emaildeliverabilityaudit

Email Deliverability Audit: A Checklist to Protect Inbox Performance in an AI World

UUnknown

2026-02-16

10 min read

A modern deliverability audit for 2026: technical checks, Gmail AI tests, and human QA to protect inbox placement and open rate performance.

Inbox performance is slipping — and Gmail's Gemini 3 features could be the reason. Here's a practical, step-by-step deliverability audit that protects your sends in 2026.

If your open rates and conversions have quietly declined since late 2025, you’re not alone. Gmail's rollout of Gemini 3 features and other AI-driven inbox behaviors changed how messages are summarized, prioritized, and surfaced to recipients. That means old deliverability checks won’t fully protect your campaigns anymore. This deliverability audit is a pragmatic toolkit: technical checks, new AI-aware inspections, and a human QA process to stop "AI slop" and protect open rate performance.

Why update your deliverability audit in 2026?

Deliverability used to be mostly about DNS, IPs, and avoiding spam filters. Today inboxes are judgment engines powered by machine learning and generative models. Gmail’s Gemini 3 integration (announced in late 2025) introduced things like AI Overviews, smart summaries, and context-aware classification — all of which change how recipients see the value of your message before they even open it.

New reality: an email can be summarized, flagged as irrelevant, or deprioritized by AI without the recipient ever opening it. So the audit you run in 2026 must include checks for: AI-driven snippet behavior, content that reads like "AI slop," and human-in-the-loop QA that prevents your creative from being auto-filtered out of attention.

Top inbox signals that now affect delivery

Engagement recency — opens, clicks, replies, and time spent reading act as strong positive signals.
Recipient behaviors — quick deletes, report-as-spam, or AI-generated summaries that deem content irrelevant.
Authentication & alignment — SPF, DKIM, DMARC still form the trust foundation.
Sender reputation — IP reputation and domain history remain decisive.
Content signals — spammy phrases, poor structure, and AI-like phrasing can trigger filters and AI deprioritization.

Audit checklist — at-a-glance (use this as your working guide)

Collect baseline metrics and seed test results
Run authentication & DNS checks (SPF, DKIM, DMARC, BIMI, MTA-STS, TLS-RPT)
Evaluate IP & domain reputation and warmup status
Review list quality, suppression, and bounce handling
Audit content for AI traits, spam signals, and snippet friendliness
Seed inbox placement across major providers + Gmail AI behavior tests
Run human QA and AI-detection review on copy and creative
Set monitoring alerts and remediation playbooks

Step 1 — Pre-audit data collection (what to gather before you start)

Collect a 90-day window of sending data for each IP and sending domain. Export the following:

Deliverability rates (delivered vs bounced)
Inbox placement and spam placement by provider (seed results)
Open, click, reply, and conversion metrics, plus engagement by recency
Complaint, unsubscribe, and soft/hard bounce details
Sample raw message headers for recent sends

These form your baseline so you can measure the impact of remediation and AI-specific changes.

Step 2 — Technical checks (the non-negotiables)

Authentication

SPF — ensure all sending services are listed, avoid the softfail '+~all'.
DKIM — verify signatures for each sending stream and refresh keys regularly.
DMARC — publish a policy (p=none initially if you’re diagnosing), then move toward quarantine/reject after alignment and reporting look clean.
DMARC reporting — enable RUA/RUF to capture forensic data and set up DMARC reporting pipelines that automatically parse and store reports.

Transport & security

MTA-STS — enforce TLS for sending to providers that support it.
TLS-RPT — monitor TLS delivery issues and fix them before they become reputation problems.
BIMI — optional but useful for brand signal in providers that show logos.

Header & routing inspection

Collect raw headers and check for `ARC-Seal` / `ARC-Message-Signature` when using forwarded services. Verify that return-path addresses and bounce domains are correct and consistent.

Step 3 — IP & domain reputation

Look up IP reputation on public blacklists and reputation providers. For shared IPs, check provider practices and ask for a dedicated IP if your volume and engagement justify it.

Warm-up new IPs slowly (recommended 7–14 days depending on volume).
Throttle sends to lower-engagement segments.
Use historical domain reputation as a decision factor before migrating sends.

Step 4 — List hygiene & sending practices

Bad list practices are still the fastest route to deliverability decline. In 2026, poor list hygiene also increases the likelihood of AI de-prioritization because low engagement patterns become obvious to inbox models.

Implement confirmed opt-in where possible and flag source for every address.
Segment by engagement recency — treat 30/90/365-day engagement separately.
Automate suppression for hard bounces and repeated soft bounces.
Run a spam trap check and remove stale addresses before major campaigns.
Use throttling to protect IP reputation during spikes.

Step 5 — Content audit: AI-aware checks

Content is now a deliverability signal itself. AI-generated or poorly structured copy can trigger models that mark messages as low value.

Checklist

AI slop detector: run a human inspection for repetitive phrases, over-optimization, or unnatural transitions. Use a simple prompt to identify sections that sound generically AI-generated.
Snippet optimization: Gmail and other providers use subject + preview + first sentences for AI Overviews. Ensure the first 2–3 sentences provide unique value, not just restated subject lines.
Subject & preview testing: avoid clickbait and deceptive language; test variations via A/B where possible.
Link hygiene: use consistent domains, avoid excessive redirect chains, and ensure all landing pages use HTTPS.
Image-to-text balance: high image ratios can reduce deliverability; include alt text and fallbacks.
Structured content: use clear headers and bullets; make content scannable for both humans and AI summarizers.

