The truth is, full automation isn’t achievable today with the tools currently on the market. And even if it were, it might not be the right move.

The smarter, and safer path forward is to use AI as a collaborator, not a replacement. Think of it as a colleague who never sleeps, can read thousands of pages in seconds and can draft a letter or summarize a document in the time it takes you to sip your coffee. But like any colleague, it needs guidance, oversight and accountability.

Three reasons why AI automation falls short for benefit plans

1. Benefit plans are not assembly lines

They are intricate ecosystems governed by plan documents, legal statutes and, in some cases, collective bargaining agreements. Each plan is its own rulebook, with unique provisions for service crediting, breaks in service and disability.

Encoding all of that into a rigid, automated system would be a monumental task. Moreover, one that can never fully anticipate the long tail of exceptions.

2. The data tends to be messy and unpredictable

Participant records may be scattered across multiple systems. In multiemployer plans, employer remittances arrive in different formats, often with errors or missing hours. Unstructured documents, like court orders and affidavits, add another layer of complexity.

Automation thrives on clean, predictable inputs. Benefit plan administration rarely offers that luxury.

3. The stakes are high

A miscalculated benefit or an incorrect eligibility determination isn’t just a technical glitch; it’s a breach of fiduciary duty that can derail someone’s retirement.

In the benefits business, speed matters, but accuracy and accountability matter more.

The automation risk that’s easy to miss

There’s another danger lurking behind the automation dream: capability debt. When organizations lean too heavily on systems to “handle it all,” human expertise begins to erode. Analysts who once knew every nuance of processing a Qualified Domestic Relations Order (QDRO) start to lose those instincts. Then, when the unexpected happens, like an alteration in the law, a benefit change or a spike in appeals, the team can be left scrambling, without the muscle memory to respond.

Capability debt makes operations brittle. It creates single points of failure, often tied to vendors or proprietary systems. And it undermines the very thing trustees and regulators expect: a defensible, transparent decision-making process.

The better way forward with AI: collaboration

So, if full automation is out of reach and out of bounds, what’s the alternative? Collaboration.

AI can be a powerful partner when used to amplify human judgment rather than replace it. Imagine an AI that reviews an employer remittance or payroll file, flags anomalies and drafts a clear, professional outreach email — or one that builds a benefit calculation worksheet, complete with citations to the plan document, so your analyst can validate the math instead of starting from scratch.

This is where AI shines: summarizing complex documents, drafting correspondence, checking calculations and identifying inconsistencies. It can prepare case briefs for meetings and extract key terms from QDROs.

In every scenario, a human stays in control, approving, deciding and ensuring that the outcome aligns with the plan and the law.

What AI collaboration looks like in practice

Picture this: A participant calls about a retirement estimate. Instead of spending hours combing through service histories and plan provisions, your analyst asks AI to prepare a draft worksheet. Within minutes, the AI system produces a step-by-step calculation, cites the relevant sections of the plan and flags missing data. The analyst reviews what the AI system created, adjusts assumptions as needed and finalizes the estimate with confidence.

Now imagine tackling something even more foundational: creating standard operating procedures (SOPs). Traditionally, drafting SOPs for complex processes, like QDRO handling, takes weeks of staff time. AI can accelerate this by analyzing historical case notes, plan documents and compliance guidelines to produce a structured draft SOP, complete with step-by-step workflows, decision points and references to governing provisions. Your team then reviews, refines and approves the document, ensuring it reflects both regulatory requirements and organizational best practices. The result is faster new employee onboarding, consistent execution and a living document that evolves as rules change.

The AI collaboration payoff

AI collaboration delivers what pure AI automation can’t:

• Speed without brittleness
• Efficiency without risk
• Consistency without losing the human touch

It also preserves institutional knowledge while giving teams the tools to work smarter. Most important, it keeps fiduciary responsibility where it belongs, with people.

AI won’t replace your team. The team that learns to work with AI will replace the one that doesn’t. In a business where trust is everything, that’s the future worth betting on.