Enterprise AI adoption often stalls at experimentation.
Proofs of concept generate interest, but few solutions are deployed where accuracy, trust, and scale matter immediately.
At enGen, we took a different approach - deploying agentic AI directly into a live, high-volume service environment during one of the most critical moments in the employee lifecycle: Open Enrollment.
Working with a large Blue health plan client, our Salesforce team designed and launched an AI-powered Open Enrollment Assistant that delivered measurable operational impact in weeks, not months - and established a repeatable model for scaling agentic AI across the enterprise.
The Operational Context
Annual Open Enrollment generates thousands of employee inquiries within a compressed timeframe. Many are routine, but all are time-sensitive. Traditional self-service tools help, but they rarely reduce enough volume to meaningfully relieve HR service teams or improve employee experience.
The objectives for the pilot were clear:
• Reduce routine inquiry volume
• Improve response speed and consistency
• Preserve human capacity for complex cases
•The constraint was equally clear: deliver quickly, using enterprise platforms that were already in place.
The Solution: An Agentic AI Open Enrollment Assistant
The enGen Salesforce team deployed a generative AI assistant using Salesforce Agentforce, made available to the full employee population during Open Enrollment.
The assistant was designed to operate directly within the service workflow:
• Employees could ask natural-language questions and receive immediate responses
• Answers were grounded in curated Open Enrollment knowledge content
• The assistant surfaced content tailored to each employee, drawing from Open Enrollment knowledge articles
• When escalation was required, the assistant automatically created and routed a service request to an HR Service Representative
As Piper Kotwica, VP of Product Development at enGen, explained:
“The goal was to reduce friction at the moment an employee needed help. If the AI couldn’t fully resolve the issue, it needed to handle the handoff without adding effort for the employee.”
This ability to initiate action - not just provide information - was central to the solution.
“The goal was to reduce friction at the moment an employee needed help. If the AI couldn’t fully resolve the issue, it needed to handle the handoff without adding effort for the employee.”
-Piper Kotwica, VP of Product Development
Speed to Value
From planning through production launch, the solution was delivered in nine weeks.
Acceleration came from deliberate choices:
• Leveraging native Salesforce Agentforce capabilities
• Using out-of-the-box AI models to avoid extended approval cycles
• Iterating quickly based on real usage patterns
“We moved quickly because the scope was focused and the alignment was strong,” said Kotwica. “From early development to launch, it was roughly a one-month turnaround.”
“We moved quickly because the scope was focused and the alignment was strong. From early development to launch, it was roughly a one-month turnaround.”
Measured Impact
During the Open Enrollment period, the AI assistant proved its value where it mattered most - driving strong employee adoption and engagement, delivering near-instant responses to employee questions, and meaningfully reducing the burden on HR teams. The successful deployment also positioned the client as one of only six Blue plans nationwide to implement an AgentForce AI Agent, translating innovation into real, measurable outcomes.
Results at a glance:
Design Principles That Enabled Scale
Several implementation choices proved essential:
Curated knowledge foundation
The assistant was trained exclusively on approved Open Enrollment content aligned to historically common employee questions.
Built-in governance and guardrails
System instructions ensured responses were factual, traceable, and constrained to approved sources.
Embedded action capability
The assistant could initiate service requests autonomously, reducing handoffs and improving resolution speed.
According to Kotwica, “That action capability takes the burden off the employee and allows the system to own the next step.”
Implications for Enterprise AI Adoption
The pilot reinforced several principles that now guide enGen’s broader AI strategy:
• Executive alignment paired with clear operational goals accelerates delivery
• Enterprise AI can scale without extensive architectural change
• Iterative improvement in live environments outperforms prolonged pre-launch refinement
• Analytics are essential for understanding adoption, gaps, and next opportunities
• Once AI is embedded directly into service workflows, employee expectations shift
As Mike Stimpson, Chief Technology Officer at enGen, noted, “This pilot demonstrated what's possible when AI is treated as a service capability rather than an experiment. The speed and reliability of delivery set a new benchmark for how we approach AI adoption.”
“This pilot demonstrated what's possible when AI is treated as a service capability rather than an experiment. The speed and reliability of delivery set a new benchmark for how we approach AI adoption.”
-Mike Stimpson, Chief Technology Officer at enGen
Looking Ahead
Building on this foundation, enGen is expanding agentic AI across additional domains, including broader HR services, commercial sales workflows, marketing automation, and transactional system integration.
The focus remains consistent: deploy AI where it reduces effort, increases speed, and supports operational reliability.
Closing Perspective
Agentic AI succeeds when it is embedded into real work, governed responsibly, and measured by outcomes.
This Open Enrollment deployment demonstrated that AI can deliver meaningful value quickly when technology, execution, and business priorities remain aligned - and provides a scalable model for future AI adoption.