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Trust

Verification Next Steps

Pair uncertain or high-impact answers with concrete validation actions: open a source, run a test, ask a human, or compare alternatives. Turn doubt into a checklist.

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Before you send

Overview

How might we design verification next steps so people can trust and act on AI output?

When to use

  • Essential for sales assistants, support copilots, and research tools where low-confidence answers must route users to a checkable source or human before send.

When to skip

  • Low-stakes creative suggestions where verification would feel preachy.
  • Answers that are already fully grounded with strong citations and no residual risk.
  • Automations that must complete without stopping for human validation.

Rules

  • Generic “please verify” banners with no actionable link or step.

  • Next steps that send users outside the product with no return path.

  • Showing verification only after the harmful action already ran.

  • Checklist spam on every message, training users to ignore it.

Evidence

ProductImplementation
GleanSuggested follow-ups to open source docs and owners.
Intercom FinHandoff and article links when the bot is unsure.
Salesforce EinsteinRecommended review actions beside AI CRM suggestions.
Enterprise knowledge botsValidate-with-owner and open-policy shortcuts on answers.

FAQ

What are verification next steps in AI UX?

They are concrete follow-up actions attached to an answer that help users check correctness before relying on it, such as open source, run test, or escalate to a human.

When should they appear?

When confidence is low, stakes are high, or the domain is regulated. Skip them for casual brainstorming.

How do they differ from confidence indicators?

Confidence says how sure the system is. Verification next steps tell the user what to do about remaining uncertainty.

How many steps is enough?

One to three primary actions. More becomes noise. Rank by impact: highest-risk check first.