Step 6 — Gmail AI specific tests

Gmail’s AI features can summarize or surface your content differently from a straight-open. Run these focused checks:

AI Overview trigger check: send samples to seeded Gmail accounts and capture the AI-generated overview when available. Does the overview correctly reflect your main CTA or does it bury it?
Snippet/summary control: adjust first sentences and preview text to ensure summaries include your core offer and CTA.
Importance markers: ensure your sending patterns don’t mimic transactional or system notifications unless that’s intentional.
Conversations & threading: set appropriate Message-Id and In-Reply-To headers for follow-ups; avoid subject changes that break threading norms.
Feature compatibility: verify how elements like AMP for Email behave with Gmail’s AI by testing in seeded accounts.

Step 7 — Deliverability QA & human review process

AI speeds up copy production, but you need human-in-the-loop QA to protect deliverability. Put the following process in place for every campaign:

Brief: include send domain, audience segment, objective, and priority signals (transactional vs promotional).
First-draft AI pass: allow AI tools for drafts, but annotate where AI was used.
Human edit: copy editor rewrites or refines to remove AI slop and ensure natural language.
Deliverability review: deliverability specialist runs the content and header checks from this audit.
Seed test: send to internal seed list (Gmail, Outlook, Yahoo, Apple, mobile clients) and capture results.
Approval gating: no campaign goes out until both human QA and deliverability checks pass.

"Speed without structure produces AI slop — and inboxes penalize slop. Add human QA and focused deliverability checks to keep performance intact."

Step 8 — Seed testing & inbox placement

Use an automated seed list (50–200 addresses depending on scale) that covers major providers and real client devices. Track:

Inbox vs spam placement
Any AI summary or preview text differences
Visibility of images, links, and CSS
Time-to-deliver and soft-fail patterns

Export and store seed results so you can compare before/after remediation.

Step 9 — Measurement & KPIs to protect open rate performance

Open rate is less reliable in 2026 due to image caching and AI Overviews. Protect open-rate-derived decisions by pairing opens with stronger signals:

Click-through rate (CTR) — stronger indicator of engagement.
Reply rate — especially valuable for B2B and high-intent campaigns.
Engagement depth — time on site, pages per session, and conversion steps.
Deliverability rate — % delivered to recipient servers, excluding blocks and bounces.
Inbox placement — percent landing in primary, promotions, or spam folders (seeded results).

Step 10 — Remediation playbook (prioritized fixes)

Immediate (0–7 days)

Fix SPF/DKIM failures and DMARC reporting.
Stop sending to hard bounces and high-complaint segments.
Run a content QA against the AI slop checklist.

Short-term (7–30 days)

Warm-up or throttle IPs where necessary.
Segment campaigns by recency and engagement; re-engage with a cautious series.
Seed test targeted Gmail audiences specifically to observe AI Overviews.

Mid-term (30–90 days)

Move DMARC policy from none → quarantine → reject as confidence grows.
Iterate on subject/preview tests informed by AI overview captures.
Automate monitoring alerts for sudden drops in inbox placement or spikes in complaints.

Human QA templates & prompts (practical tools you can use)

Below are quick prompts and checks your human reviewers should run before approval.

AI-scan prompt for editors

"Read this email aloud. Does it sound like a specific person or a machine? Flag repetitive structures, marketing clichés, and generic CTA language."
"Highlight the first 20 words of the body — would a recipient know the one clear benefit in that preview? If not, rewrite."

Deliverability checklist for each campaign

SPF/DKIM pass (yes/no)
DMARC policy & recent RUA reports checked
Seed test passed all primary provider inboxes
Human editor signed off (name & date)
Sent to correct segment & suppression list applied

Brief case example (anonymized)

A mid-market SaaS client saw a 14% drop in opens after Gmail rolled out Gemini 3 features in late 2025. A quick audit revealed three issues: overused AI-generated subject lines, a shared IP with volume spikes, and stale segments. After implementing the checklist above — human-editing content, segmenting engagement, warming a dedicated IP, and adjusting DMARC alignment — inbox placement rose 18% and clicks improved 22% within 60 days.

Tools & resources for ongoing monitoring

Use a mix of vendor platforms and in-house seed tests. Important capabilities include seed inbox placement, authentication testing, reputation monitoring, and alerting for sudden shifts. Integrate DMARC reports into your monitoring stack and track engagement decay by cohort.

Future predictions — what to watch in 2026 and beyond

Inbox models will prioritize intent over volume. Expect AI to favor messages with measurable conversational intent (replies, confirmations, transactions) over broadcast updates.
AI summaries will become standard UI elements. Your subject and preview will be distilled into short takeaways — craft those first lines intentionally.
Brand signals will matter more. BIMI-like features and reputation tied to authenticated domains will become stronger trust tokens.
Human QA is a competitive advantage. Teams that pair AI productivity with structured human review will maintain better deliverability and higher conversion rates. See approaches for proving human review in audit trails like designing audit trails.

Actionable next steps — a 30/60/90 day plan

30 days: Run this full audit, fix authentication issues, and implement human QA gating for outbound campaigns.
60 days: Complete IP warm-up and segmentation changes. Run repeated seed tests and iterate subject/preview based on Gmail behaviors.
90 days: Move DMARC to stricter policy, automate monitoring, and codify an AI-aware content style guide for all writers.

Wrap-up: Keep human judgment in the loop

Deliverability in 2026 is part technical hygiene and part content strategy. Gmail AI and other inbox models now operate between your send and the recipient’s attention — so protecting inbox performance means protecting how AI perceives your message. Use this deliverability checklist, adopt a tight human QA workflow, and treat AI as an assistant, not a replacement, for critical email decision-making.

Ready for a hands-on audit? If you want, download our editable Deliverability Audit Template and AI-aware QA checklist to run your own review, or schedule a guided audit with our deliverability team to get prioritized fixes and a 90-day recovery plan.

Unknown

Contributor

Senior editor and content strategist. Writing about technology, design, and the future of digital media. Follow along for deep dives into the industry's moving parts.