# D — Vendor-Published Commercial Case Studies on "Human-Like" AI

**Research value: high** — Vendor case-study corpus on "human-like" customer-facing AI is dense and metrics-rich across all six target vendors (Salesforce, HubSpot, Zendesk, Intercom, Drift, Ada) plus Microsoft and Google Cloud. The biggest signal is not whether the claims are true but *which metrics* vendors choose to anchor their "human-like" narrative on — and the gap between those metrics and any direct measurement of perceived humanness.

**Scope note.** All sources below are vendor-published (or close partners/resellers referencing vendor collateral). Treat numbers as marketing-grade unless independently corroborated. Where a metric comes from a third-party aggregator, that is flagged.

**Last updated:** April 2026. Case studies 1–39 are from pre-April 2025 sources. The Patterns & Trends and Gaps sections are updated to reflect the April 2025–April 2026 period, including Salesforce Agentforce's 500K/2M conversation milestones, Fin 3, Sierra's $150M ARR, and the post-Klarna metric-shift to resolution depth.

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## Case Studies

### Salesforce (Einstein / Agentforce)

**1. de Bijenkorf — Luxury Retail (Netherlands) · Einstein Bots + Next Best Action**
- Use case: Retail customer service, returns, service chat.
- "Human-like" framing: Personalized recommendations and context-aware replies via Next Best Action.
- Metrics: 18,600 actions driven by next-best-action recommendations in 2023; –70s average chat handle time; 75% first-contact resolution; NPS for returns 25 → 55 (+30 pts).
- Source: gen25.com/cases/bijenkorf-einstein (Salesforce partner case).

**2. Salesforce Internal Sales Ops — Einstein 1 Service**
- Use case: Internal sales-support chat (SMB sellers).
- "Human-like" framing: Einstein drafts replies in brand voice; agents edit, not author.
- Metrics: 80% faster chat close; avg chat close 90 min → 18 min; 30,000 cases/yr closed by Einstein Bots; Einstein writes ~25% of all service replies.
- Source: salesforce.com/salesforce-stories/artificial-intelligence-closes-deals-faster.

**3. Wiley — Publishing/EdTech · Agentforce + Service Cloud**
- Use case: Back-to-school surge support (password resets, access, payments).
- "Human-like" framing: Prompt Builder templates in brand tone; automated case summaries for humans.
- Metrics: 213% ROI; +40% case resolution efficiency in first weeks; 50% faster onboarding of seasonal agents; $230,000 savings.
- Source: salesforce.com/customer-stories/wiley.

**4. OpenTable — Hospitality Tech · Agentforce**
- Use case: Restaurant + diner support; 60,000 restaurants, 1.9B seats/yr.
- "Human-like" framing: Conversational agents that "take action," flexible escalation logic, tested on real conversations.
- Metrics: 73% case resolution within 3 weeks of launch; 11,000 conversations/week handled by agents.
- Source: salesforce.com/customer-stories/opentable.

**5. Heathrow Airport — Aviation · Agentforce ("Hallie")**
- Use case: Passenger digital concierge (security wait times, gates, dining).
- "Human-like" framing: Framed as a "digital concierge that holds your hand through your end-to-end airport experience."
- Metrics: 90% of chats resolved by Hallie without live-agent transfer; 50%+ fewer chat exchanges per answer; 40% improvement in digital contact efficiency.
- Source: salesforce.com/customer-stories/heathrow-airport.

**Salesforce Agentforce 2025–2026 milestones (platform-level, not single customer):**
- Salesforce's own deployment on help.salesforce.com (Customer Zero): 500,000 conversations by mid-2025, 2M+ by early 2026. 84%+ resolution; 4% human handoff rate.
- Reddit: 46% support case deflection; resolution time –84% (8.9 min → 1.4 min).
- SDR agent on 43,000+ leads; $1.7M new pipeline from dormant accounts.
- "Empathy at scale" framing: Agentforce learned that "delivering the right answer doesn't matter if it lands the wrong way" — empathetic acknowledgment before resolution became a required behavioral spec, not a nice-to-have. Teaching bots to say "I'm sorry" and recognize frustration drove higher CSAT than raw automation.
- Harvard Business School published Agentforce case study (April 2025): "Salesforce Agentforce: The Limitless Workforce" — examines workforce disruption, human-AI partnership, ethical oversight.
- Source: salesforce.com/news/stories/agentforce-customer-support-lessons-learned/; salesforce.com/blog/support-requests-agentforce/; HBS case #67220.

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### Intercom (Fin AI Agent)

**6. Anthropic — AI Infrastructure · Fin**
- Use case: Anthropic's own customer support (build-vs-buy decision story).
- "Human-like" framing: Fin 2 explicitly positioned as "first AI agent that delivers human-quality service."
- Metrics: 50.8% resolution rate within ~1 month; 96% Fin involvement rate; 1,700 hours saved in month 1.
- Source: intercom.com/customers/anthropic.

