announced partnerships with Accenture and Deloitte, with more enablement programs in the planning. 

Now, other consultancies in the Salesforce space (and beyond) are skilling up their workforce to capitalize on the impending demand. 

Though it’s tough to say that anyone is an “expert” in AI, given the rapidly changing technological developments, the role of consultancies is to keep a pulse on the tools that can make a difference for your business and guide you along the way to successful adoption.

When you hear the term ‘consultant’, you will immediately think of those working for consultancies. But, reconsider the word, and you will see that many others act as consultants to other stakeholders in their organization. With that in mind, let’s be clear that when we say ‘consultant’ in this context, we could also be referring to the administrators, developers, and other players who recommend the optimal way for Salesforce to be enhanced for their organization. 

With consultancies and other organizations dedicating time and effort for their teams to learn, research, and apply gained knowledge on AI, ‘flavors’ of Salesforce AI professionals could emerge. A professional wouldn’t necessarily fall exclusively into one, and be excluded from others – after all, Salesforce career paths already blend together. This rundown is intended to show where these professionals’ strengths lie. 

So, what can be expected of these emerging ‘flavors’ of Salesforce AI professionals?

1. Low-code Salesforce AI Professional

This role involves:

• Maintaining Einstein GPT capabilities, and make further enhancements day-to-day. 
• Taking control over generated outputs for their users, through prompt engineering. 

Salesforce are ‘covering all bases’ by introducing Gen AI features across the platform – and delivering these capabilities in a way that is declarative (low-code) for those managing Salesforce orgs (namely admins) to master.

Salesforce Admins with their sights on Gen AI will be tasked with both maintaining Einstein 1 features and enhancing them for their user base in the long run. 

Salesforce wants to provide the ability for any admin to control how generative AI is deployed and used within their Salesforce orgs. Salesforce Admins will step up to the mark through a practice called ‘prompt engineering’ – the art of writing prompts to get the most optimal answer. As prompts are natural language queries (i.e. a user typing as they would in conversation), how a prompt could be written varies greatly from one person to the next.

Prompt Builder is looking to be the tool that will support admins in bringing better GenAI outputs to their users, enabling them to essentially create templates that keep prompts consistent, determining the data they should be grounded in, and testing for toxicity. 

2. Code Gen Salesforce AI Professional

This role involves:

• Writing code with Einstein GPT, with the ability to write quality prompts, tweak the outputted code, and detect potential errors.  

Salesforce developers can use the code gen capabilities Einstein for Developers (formerly Apex GPT) which offers to write Apex Code and LWCs. Salesforce’s own IDE, Code Builder, also has Einstein embedded.

This AI-conscious developer will be apt at writing code with Einstein at their side, being able to guide the AI assistant with quality prompts, tweak the outputted code until it meets the full requirements, and detect potential errors.  

This not only frees skilled developers up to work on more complex requirements but also guides those who are just starting to write code in line with best practices. 

3. Enterprise Architect/Consultant (Specialized in AI) 

This role involves:

• Working with the bigger picture by first working with the C-Suite on which commercial strategies the organization should be pursuing.
• Crunching the relevant numbers to identify use cases that align with the commercial goals.

Enterprise Architects/Consultants are typically placed in large client organizations to work with the bigger picture (a ‘helicopter view’) by first working with the members at the top of the org chart – the C-Suite, offering a fresh pair of eyes on what commercial strategies the organization should be pursuing.

You may have heard about Management Consultants, who are technology agnostic; however, with CRM being at the heart of any efficient organization, the client using Salesforce will scrutinize how it’s being used, and the opportunities its GenAI capabilities present to bolster commercial goals. 

Goals are, at times, not all about addition. There can be an element of subtraction that will enable the organization to meet its goals – for example, freeing up service agents from typing up case notes (and using summarization tools instead), will increase overall agent productivity. As a result, the service team will become less of a cost center. 

Armed with the objectives set by executives, and their perception when it comes to suggested improvements, they will crunch the relevant numbers to identify use cases that align with their commercial goals.  

