Salesforce, the industry standard for customer relationship management (CRM), is shaking things up in life sciences. With a suite of tailored solutions, they’re empowering innovators to reach new heights of efficiency, innovation and customer experience.
Recently, Salesforce introduced Agentforce, a powerful set of generative AI capabilities within its Einstein platform. It’s being billed as part of the “Third Wave of AI,” moving beyond traditional chatbots and co-pilots toward highly autonomous agents capable of executing complex tasks that can be tailored to the specific processes of healthcare and life sciences with minimal human oversight.
The agents that come out-of-the-box in Agentforce are versatile problem-solvers, helping your teams deploy ready-to-use workflow automations and perform tasks unique to your business. A network of autonomous agents from other partners is also available to extend your capabilities. By design, agents can operate seamlessly across systems and channels—both within and beyond the Salesforce ecosystem.
Agentforce success: Key considerations for life sciences
While Agentforce has great promise, life sciences and healthcare organizations need a holistic strategy and careful consideration of several elements before diving in.
Many of these are familiar, but it’s essential to consider them in the specific context of your commitment to Salesforce and the capabilities of Agentforce:
- Business case and expected returns: To unlock the value of Agentforce, it’s crucial that your plan links to overall business goals. Identify specific business goals and KPIs that Agentforce can improve. Prioritize use cases that drive improvement goals to target specific processes, whether they are centrally managed or distributed.
- Business processes readiness: Automating with agents requires reengineering business processes, including setting new objectives and key results. Collaborate with business owners to assess the effort and investment needed to reimagine processes, align them with the platform roadmap, and consider the costs of retiring legacy processes and ensuring business continuity.
- Alignment with the AI strategy and existing investments: Most organizations have an established AI strategy, which includes organization-level standard operating procedures and compliance standards, and partnerships with Open AI, Microsoft, Google or others. It’s important to evaluate how Agentforce fits into your organization’s AI strategy framework and how its capabilities, like connecting to externally hosted LLMs, can be leveraged.
- How priority use cases match Agentforce’s maturity: You’ll want to assess Agentforce’s ability to deliver results, scale and comply with regulations for your chosen use cases. Pay close attention to the specific roles and tasks the agent will need to perform to achieve consistent outcomes.
- How well proof of concepts and pilots deliver: Set up sandbox environments to test Prompt Builder’s, out-of-the-box agents and partner agents for your use cases. Run small-scale pilots with real users to measure performance against current KPIs. This will help build confidence in future investments and inform your CRM development roadmap.
- Data readiness: The entire reason to choose Agentforce is that it’s grounded in Salesforce data. However, if your Salesforce data isn’t high quality, the agent results will also be suboptimal. Carefully assess your Salesforce data for every chosen use case.
- Integration readiness: Altering or automating a business process often requires integration with other enterprise systems. As part of your feasibility steps, check your readiness to build integrations between Salesforce and other enterprise systems like ERP, content management, data platforms and HR systems.
- Change management and adoption: With change in business processes and new platform capabilities, organizations need to consider the change effort, including communication planning, training, initiatives to drive adoption, evangelizing success stories with agents and many more.
- Regulatory compliance and data privacy: Many organizations deal with sensitive data such as patient data which require adherence to regulations like GDPR, HIPAA and CCPA. So it is critical to evaluate Agentforce’s Trust Layer, its claims for “zero-copy” data, and how you’ll maintain audit information in Data Cloud to meet your company’s compliance requirements.
- AI and domain expertise: Many of the above considerations, especially in highly regulated industries, require significant domain expertise in areas such as user persona identification, domain-specific workflows and process reengineering, data assessment, regulatory compliance and AI experience. A Salesforce service partner with proven technical and domain expertise can help define and execute a holistic approach.
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