Recently, the Protiviti Salesforce team attended the NY World Tour Agentforce event which provided a vision for Agentforce. Salesforce’s Agentforce, first introduced last fall, is an AI application that allows companies to create and manage AI agents across the organization, orchestrating across both custom and out of the box workflows built on a Salesforce platform. To scale, companies can further leverage Data Cloud to enrich agents with real-time customer data and industry insights. Connections to external sources allow agents to scale as the database grows and companies’ customer portfolios expand, enabling firms to manage increased interaction volumes without compromising service quality. By providing a low-code, citizen developer interface, Agentforce accelerates the transformation to agentic AI. Rather than creating an entire application, organizations need only outline the building blocks and guardrails and allow the agent to figure out the rest (of course, with a little help and oversight from humans first).
We believe 2025 will see a spike in AI agents supplementing human workers, allowing people to focus on more strategic or higher value tasks. In anticipation, Protiviti recently launched accelerators to simplify agent implementations and ensure the agents function as intended.
Start simple with high-value quick wins
Selecting the right use cases for AI agents is key for any organization. The most common initial Agentforce use cases we see are centered around operational wins like automating invoicing, procurement activities and first-line customer support as the most attainable and highest impact for deployment complexity.
In an initial Agentforce implementation, we recommend companies focus on processes with the most cost-saving potential, typically larger and perhaps more repetitive functions that can be easily automated. In financial services, where relationship management is a key driver of revenue, an agent that dynamically summarizes portfolio activity on the home page is a quick operational win – but its standalone value is limited. Extending it with a knowledge agent that surfaces real-time news relevant to the client’s holdings drives significantly higher ROI by reducing research time. Better yet, this data stream can be implemented quickly using low-code, seamless integration.
AI agents can scale dynamically, allowing organizations to scale operations without significantly increasing their workforce; over time, this unlocks higher ROI from agents as they start to work seamlessly in tandem with humans.
The best way to stay up to date and capitalize on AI agents? Get hands-on experience building agents and start a few quick wins that tangibly demonstrate the value of AI agents – which is the best way to enable growth and success in today’s competitive landscape. By showcasing the operational value of these agents, companies can effectively illustrate to their boards how agentic AI-driven solutions contribute to tangible improvements in customer experience, operations, and knowledge and dynamically scale with company growth. On the customer side, more personalized and timely interactions lead to higher satisfaction rates. These advantages, in conjunction with a low barrier to adoption, can be key differentiators in a crowded market.
Future proof data
A core enabler for Agentforce success is ensuring the organization is built upon solid data assets. As such, an initial architecture review should prioritize access control, user privacy and data accuracy. Beyond the obvious benefit of faster implementation, a strong data governance culture establishes trust with customers and allows the business to meet compliance policies that are constantly changing to address this apprehension.
Much like with analytics and other data use cases, context to the data being used is key. Within agentic AI, this context is provided by giving descriptions to the AI on what each field does and context to proper and appropriate use. This data about data (aka metadata) helps the agent make better choices, much like a data dictionary or business glossary helps a human user better understand the data they are leveraging.
Salesforce is broadening its presence in the CRM ecosystem by frequently adding more external connections to Data Cloud. The increasing demands for data residency and compliance in multinational operations means companies should begin by locating their source of truth data sources and determining which fields within those data sources are relevant for Data Cloud and the agent, and which will enrich current data sources. Data Cloud’s strategic data management tools guarantee a more scalable and secure implementation of Agentforce in the long run.
Ultimately, the integration of agents within Salesforce positions firms to leverage automation for sustained growth and success while adapting to the evolving needs of clients and the market. The operational value of these agents can help accelerate both internal ROI and improved client experience. Now that agents are making the developer experience more automated, clients should empower someone on their Salesforce team to procure a free Developer Edition sandbox to start experimenting with use cases.
Ryan Eichenlaub, Managing Director – Business Platform Transformation, and Sandy Meers, Senior Manager – Business Platform Transformation, also contributed to this blog.
To learn more about our Salesforce consulting services, contact us. Or visit our AI Studio to experiment with use cases.