The idea is that their recommendations will be implemented through the organization. This leads to where the next types of professionals (Technical Architects, Business Analysts, and Change Management Consultants) step in to continue the objective.

4. Technical Architect (Specialized in AI)

This role involves:

• Being responsible for planning how data goes in and out of Salesforce (both from and to integrated systems).
• Having the entirety of data available at the time the user wants to make a request via Einstein GPT’s Gen AI capabilities is key. 
• Determining the medium-term direction as to how Gen AI technologies, both within and relating to Salesforce are implemented – and keeping abreast of developments in regulation. 
• Overseeing the smooth operation of any large deployment. 
• Drawing up a roadmap for the next major phases of development.

Technical architects bring a data-led approach to Salesforce projects, responsible for data going in and out of Salesforce (both from and to integrated systems). These data streams are entirely different from one organization to the next, which means they design how the system will act as the wider, single source of truth specifically for that organization.

Becoming an architect at this level requires hands-on experience working with Salesforce (or equivalent) technologies, and understanding how Salesforce isn’t an island. 

Technical architects have an innate passion for technology, and are among the first to explore new technologies – they could have even picked up on GenAI before it ‘went viral’. 

We’ve heard Salesforce advocating for their golden trifecta: CRM + Data Cloud + AI. In simple terms, this hones in on the importance of having the entirety of data available at the time the user wants to make a request via Einstein GPT’s GenAI capabilities. While Data Cloud is mostly known for profile resolution and identity resolution, complete and good quality data is at the core of driving the most optimal GenAI outputs. 

So, where could Technical Architects play a key role? One possibility is in determining the medium-term direction of how GenAI technologies, both within and relating to Salesforce are implemented. I say ‘medium-term’ because technology is changing rapidly, as is the regulatory environment. Keeping abreast of developments in regulation is key, which has implications on how this new breed of technology could/should be reflected in the organization’s technology stack. 

Overseeing the smooth operation of any large deployment is also perfectly suited to Technical Architect. As they design the medium-term plan (‘medium-term’ for the reasons mentioned above), drawing up a roadmap for what the next major phases of development could be is part of this role (even if the technical vision imagined is suddenly thrown ‘out of the window’ with sudden changes/advancements!)

5. Business Analyst 

This role involves:

• Identifying stakeholder groups (usually teams of users), possibly sub-groups for pilots.
• Conducting a period of analysis, detailing the as-is state – meticulous understanding is key when implementing disruptive technology.  
• Reporting on usage to lay the foundation for further project phases.

Business Analysts have been described as the translators between the ‘business’ (the people who work at the company, and the processes they follow), and the technology (what they leverage to make the processes happen).

With the high-level objectives determined, the Business Analyst will first identify stakeholder groups (usually teams of users), which could include sub-groups for piloting GenAI capabilities, possibly determined by the users’ technical prowess. They then conduct a period of analysis, detailing the as-is state of how users interact with the technology.

This meticulous understanding is key to planning the implementation of disruptive technology, like Gen, properly – we don’t mean ‘disrupt’ negatively, but in a way that will significantly change the way people work. 

The Business Analyst keeps a close pulse on how the solution develops during implementation and is responsible for outlining how user acceptance testing (UAT) should be conducted – by who, testing what, and what the acceptance criteria is. With GenAI, outputs could be less predictable than a traditional solution, with many more variables (e.g. sources of data) at play. 

Their work doesn’t stop there. The Business Analyst will also report on usage, including compliant usage, to lay the foundation for further project phases.

6. Change Management Consultant

This role involves:

• Putting the ‘wheels into motion’ for GenAI technology adoption.
• Reassuring users who may be concerned or threatened by GenAI (‘bringing them on side’).
• Conducting training to help the user base up-skill.
• Instilling user-friendly guidelines for compliant usage.

Change management is a highly sought-after skill. Often the ‘last mile’ to tackle to bring an implementation to success, it can often be overlooked – but do this, and the likelihood is that your big investment will fall by the wayside. 

