The Impact of AI on the Salesforce Ecosystem: Key Takeaways
The Dreamforce buzz may have settled, but artificial intelligence (AI) is poised to revolutionize the future of work within the Salesforce ecosystem. According to the IBM State of Salesforce 2023-24 report, AI emerged as a pivotal trend. This new wave of generative AI stands out from previous iterations.
This new wave of generative AI brings a distinct feel. Following a 2016 acquisition spree, Salesforce introduced “Einstein” products like Opportunity Scoring, Forecasting, Conversational Insights, and Bots. While they likely yielded ROI for some, they may not have been truly groundbreaking.
Executives in the IBM report emphasize a departure from settling for small gains in generative AI. They’re actively experimenting with use cases to boost profitability and allocate resources towards high-value, customer-centric tasks. Prior to this AI wave, Einstein products enhanced user productivity and ROI, but their impact on the bottom line may not have been anticipated by leadership.
Notably, 75% of CEOs see advanced gen AI as a key competitive advantage, with 50% incorporating it into their products and services, and 43% using it for strategic decision-making. The influence of generative AI on companies in the Salesforce ecosystem is currently tangible, not just theoretical.
AI in the Salesforce Ecosystem
In the Salesforce ecosystem, getting ahead with generative AI requires careful consideration and strategic planning. Before delving further, it’s crucial to identify the key areas of impact:
Internal Salesforce users: One major application of generative AI in the Salesforce ecosystem is with internal users, particularly with the newly introduced Einstein 1 powered toolset. IBM identifies a group of users as “pioneers” who are extracting the highest ROI from Salesforce. They anticipate enhancing nearly 15% of their workforce with generative AI tools in the coming year.
Sales Cloud users will benefit from AI generating sales emails based on contextual account details and history. Service Cloud users can expect a similar feature called service replies for automated customer case responses. This functionality also extends to Marketing Cloud, Commerce Cloud, Tableau, and Slack.
External customer-facing tools: Next, we have customer-facing tools that operate independently of Salesforce. Examples include Einstein Bots and Commerce Concierge, leveraging bot technology and generative AI to assist shoppers on e-commerce platforms.
This area is a significant priority for Salesforce, evident in their recent acquisition of Airkit.ai. Airkit.ai, a commerce-centric GPT-4 powered bot, pledges to instantly resolve 90% of customer queries. Stephen Ahikian, the founder, highlighted in a press release that customer satisfaction is currently at a 17-year low, with call teams experiencing heightened stress levels—an experience many can relate to.
Interestingly, IBM’s identified “pioneer” group places a greater emphasis on customer-facing operations. In contrast, the “pensive” group (opposite of pioneers, yet to complete their digital transformation) focuses more on internal operations.
AI-powered development tools: Generative AI’s impact on software development is widely discussed. The revelation that tools like ChatGPT can generate code in various languages, including Apex, sparked both excitement and some apprehension. This led to the question: will artificial intelligence replace Salesforce professionals?
Ultimately, the answer is no. However, there are numerous tools that can augment the workflow of a Salesforce professional. These include developer-focused tools like GitHub Copilot and Einstein GPT for Developers (recently launched), as well as Admin-centric tools like Copilot Studio and Prompt Builder. Additionally, the upcoming Flow GPT will allow admins to easily build flows with a text prompt.
AI is making significant strides and not only enhances user productivity but also potentially reduces development time, enabling faster deployment of new Salesforce features.
Implementation of generative AI: Now, onto a crucial but often overlooked aspect: who will be tasked with implementing this exciting emerging technology?
In typical Salesforce fashion, they’ve established a range of no/low code tools to support their generative AI revolution. These tools reside within the new Copilot Studio hub, housing features like the Prompt, Skills, and Model Builder. They essentially allow you to create templated prompts for specific use cases.
These features will be accessible across the Salesforce ecosystem, with a clear emphasis on catering to internal Salesforce Admins. However, for larger, more complex Salesforce organizations that may opt for a blend of LLM models, including custom ones on platforms like Amazon Sagemaker, implementation partners may be necessary.
While Salesforce partners are the initial go-to choice, it’s possible that smaller, specialized Salesforce partners might lack familiarity with tools like Anthropic, Cohere, Amazon Sagemaker, etc. With 61% of “pioneers” in the State of Salesforce report expressing interest in capabilities beyond out-of-the-box generative AI, there could be a market gap for Salesforce partners to address.
Crafting Your Salesforce AI Strategy
Getting excited about AI and its groundbreaking features from Dreamforce ’23 is natural, but a strategic approach is essential.
1. Start with understanding use cases within your organization and how AI can enhance them. Follow a two-step approach for discovery
- Organizational discovery: Identify your company's unique attributes and prioritize organizational goals over the next few years. This aligns your efforts with the company's overall strategy.
- Use-case discovery: Examine individual roles, processes, and tasks where AI can augment operations, with a focus on addressing significant challenges and pain points.
2. Once vital use cases are identified, embark on experimentation. As per IBM's report: Pioneers are leading the way, experimenting with generative AI to boost overall profitability.
3. IBM suggests the following action points for generative AI:
- Initiate action immediately; pioneers are diving in to gain a competitive advantage and to grasp the full potential, challenges, and limits of generative AI.
- Aim beyond just improving current operations. Generative AI offers transformational potential that extends beyond current use cases and will endure beyond the generative AI hype cycle.
- Design intelligent workflows with a holistic impact. Envision how generative AI can benefit the entire enterprise. Organize workshops involving your CIO and CMO to define clear business cases, data sources, and strategies to mitigate potential risks and barriers associated with transformative technology.
Artificial intelligence stands as the prevailing technology, hailed by thought leaders as the most significant shift in technology to date. It's crucial not to overlook CRM basics.
IBM offers additional insightful strategies for optimizing Salesforce ROI among top performers. These encompass trends like Salesforce Industry Clouds, data integration, fostering an adaptable culture, and breaking through enterprise inertia with innovation.
Download the IBM State of Salesforce 2023-24 report for a deeper dive into how these innovations can elevate your Salesforce practice.