**7. Synthesia — AI Video SaaS · Fin**
- Use case: Support scale-out during 690% contact volume spike (40K → 316K monthly queries in 4 months).
- "Human-like" framing: Fin asks clarifying questions and compiles multi-source answers.
- Metrics: 55% resolution rate; +33 pts CSAT increase; 96% reduction in resolution time; >275,000 additional monthly queries absorbed at flat headcount.
- Source: intercom.com/customers/synthesia-pioneer.

**8. Fundrise — Fintech · Fin**
- Use case: Investor support volume reduction.
- Metrics: 50% support volume resolved; 95% response accuracy.
- Source: intercom.com/customers/fundrise.

**9. Lightspeed — Commerce Platform · Fin + Copilot**
- Use case: Multi-product merchant support.
- Metrics: Up to 65% end-to-end resolution; 99% Fin involvement; +31% daily conversations closed per human using Copilot.
- Source: intercom.com/customers/lightspeed.

**10. Sharesies — Investing App · Fin**
- Use case: Retail investor support.
- Metrics: 70% resolution rate within 12 weeks.
- Source: virtualassistantva.com aggregator citing Intercom data (2026).

**Fin aggregate benchmark** (useful context, not a single case): 66% avg resolution across 6,000+ customers and 40M conversations; 20%+ of customers exceed 80% resolution; claim of "human-quality service" anchored on knowledge, brand-voice behavior, action-taking, and insights. Source: intercom.com/blog/whats-new-with-fin-3.

**Fin 3 / Pioneer 2025 update (April 2025–April 2026):** Fin Voice launched as enterprise voice humanization feature; customers report being "surprised it isn't a human." Procedures feature allows natural-language SOP training. "Fin Flywheel" positions the product as continuously improving via human-AI feedback loops — directly responsive to the Klarna lesson. Source: intercom.com/blog/headlines-from-pioneer-2025/

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### Zendesk (AI Agents / Agentic AI, March 2025)

**11. New Look — Fashion Retail (UK) · Zendesk AI Agents**
- Use case: High-volume email + chat support.
- "Human-like" framing: Tone shifting + macro suggestions for brand-consistent responses.
- Metrics: 99.5% faster first reply time (16.5 hr → 5 min); 42% automated resolution; 66% agent productivity lift; 30% shorter total resolution; 305,761 contacts resolved within weeks.
- Source: zendesk.com/customer/new-look.

**12. WeRoad — Travel · Zendesk AI Agent "Bob"**
- Use case: Travel Q&A and booking support.
- Metrics: 30% ticket resolution by AI; 93% CSAT; 0-minute AI first response; +20% YoY agent conversions.
- Source: zendesk.com/customer/weroad.

**13. Liberty London — Luxury Retail (UK) · Zendesk AI**
- Use case: Intelligent triage + intent/sentiment labeling across phone, chat, email, WhatsApp.
- "Human-like" framing: AI routes based on sentiment + language so humans arrive context-ready.
- Metrics: –73% first reply time; –11% resolution time; +9% CSAT; $21,461 annual help-center savings.
- Source: zendesk.com/customer/liberty-london.

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### Ada

**14. Wealthsimple — Fintech (Canada) · Ada Reasoning Engine**
- Use case: Retail-investor self-service across 3M users.
- "Human-like" framing: Moved from scripted chatbot to "reasoning" agent that handles complex intent.
- Metrics: +10% CSAT; higher automated resolution rate; freed team for complex issues.
- Source: ada.cx/case-study/wealthsimple.

**15. Loop Earplugs — DTC Consumer · Ada AI Agent**
- Use case: Global DTC support.
- Metrics: 80% CSAT; AI workload equivalent to 25 FTEs; 357% ROI.
- Source: ada.cx/case-study/loop-earplugs.

**16. Tilt — SaaS · Ada**
- Metrics: 84% automated resolution across channels.
- Source: ada.cx/case-studies.

**17. IPSY — Beauty Subscription · Ada**
- Metrics: 943% ROI on generative-AI investment; simultaneous CSAT and automated-resolution lift.
- Source: ada.cx/case-studies.

**18. Indigo — Retail (Canada) · Ada + Convey**
- Use case: "Where is my order" (WISMO) deflection across 8 delivery carriers.
- Metrics: –14% orders requiring CS intervention; $150K saved; 120,000 proactive reroutes during holiday.
- Source: ada.cx/case-study/indigo.

**19. Neptune Flood / Wave — Insurance / SMB Finance · Ada**
- Metrics: Neptune Flood –78% cost per ticket; Wave –65% ticket creation in first month.
- Source: ada.cx/case-studies.