Change management is often listed as a skill by Salesforce functional consultants. However, this is a specialization in its own right, requiring emotional intelligence balanced with technical project awareness. In this case, there’s no blueprint to follow. 

Consider if an organization decides to introduce GenAI into Salesforce – the place where some people work day-to-day, where they’ve seen it boost their productivity – but now, are they concerned that GenAI technology could replace them?

For this type of ‘consultant’, their job is to put the wheels into motion to encourage long-term adoption of GenAI technology. This includes reassuring those who may be concerned or threatened by GenAI (‘bringing them on side’), teaching the concepts of GenAI in Salesforce and giving them the skills to work effectively with it, and instilling user-friendly guidelines for compliant usage. 

7. Marketing Strategist

This role involves:

• Being heavily involved with identity resolution and profile unification (via Data Cloud) which provides the solid data foundation that powers much of what’s generated by AI. 
• Being heavily involved with the AI-enabled tools that prospects and customers will interact with, e.g. chatbots and real-time interaction management (RTIM). 

In recent years, there’s been a phrase circling that “marketing owns the customer experience (CX)”. While strategists are required to implement AI into the workflows of other business functions, marketing stands out with its unique requirements – with more channels at marketers’ disposal and increasingly demanding prospect/customer expectations when it comes to digital experiences.

We’ve already mentioned Salesforce’s golden trifecta: CRM + Data Cloud + AI (emphasis added). CDPs, that take care of identity resolution and profile unification, are a breed of tools that started life in the marketing department.

Back then, it was marketing that was handling masses of potentially ‘raw’ or ‘dirty’ incoming data, and processing it to make it into something usable (i.e. activation). Now, other departments are working with more data than ever before, and Salesforce recognized this by bringing Data Cloud to the market – formerly their ‘Salesforce CDP’ that was part of Marketing Cloud, which forms the backbone of all products across their platform. 

Nevertheless, marketing remains drivers of the customer experience and will be heavily involved with the AI-enabled tools that prospects and customers will interact with. One example is chatbots, which will only become more sophisticated but need to be molded to the organization – context that the Marketing Strategist will possess. 

Another type of CX technology is real-time interaction management (RTIM). This gives organizations (especially marketers) the ability to promote relevant products and services to their customers and prospects across channels like web, email, and mobile in real-time with offers specifically and uniquely for them. There needs to be some form of CX strategy here to implement this successfully, otherwise, it would become a “garbage in, garbage out” situation, but exacerbated by automation via AI. 

Marketers will be able to use GPT-enabled tools for a host of tasks such as generating email copy, landing pages, and surfacing insights from analytics; however, the strategist would be interested in the quality of these outputs, how impactful these assets are, and opportunities for optimization (e.g. conversion rate optimization). 

8. ISV

• Understanding how LLMs (large language models) work, the best provider to support their application, and how to integrate that into their product.
• Identifying emerging use cases in their product category, and monitor how new GPT capabilities improve KPIs for their customers.

App vendors have been rushing to explore and develop GPT features into their offerings – and the Salesforce ISV partner network is no exception. 

ISV app builders typically have an in-depth knowledge of their product’s bespoke technology stack, the use cases they are catering to for their target market, and also the Lightning platform/Salesforce API framework (depending on where their product is run from). They will need to develop an understanding of how LLMs (large language models) work, the best provider to support their application, and how to integrate that into their product. 

Similar to other roles in this rundown, activities in this sector of the ecosystem will include identifying emerging use cases in their product category, monitoring how new GPT capabilities improve KPIs for their customers, writing up new testimonials, and other activities to remain competitive.  

Summary

By understanding and appreciating these different flavors of Salesforce GenAI roles, businesses can put themselves in a much better position to make the most of AI’s limitless benefits. 

Whilst achieving expertise in the AI field is difficult, many of these roles work cooperatively to give you the best opportunity to unlock AI’s truest potential and boost overall productivity.