AI Hiring Compliance: Avoid ADA Service Dog Mistakes

A job offer can fall apart in a single email.

This week’s headline is a painful reminder: a lawsuit alleges that SHRM rescinded a candidate’s job offer after she requested to bring a trained service dog to the office as a reasonable accommodation for Type 1 diabetes. According to the complaint, the candidate said the dog alerts her before blood glucose levels swing into dangerous territory—and that severe hypoglycemia episodes dropped from about 10 per year to one incident over eight years once paired with the dog.

If an HR trade organization can allegedly mis-handle an accommodation request, any employer can. And that’s exactly why this belongs in an “AI in Human Resources & Workforce Management” series: accommodation decisions are high-stakes, time-sensitive, and full of documentation requirements. Those are conditions where AI-driven compliance can genuinely help—not by deciding who gets hired, but by preventing process breakdowns that lead to discrimination claims.

What this case signals: accommodation risk starts before Day 1

Answer first: The biggest compliance risk in accommodation requests isn’t the final “yes/no”—it’s failing the interactive process and leaving a messy record.

The lawsuit claims SHRM requested more information, denied the accommodation on the basis that the candidate could do the job without the service dog, then ended the interactive process and withdrew the offer after receiving additional details. Whether or not the allegations are ultimately proven, the pattern HR leaders should notice is familiar:

• An accommodation request shows up late in the hiring workflow (often after offer, pre-start).
• A manager reacts fast—sometimes emotionally—because it “changes the plan.”
• HR scrambles to evaluate medical documentation, workplace policies, and safety concerns.
• The process stalls, communications get sloppy, and someone makes a final call without a defensible trail.

That sequence is a lawsuit magnet.

Why service dog requests are uniquely mishandled

Answer first: Service dog requests get mishandled because people confuse service animals with pets, and because workplaces over-index on “exceptions” rather than essential functions and risk controls.

Many organizations still treat service animals like a perk they can approve “when convenient.” That’s not how it works. The operational reality is that employers need a consistent way to evaluate:

• Essential job functions (what must be done, not how you prefer it done)
• Workplace constraints (allergies, shared spaces, safety requirements)
• Alternative accommodations (if the requested accommodation isn’t feasible)
• Documentation and timing (what you requested, what you considered, and why)

The alleged facts also highlight another common failure: treating technology as a replacement for accommodation. If an employer suggests “just use a glucose monitoring system” and the employee provides evidence it’s insufficient for preventing life-threatening events, the employer can’t simply shrug and move on. The obligation is to engage, evaluate, and document.

Where AI helps (and where it absolutely shouldn’t)

Answer first: AI should run the process—workflows, deadlines, documentation, consistency checks—not the outcome of whether someone “deserves” an accommodation.

A practical way to think about AI in HR compliance is: use it to prevent human forgetfulness and inconsistency, not to automate judgment calls that carry legal and ethical weight.

Here’s what I’ve found works best in real HR environments: AI supports the parts of accommodation handling that are repetitive, traceable, and rules-based.

1) AI can enforce an interactive-process workflow

Answer first: The easiest win is an AI-assisted workflow that prevents the “we stopped engaging” allegation.

A well-designed system can:

• Trigger a standardized accommodation intake the moment the request is received (including during recruiting)
• Route tasks to the right owner (HR, recruiter, facilities, legal, manager)
• Set SLAs (for example: acknowledge within 1 business day; schedule interactive discussion within 5)
• Flag stalled cases automatically (no response, missing follow-up, unclear decision rationale)
• Create a time-stamped audit trail of every step

This isn’t glamorous. It’s just effective.

2) AI can spot inconsistent handling across managers and locations

Answer first: Inconsistent decisions are how “one-off” mistakes become discrimination patterns.

If one manager approves service animal requests routinely and another always denies them, you don’t just have a training issue—you have a liability issue.

AI analytics can monitor trends like:

• Approval/denial rates by department, manager, region
• Average time-to-resolution (and where cases bottleneck)
• Common reasons for denial (and whether those reasons are defensible)
• Re-open rates (signals poor initial analysis)

Think of this as workforce compliance monitoring. It’s not about catching “bad people.” It’s about catching broken systems.

3) AI can improve documentation quality (without inventing facts)

Answer first: Most accommodation files are weak because notes are vague, scattered, or written after the fact.

AI can help HR teams draft structured documentation that prompts for what matters:

• The essential functions discussed
• The employee’s (or candidate’s) stated limitations and requested accommodation
• Options considered and why they were feasible or not
• Any safety, operational, or client-site constraints explored
• Next steps and timelines

The critical line you don’t cross: no AI “medical interpretations” and no auto-generated conclusions like “not disabled” or “not credible.” Your system should support clarity, not pretend to be a clinician.

