Retirement Plan Advising 8 ways AI can help your retirement plan practice – and where it can’t

Ryan Tiernan

July 21, 2026

KEY TAKEAWAYS

  • AI works best as a complement — not a replacement — for retirement plan advisors. 
  • AI can help create operational efficiency across your practice. 
  • Know the boundaries: AI supports the work but doesn’t own the responsibility.

I recently attended a conference for retirement plan advisors and, you guessed it, AI was broadly featured on the agenda. One common refrain emerged from the sessions I attended: “AI won’t replace financial advisors, but advisors using AI will replace those who don't.”
 

While that may be reassuring to some, it doesn’t answer the real question retirement plan advisors face: How do I use AI in my retirement practice? What can it do, and maybe more important, what can't or shouldn’t it do? Advisors who want to make the most of AI need to have a strategy.
 

By using AI as a complement, not a replacement, retirement plan advisors have the potential to use it to free up time for the judgment, relationships and personalized guidance that only they can provide.

First things first

If you've ever typed a question into an AI chatbot, you've used a prompt. A prompt is the input you give to AI that it uses to create its output, but the more specific you are, the better the result. Think of that old phrase “Garbage in, garbage out.” The better the input, the better the output. I've included sample prompts tailored to retirement plan workflows. They're starting points that you can adjust to fit your practice.
 

AI can help move your business forward by cutting down on manual work without replacing your judgement. Here are eight ways to get started:

1. Ideal client profile (ICP) development

AI can translate your definition of an "ideal client" (plan size, industry, workforce, complexity) into consistent screening criteria, so your team can prioritize the right opportunities across a larger prospect pool.

Sample prompt: Based on these characteristics (plan assets between $20M and $100M, manufacturing or healthcare industry, 200+ participants, auto-enrollment in place), create a screening checklist I can use to evaluate new prospects.

2. Form 5500 prospecting

Instead of manually digging through these public filings, AI tools can help analyze large volumes of Form 5500 data to help flag potential buying signs: declining participation, provider changes, fee outliers, compliance issues or plans with no advisor of record. You decide which plans to pursue; AI just narrows the field faster.

Sample prompt: Analyze these Form 5500 filings and flag plans between $10M and $50M in assets that show declining participation, recent provider changes or fees above the peer group median.

3. Request for proposal (RFP) support

If you’ve ever done an RFP, you know how time-consuming it can be. Many of the questions are similar but asked in slightly different ways, requiring customized responses. AI can organize inputs, reference prior responses and coordinate data across stakeholders so you can respond faster and more consistently without starting from scratch.

Sample prompt: Using our previous RFP responses, draft answers to these 12 questions. Flag where the prior response is more than a year old or references outdated data.

4. Finals meeting preparation

AI can pull together a concise sponsor brief, draft potential Q&A and suggest follow-up questions, so you spend less time assembling materials and more time preparing for the actual conversation.

Sample prompt: Based on this plan's Form 5500, investment lineup and committee meeting notes, create a one-page sponsor brief and a list of 10 questions they're likely to ask in a finals meeting.

5. More customized plan reviews

Plan reviews are a cornerstone of advisor value, but they are also time consuming. AI can take the heavy lifting off your plate without starting from scratch by:
 

  • Turning plan data and prior notes into a draft agenda.
  • Flagging year-over-year changes worth discussing.
  • Summarizing what changed, what matters and what to prioritize.
     

The result is a more focused review where you spend less time preparing materials and more time guiding the discussion.

Sample prompt: Compare this plan's current data to last year's review. Summarize what changed in participation, deferrals and asset allocation. Recommend three discussion points for the plan-sponsor meeting.

6. Committee communication and governance support

Committee meetings demand clarity, consistency and documentation. AI can help you communicate more clearly with committees by:

  • Compiling meeting briefs from prior notes and recent account activity.
  • Turning plan data into narratives a committee can actually use.
  • Building hypotheticals to illustrate strategy options or design changes.
  • Drafting follow-up summaries with action items and owners.
  • Translating technical concepts into plain English for committee members who aren't steeped in plan mechanics.
  • Creating repeatable talking points on common governance topics such as QDIA basics, participation and auto-features, monitoring responsibilities and common fiduciary questions.
     

You still own the conversation. AI just makes it easier to deliver consistently.

