When AI Gets It Wrong: AI customer service limitations and how Mando handles edge cases
It’s 4:57 pm. Your inbox spikes. One customer asks for a refund on a non-refundable voucher, another wants a last-second address change, and a third raises a data-privacy concern. These are classic AI customer service limitations. The answer isn’t to pretend they’ll vanish. It’s to design for them so customers still feel heard and helped.
Why edge cases happen (and why planning wins)
AI is brilliant with patterns and policies. It struggles when intent is fuzzy, emotions run high, or rules clash. That’s normal. We plan for it with three safeguards: human escalation, tight links to your knowledge base, and conversation summaries with sentiment so your team sees risk at a glance. Crucially, we keep meaningful human oversight in the loop for decisions that actually affect people’s rights, which regulators expect. (ICO)
Here’s the thing: not every query should be automated. We prefer fast, clean hand-offs on money, legal or safety issues, while automation handles routine shipping, billing and FAQs. That balance protects first-contact resolution and customer trust. It also keeps your team focused on judgement calls rather than wrestling with corner cases.
A quick story from our inbox
Last month, a 22-person e-commerce brand messaged us in a flap. A birthday gift arrived late and the buyer demanded a full refund outside policy. Our AI explained the policy clearly, detected rising frustration, and flagged “goodwill exception”. It escalated to a manager with a two-line summary and a link to the shipping SLA. The manager approved a one-off voucher and replied in 12 minutes. The customer edited their review to five stars. Small team, big save.
What changed after? We added a tagged template for courier delays and clarified when a voucher beats a refund. One tweak, measurable lift. At Mando, we’ve learnt that telling the team exactly when the bot should stop is as important as teaching it what to say. Sounds obvious, but in busy weeks obvious gets missed.
Our stance: where AI should stop, and why
Two opinions, stated plainly.
AI shouldn’t decide refunds, legal complaints or safety outcomes on its own. Its job is to gather facts, cite sources, and route fast to a human with context. People have rights not to be subject to solely automated decisions with legal or similarly significant effect, so structured oversight is non-negotiable. (ICO)
The best ROI appears once you’ve a steady ticket flow. Very small teams often win by tidying processes and a simple help centre first, then layering automation where it won’t create rework. We’d rather be honest about limits and cost than oversell.
We also believe some service moments should never be automated at all. Empathy, apology, and complex exceptions often land better coming from a person, which research has highlighted for years. (Harvard Business Review)
Technically, we keep responses grounded with retrieval-augmented generation that cites your knowledge base. Practically, we enforce confidence thresholds, approvals for sensitive replies, and transparent pricing so you stay in control. Pay for the automation you actually use, not for promises. That’s our choice because healthy scepticism saves small teams money, and money matters.
Turning limits into your playbook
Here’s a simple, no-nonsense plan to tame AI customer service limitations this week:
Write 10 queries you will never automate: refunds, chargebacks, legal notices, safety concerns.
Mark three “grey areas” where goodwill might apply and draft approved replies.
Set escalation triggers: low confidence, angry sentiment, missing order ID.
Map your evidence: one short policy article per trigger in your help centre.
Pilot with real transcripts for seven days; review twice weekly and prune anything noisy.
Prefer a quick decision frame? Automate routine FAQs; Assist complex queries with suggested replies; Escalate anything involving money, law or safety. Keep owners and SLAs visible. Add a short checklist to every escalated ticket so humans don’t repeat the the bot’s work.
How Mando makes this painless
We tuned Mando for SMB realities. Setup in hours, not months. Connect your help centre, set confidence thresholds, and define escalation rules by channel. Managers get tidy summaries and links to the sources the AI used, so a reply can go out in minutes. You can monitor exceptions, spot gaps in content, and refine policies without a full-time ops team. And yes, you can keep humans firmly in charge where oversight is required by law or just by good sense. (ICO)
Your customers don’t need perfect AI. They need a quick answer or a quick hand-off to someone who can decide. Design around AI customer service limitations, measure what improves, and update your playbook monthly. What’s one messy edge case you’ll map this week 🙂?
Articles you would love to read:
External Links Included:
UK ICO guidance on AI, individual rights and oversight. (ICO)
HBR: The parts of customer service that should never be automated. (Harvard Business Review)