This discovery framework is designed to help facilitate a collaborative conversation regarding Agentforce. By exploring these operational scenarios, Retirement Plan Administrators can accurately assess internal workflows and identify how specific Agentforce capabilities can support their unique clinical and administrative needs, starting with areas of highest impact to business revenue and institutional client care.
How does the firm manage sudden spikes in participant support requests without linearly increasing contact center headcount costs?
Scenario A: Abandoned Calls and Lost Revenue
"During market volatility, our hold times exceed forty minutes, leading to abandoned calls and missed opportunities to capture high-net-worth rollovers before participants take their funds elsewhere."
Scenario B: Expensive Outsourcing Models
"We rely on an external business processing outsourcer to handle seasonal overflow, but the quality of participant care suffers and the variable costs cut deeply into our margins."
What controls are in place to guarantee that automated participant communications adhere strictly to distinct institutional plan rules as the firm expands multi-site operations?
Scenario A: Compliance Vulnerability
"We are terrified of deploying AI because a hallucinated response regarding vesting schedules or ERISA rules could expose the firm to massive regulatory fines and reputational damage."
Scenario B: Rigid, Unhelpful Automation
"To stay compliant, our current chatbot only provides generic links to plan documents, frustrating participants who are forced to call our support line for specific answers anyway."
How are internal teams currently executing routine administrative workflows, such as processing address updates or initiating standard rollovers?
Scenario A: High Cost of Routine Tasks
"Our highly paid operations staff spends half their day manually rekeying address changes and beneficiary updates from emails into our core recordkeeping system."
Scenario B: Disconnected Web Forms
"We have web forms for basic requests, but they still generate a ticket that requires an employee to review and approve the action before the system updates."
What mechanisms support your contact center staff when they must rapidly interpret complex vesting schedules or loan provisions while on a live call?
Scenario A: Excessive Handle Times
"Agents place participants on long holds while they frantically search through hundred-page PDF plan documents trying to find specific withdrawal penalty clauses."
Scenario B: Subject Matter Expert Bottlenecks
"When front-line agents get stuck on a complex plan rule, they ping our senior specialists, which solves the issue but grinds our internal escalation desk to a halt."
How do you audit AI-assisted communications to prove to regulators that automated systems are not hallucinating restricted financial advice?
Scenario A: Total Innovation Paralysis
"We have explicitly banned all use of generative AI because we currently have no systematic way to audit prompts or prove that the outputs are factually accurate to auditors."
Scenario B: Unsustainable Manual Spot-Checks
"We run a limited pilot of an automated assistant, but my compliance team has to manually read daily chat transcripts to ensure no unauthorized advice was given."
How quickly can your organization update automated support logic when federal tax regulations regarding retirement withdrawals suddenly change?
Scenario A: IT Bottlenecks Delaying Compliance
"When the IRS updates withdrawal limits, it takes our developers three months to rewrite the hardcoded logic in our participant portal, leaving us vulnerable in the interim."
Scenario B: Brittle Decision Trees
"We use a standard bot builder, but updating it means manually untangling massive, complex decision trees, which almost always breaks another workflow."
What is the process for drafting highly customized RFP responses when competing for large institutional plan sponsor accounts?
Scenario A: Slow Cycle Times Costing Deals
"Our sales team wastes weeks manually compiling past responses and plan specifics to build an RFP, causing us to miss deadlines or lose momentum with key institutional prospects."
Scenario B: Generic Pitch Material
"To speed up the process, we use boilerplate templates for our proposals, but they often fail to address the specific, nuanced needs of high-value institutional clients."
How is the technology team managing the integration of AI capabilities without increasing security vulnerabilities or compounding technical debt?
Scenario A: Risky Data Exposure
"Business units are piecing together third-party AI tools that require us to send highly sensitive participant financial data outside our secure firewall to external language models."
Scenario B: High Maintenance Integrations
"We built a custom AI integration, but maintaining the middleware and updating the API connections consumes a massive portion of our quarterly IT budget."
How do your teams proactively notify institutional plan sponsors about upcoming compliance testing deadlines or missing census data?
Scenario A: Missed Deadlines and Penalties
"Account managers manually track non-discrimination testing deadlines on spreadsheets, and when a date slips through the cracks, the plan sponsor faces severe IRS penalties."
Scenario B: Ignored Mass Communications
"We send out automated mass emails for missing census data, but because they lack specific institutional context, plan sponsors ignore them, requiring manual phone calls anyway."
What strategies are employed to reduce the training ramp time for new administrative staff who must learn complex retirement plan variations?
Scenario A: Prolonged Shadowing Periods
"It takes six months of shadowing senior staff before a new agent is confident enough to navigate our legacy systems and handle a complex rollover call independently."
Scenario B: Ineffective Knowledge Bases
"We direct new hires to our corporate intranet to find answers, but the search functionality is so poor that they end up guessing or providing outdated information."