Sample prompt: Using these committee meeting notes and the latest plan data, draft a follow-up summary with action items, owners and deadlines. Write it in plain-English language for a committee that includes non-financial professionals.

7. Participant education

Participant education is where AI can have an immediate, practical impact. Most advisors want to do more outreach but don't have the bandwidth to create, customize and track it all. AI can help by:
 

  • Drafting enrollment invitations, FAQs and follow-up communications.
  • Segmenting campaigns by life stage, behavior or plan events.
  • Documenting what was delivered and when.
  • Preparing talking points for enrollment meetings and common participant questions (e.g., contributions, QDIA and retirement readiness).


AI can also augment advisor-led education with personalized follow-up content that reinforces messages without crossing into individualized advice. AI can support education at scale, but it does not replace the advisor's role in guidance, suitability or delivery.

Sample prompt: Draft three versions of an enrollment meeting follow-up email: one for employees under 30 who haven't enrolled, one for mid-career employees not maximizing their match and one for employees within 10 years of retirement. Keep the tone encouraging, not dogmatic.

8. Using AI to create an AI policy for your practice

During my visits with clients, some have been asking about creating an AI policy. Neither the SEC nor FINRA has issued AI-specific rules, but both have offered guidance making clear that existing obligations, such as supervision, recordkeeping, communications and fiduciary duty, apply to AI the same way they apply to any other tool.

In the retirement plan context, existing ERISA fiduciary standards continue to govern how AI is used. The Department of Labor (DOL) has issued best practice guidance for employers on the use of AI, highlighting themes like transparency, human oversight and responsible use of data. While it’s focused on workplace use, it helps reinforce the importance of clear guardrails when incorporating AI into a practice.

With these guidelines in mind, consider implementing an AI-usage policy. Not a 30-page compliance manual. Just a clear document that answers the basics so everyone's on the same page. While not an exhaustive list, some examples of what you may consider covering in your AI policy include:
 

  • What tools can we use? Define what's approved and who can authorize new ones.
  • What data stays out? Client and proprietary data should never go into a public AI tool. Be specific so there's no gray area.
  • Who reviews the output? While firm policies and regulatory requirements may differ, consider whether every AI work product gets reviewed by a human before it goes anywhere.
  • What do we keep on file? If AI helped produce it, consider retaining the record the same as any other work product.
  • Are we being transparent? If AI played a meaningful role, say so.
  • How often do we revisit this? At least once a year and more frequently as needed. AI is moving fast and your policy should keep up.

Sample prompt: Create a one-page AI acceptable use policy for a retirement plan advisory practice with 10 employees. Include sections on approved tools, data restrictions, human review requirements, recordkeeping and annual review.

Getting the most out of AI means understanding both sides — where it helps and where it doesn't. The same tool that can prep a committee brief or draft an enrollment email can also produce a confidently wrong answer if you're not clear on its limits. Next, we’ll discuss where AI should NOT be used.

Where AI cannot — and should not — be used

AI is a powerful assistant, but it's not a fiduciary, a compliance function or a substitute for your knowledge. In highly regulated areas like ERISA, the line is even clearer: AI can support the work, but it cannot assume the responsibility behind it. Although not an exhaustive list, here are a few boundaries worth bearing in mind. AI cannot:

  • Exercise fiduciary judgment or oversight. AI can organize the inputs, but it's human judgment that makes a recommendation meaningful and helps you build client trust.
  • Replace live sponsor, committee or participant interactions. Trust is built on conversation, not automation.
  • Serve as a compliance or risk backstop. AI does not ensure regulatory accuracy.
  • Choose your client. While AI can screen data to help you identify your “ideal client,” at the end of the day it’s you who decides which relationships to pursue and why.
     

None of this should discourage adoption. It should sharpen it. Understanding these boundaries is what makes AI use credible, and the sample prompts throughout this article are a good place to start. For more prompts you can tailor to your practice, you can check out our prompt library created especially for financial advisors.  

The bottom line

AI isn't going to replace what makes a great retirement plan advisor great. But it can take a lot of the manual, repetitive work off your plate, so you have more time for the things that actually build a practice: judgment, accountability and trust. The question isn't whether to use it. It's how well.

Read important disclosures

Ryan Tiernan is an institutional retirement strategic growth counselor at Capital Group, with 25 years of industry experience as of 12/31/25. He holds a bachelor's degree in biology from the University of Massachusetts at Amherst.

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