**Ada aggregate benchmark:** resolution rate 30% → 60% after GPT-4 integration; top performers >80%; 4B+ interactions across 350+ brands (Meta, Verizon, AirAsia, Yeti, Square). Source: ainews.com/p/ada-uses-gpt-4; ada.cx.

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### HubSpot (Breeze Customer Agent)

**20. Agicap — Fintech SaaS · Breeze**
- Use case: Content generation + workflow/copilot.
- Metrics: 750 hours/week saved; +20% deal velocity; 100% CRM adoption by sales reps.
- Source: hubspot.com/case-studies/agicap-1.

**21. Kaplan Early Learning — EdTech · Breeze**
- Use case: Service response automation.
- Metrics: –30% avg ticket response time; 25–30% self-serve via AI chat; +63% YoY CS staff retention.
- Source: hubspot.com/case-studies/kaplan.

**22. Xeople — Mid-Market Software · Breeze Customer Agent**
- Metrics: 73% CSAT across 307 surveyed interactions.
- Source: hubspot.com/breeze-ai-use-case-library.

**23. "RevPartners" / Unnamed Vehicle Customization Company — Breeze ("Jarvis")**
- Metrics: 100 tickets/month resolved with no human; 120 hrs/yr saved (15 workdays); knowledge base built from analysis of 6,000 past tickets.
- Source: hubspot.com/startups/ai/launching-breeze-customer-agent; anneomaly.com case writeup.

**Breeze aggregate benchmark:** 65%+ conversations auto-resolved (top teams 90%); 39% faster resolution; –77% tickets handled by humans for deploying teams; +10% close rate. Source: hubspot.com/products/artificial-intelligence/ai-customer-service-agent.

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### Drift (Conversational Marketing / Sales AI)

**24. Okta — Identity · Drift**
- Use case: Inbound website qualification + multilingual sales chat.
- Metrics: 30× Q/Q pipeline influenced; 2× MQL → SQL conversion; fastest channel MQL → pipeline.
- Source: drift.com/case-studies/okta.

**25. Tenable — Cybersecurity · Drift Conversational AI**
- Metrics: 3× qualified pipeline.
- Source: drift.com/blog/tenable-conversational-ai.

**26. EAB — Higher-Ed Research/Advisory · Drift**
- Metrics: +120% demo requests; 2× qualified leads.
- Source: salesloft.com/resources/case-studies/eab.

**27. Emerson — Industrial/Engineering · Drift**
- Metrics: 600+ meetings booked; 80% of bot traffic from net-new contacts.
- Source: salesloft.com/resources/case-studies/emerson.

**28. Drift + Lift AI Cohort (21 clients, 22M+ visitors)**
- Use case: Intent-scored chat routing (high-intent → live rep; medium → qualification bot; low → nurture bot).
- Metrics: 9× pipeline lift (0.4% → 3.7% conversion); 11.7% conversion on high-intent cohort.
- Source: lift-ai.com/case-studies/drift-9x-conversions.

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### Microsoft Customer Stories (Copilot / Copilot Studio / Power Platform)

**29. Virtua Health — US Healthcare · Copilot Studio + Power BI**
- "Human-like" framing: Explicit vendor quote — presents patient data in "human-like language that is easy for people to digest and act upon."
- Metrics: Clinician review 30 min → 5 min per patient; +80% sepsis identification.
- Source: microsoft.com/customers/story/26318-virtua-health.

**30. Morningstar — Financial Research · Microsoft 365 Copilot + MCP**
- Use case: Advisor research + client-ready portfolio explanations.
- "Human-like" framing: Natural conversational interaction with firm-internal data.
- Metrics: Generation of research-backed portfolio insights "in minutes" (qualitative; no deflection/CSAT numbers published).
- Source: microsoft.com/customers/story/26333-morningstar-inc.

**31. "Ask Microsoft" — Microsoft's Own Customer Support Agent · Copilot Studio**
- Use case: Public web agent for product inquiries (millions of visitors).
- Metrics: –61% latency; –70% human escalations; 10× signup completion lift.
- Source: microsoft.com/customers/story/26166-microsoft-microsoft-copilot-studio.

**32. JCB — Construction Equipment · Microsoft 365 Copilot**
- Metrics: 83% avg monthly usage since June 2024; ~6 hours/employee/month saved.
- Source: microsoft.com/customers/story/25324-jcb.

**33. Nsure.com — Digital Insurance · Power Automate + Azure OpenAI**
- Use case: Voice/email/SMS interactions — 100,000+ monthly.
- Metrics: –60% manual processing time; –50% associated cost.
- Source: microsoft.com/customers/story/1728829430186194098-nsure.