A compliance-first accommodation playbook for HR teams (that AI can power)

Answer first: The best accommodation approach is boring, consistent, and documented—and AI makes “boring and consistent” scalable.

If you want fewer blow-ups at offer stage (and fewer panicked calls to counsel), build your accommodation process like a product: clear inputs, controlled steps, measurable outputs.

Step 1: Treat accommodations as part of the hiring lifecycle, not an HR side quest

Accommodation requests don’t start at onboarding. They often show up:

• After a conditional offer
• Before the first in-office day
• When remote work expectations shift (a common December/January flashpoint)

Operationally, that means your recruiting team needs a clean handoff into an accommodation workflow the moment a request appears.

AI assist: automatic case creation, routing, and templated communications that keep tone respectful and consistent.

Step 2: Standardize the “essential functions” check

If your denial rationale is “you can do the job without it,” you’d better be able to defend:

• What the essential functions are
• Why the requested accommodation isn’t needed to perform them or why it creates undue hardship

Too many teams confuse “not needed” with “not preferred.” Preference isn’t the legal test.

AI assist: job-description parsing to pre-fill essential functions, plus prompts requiring manager-specific examples (not generic statements).

Step 3: Build a service animal readiness checklist

A service dog request shouldn’t trigger chaos. It should trigger a checklist.

Here’s a practical version most offices can support:

• Identify primary work areas and shared spaces
• Confirm vaccination/behavior standards consistent with policy (avoid asking for irrelevant details)
• Plan entry/exit routes, relief area, and sanitation expectations n- Identify any documented allergy conflicts and explore solutions (seating plans, air filters, scheduling)
• Review safety constraints (labs, food prep, restricted areas) and define boundaries

AI assist: case templates by workplace type (corporate office vs. client site vs. manufacturing) and automated reminders for facilities tasks.

Step 4: Use “risk flags,” not auto-decisions

AI should raise a hand when a scenario is legally sensitive or trending off-course. For example:

• Offer withdrawal after an accommodation request
• Manager language that signals bias (“this will be distracting,” “clients won’t like it,” “we don’t allow animals”)
• A denial issued without documenting alternatives considered
• Excessive delays or repeated requests for information beyond policy norms

AI assist: natural-language flagging inside HR case notes and email summaries—paired with human review.

Step 5: Close the loop with employee engagement, not just compliance

Accommodation processes aren’t only legal. They’re cultural. Candidates and employees remember whether you treated them like a problem to manage or a professional to support.

A simple post-resolution check-in (even during onboarding) improves:

• Retention
• Time-to-productivity
• Trust in HR
• Willingness to request help early instead of waiting for a crisis

AI assist: scheduled check-ins and sentiment tracking—careful to respect privacy and avoid collecting unnecessary health details.

People also ask: “Can AI prevent discrimination in hiring?”

Answer first: AI can prevent discrimination in hiring only when it’s designed to reduce inconsistency and improve oversight—and when humans stay accountable for decisions.

If you’re using AI to score candidates, rank resumes, or draft interview feedback, you also need AI (and governance) to monitor the downstream effects:

• Are certain protected groups disproportionately screened out?
• Are accommodation requests correlated with offer withdrawals?
• Are certain managers creating higher legal exposure than peers?

This is where workforce analytics belongs: measuring outcomes, identifying outliers, and forcing review before harm occurs.

Another practical question HR teams ask:

“Should we automate accommodation approvals?”

Answer first: Don’t automate approvals; automate everything around approvals.

Approvals require context. The system can prepare that context, ensure timelines are met, and ensure alternatives are explored, but the final call should be accountable to a named human.

The real lesson: your process is your protection

The lawsuit allegations against SHRM land harder because SHRM is widely viewed as an authority on HR practice. But the uncomfortable truth is that many organizations run accommodations on tribal knowledge, manager instincts, and scattered emails.

If you’re serious about fair hiring practices and ADA compliance in recruiting, you need a system that does three things consistently:

1. Captures requests early and respectfully
2. Guides HR and managers through a defensible interactive process
3. Flags risk patterns before they become headlines

AI can do that well—especially as we head into 2026 planning cycles, when budget tightening and return-to-office enforcement often increase accommodation friction.

If you’re building an AI-enabled HR function, start here. Accommodation handling is one of the clearest places where better workflows create immediate legal and employee-experience returns.

If your accommodation process can’t explain what happened in 10 minutes to a neutral third party, it’s not a process—it’s improv.

What would change in your hiring outcomes if your team had an early-warning system for accommodation risk before an offer ever gets pulled?