Insurance carriers have been some of the quintessential pioneers of AI, from advanced mathematics modeling in the days of paper policies to machine learning and, in more recent years, artificial intelligence supporting actuarial sciences and fraud detection. Recognizing the potential to analyze vast amounts of data and predict outcomes, insurers began leveraging AI and machine learning for more accurate risk assessments, predictive modeling, and dynamic pricing.
AI for insurance agents is rapidly evolving, and the narratives have shifted significantly from even a year ago as new technologies are introduced. Organizations are seeing the benefits, and according to Salesforce’s Generative AI Snapshot Series, 84% of leaders say AI helped increase sales at their organization by enhancing and speeding up customer interactions.
82% of large companies plan to implement AI Agents by 2027, and Agentforce is leading the charge with fully configurable, role-based AI Agents that don’t just guide and assist employees, but augment your workforce by taking action and engaging with customers directly. Now is the time for insurance organizations to be AI relationship pioneers, leading the way by integrating Agentforce into their interactions with policyholders to reshape relationships through innovative, data-driven solutions.
Assistive AI is just the beginning
Insurance organizations have relieved the burden of handwritten policies by investing in connected, governed, and secured Salesforce solutions that adapt to meet the evolving needs of their customers, connecting with policyholders and stakeholders across channels and through rich portal experiences. These Salesforce solutions automate processes, enable collaboration, and organize information to accelerate business outcomes and enrich customer connections.
It’s a continuously evolving foundation, and the next evolution is to embrace opportunities with Agentforce and agentic (or autonomous) AI. These AI Agents can engage customers autonomously across channels 24/7 with natural language responses, and resolve cases swiftly and accurately by grounding every answer in a company’s trusted data.
Assistive Agentforce tools like chatbots, predictive analytics, and automated recommendation engines are tremendously powerful and play an important role in driving AI for insurance agents. For example, when a customer reaches out for assistance with a claim, the AI analyzes their history, identifies opportunities for upselling or cross-selling based on real-time intent and behavior, and suggests the best course of action.
Agentforce communicates these insights to a human agent who can guide the conversation, leveraging the AI’s real-time feedback to deepen the relationship. During moments where human empathy or complex judgment is required, the AI steps back and allows the human agent to take the lead.
Shifting from assistance to decision-making
While these assistive AI tools are helpful and part of a healthy AI strategy, they are still assistants, not decision-makers. While complimentary to assistive AI, agentic AI represents a shift from human-agent collaboration, where actions are recommended, to co-creation. The AI Agent autonomously makes decisions within Salesforce, executes actions, and adapts based on real-time data. These decisions and actions originate from Salesforce, but they can occur across your enterprise of integrated data and systems.
Furthermore, a collection of AI Agents are capable of managing major portions of the customer journey without direct human intervention, understanding customers needs, making recommendations, managing routine tasks, and even negotiating renewals.
Underwriting Agents can automatically and autonomously assess a customer’s risk profile, recommend coverage adjustments, and dynamically set premiums in response to a renewal date, a policyholder’s question, or some other event. This is all done in the context of your history with that individual policyholder, showing respect and insight for that unique relationship.
Claims Agents can resolve straightforward claims and do so by learning from previous interactions. They are informed by all global interactions across all clients in all situations to make decisions on immediate actions and predict future customer needs.
Humans are still involved in more complex or emotionally charged situations, but routine interactions are handled by these agentic Agents. With these agents in place, humans experience a time shift, focusing their valuable time on the most valuable outcomes.
Agentforce operates in the background, learning and adapting from every customer interaction and improving their decision-making over time. Here’s a breakdown of different jobs to be done for insurance agents, where AI Agents take the lead, and where they need to engage with a human employee:
Source: Salesforce
An agile mindset is essential to AI adoption
Being an AI relationship pioneer is a journey, and here are the main things to keep in mind as you look to start, or make progress, on this journey. Embrace a pioneering mindset. Explore your foundation technologies and your data across the enterprise to understand your strengths and your starting point. Go out across your teams and collaborate broadly and challenge perceptions on what AI can mean to your organization while testing your team’s assumptions. When you find success, immediately improve on that success to refine and innovate.
An agile mindset has never been more important, allowing you to move forward incrementally, assess continuously, and adapt to new opportunities that present themselves. Agentforce AI is an exploratory endeavour, you will learn more about what the most meaningful next step may be just prior to making that next step at time. Agentforce, Data Cloud, and other Salesforce empower teams to collaborate with clients, identify and pursue opportunities, access and collect new data, and drive Agentforce actions both within Salesforce and across the enterprise.
Take a holistic approach to unlock the full potential of your business and the technologies that support it. Your optimized solution is likely a combination of many technologies, some that you’ve invested in and refined and others with which you’re just starting your journey. It will be a combination of assistive agents, agentic agents, process automations (like flow in Salesforce), and process integrations, effectively consuming enterprise data and integrating across your enterprise systems.
Finally, don’t let analysis drive inaction. Data quality and gaps in your existing technology aren’t a barrier to taking a pragmatic first step. Our experts can help you develop the data strategy you need to implement Agentforce successfully, giving your organization a sturdy data foundation to build the AI Agents that will best serve your teams. Learn more about our Agentforce solutions.