**34. Lumen Technologies — Telco · Microsoft Copilot**
- Metrics: Seller research 4 hrs → 15 min; ~$50M annual revenue impact.
- Source: microsoft.com/customers/story/1771760434465986810-lumen.

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### Google Cloud (Gemini / Vertex AI)

**35. Callers — Voice AI Operator · Gemini**
- "Human-like" framing: CTO quote — "Gemini is the heart of our human-like agents. It delivers the best blend of latency and quality…"
- Metrics: 30× scale to "hundreds of thousands of daily calls"; 250,000+ daily interactions; –30% latency; improved conversion/connect rates.
- Source: cloud.google.com/customers/callers.

**36. Best Buy — Retail · Gemini + Vertex AI**
- Use case: "Gift Finder" shopping assistant; gen-AI virtual assistant for self-service support; agent-assist with sentiment detection.
- "Human-like" framing: "Human-like shopping assistant" positioned on personalized recommendations.
- Metrics: Production-cycle acceleration; Q&A generation at "fraction of previous cost"; claimed CSAT + trust lift (no hard numbers).
- Source: cloud.google.com/customers/bestbuy.

**37. Oscar Health — US Health Insurance · Vertex AI**
- Use case: Clinical Intake Bot ahead of virtual urgent care visits.
- "Human-like" framing: Natural adaptive conversation replacing rigid intake forms; mirrors how medical assistants triage in brick-and-mortar clinics ("top of license" model).
- Metrics: No public quantitative CSAT/resolution data; qualitative lift in provider focus.
- Source: medium.com/oscar-tech (Oscar's own engineering blog; referenced by Google Cloud).

**38. Revolut — Fintech · Google Cloud AI Agents**
- Use case: FinCrime agent (2M tasks/mo over 700K customers) + support chatbot.
- Metrics: ~80% support resolution without human; ~1.2M tickets/mo absorbed.
- Source: nebius.com/customer-stories/revolut (partner infra story; Revolut also profiled in Google Cloud Gemini at Work 2024).

**39. Albertsons — Grocery Retail · Vertex AI Conversational Commerce Agent**
- Use case: Shopping discovery-to-purchase dialogue.
- Metrics: Incremental basket add-ons (qualitative early signal; no volumes published).
- Source: cloud.google.com/blog/products/ai-machine-learning/introducing-conversational-commerce-agent-on-vertex-ai.

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## Patterns & Trends

*Patterns updated April 2026 to reflect post-Klarna narrative shift and 2025 data.*

1. **"Resolution rate" is the master metric — but the definition is shifting.** Across every vendor, the single most-cited number is % conversations resolved without human handoff. Anchored ranges vendors publish as typical:
   - Fin: 51% out-of-box → 66% avg → 80%+ for top customers.
   - Ada: 60% avg post-GPT-4, >80% for top performers.
   - Breeze: 65% avg, 90% top.
   - Zendesk cases: 30–42% on real customer deployments.
   - Agentforce (Heathrow): 90% in a vertical-concierge scope.
   The headline numbers cluster suspiciously around 50–80%, and nearly always exclude complexity weighting.

2. **"Human-like" is almost never measured directly.** None of the 39 cases reports a Turing-style, blind-preference, or perceived-humanness score. The term is used rhetorically; the supporting metrics are deflection, latency, CSAT, conversion, or cost. Virtua Health and Callers are the only cases where a customer is quoted using "human-like" explicitly as a product claim.

3. **Latency is becoming a proxy for humanness in voice.** Callers (Gemini) and Ask Microsoft (Copilot Studio) both cite latency reductions (–30% and –61%) as core to the "feels human" pitch. This echoes Google Cloud's "thinking budget" framing — trading reasoning depth for turn-taking speed.

4. **Brand voice + tone shifting is the new table stake.** Zendesk (New Look), Intercom Fin ("Behavior" pillar, 45 languages), and Salesforce (Prompt Builder) all lead with tone-matching as a first-class feature. Two years ago case studies led with "answers correctly"; now they lead with "sounds like us."

5. **Clarifying-question capability is the preferred signal of intelligence.** Fin (multi-source answers, clarifying questions), Salesforce Einstein redesign (behavioral triggers), and Oscar's Clinical Intake Bot all frame "asks follow-ups" as the humanizing feature — not fluency or style.

6. **Escalation handoffs are narrated as feature, not failure.** Zendesk (private-note on low confidence), OpenTable ("flexibility into escalation logic"), Ada (reasoning engine decides when to escalate). Vendors are selling *graceful* handoff, implicitly admitting sub-100% autonomy — a shift from 2023's "full automation" framing.

7. **ROI quoted as multiple-of-investment, not absolute dollars.** Ada (357%, 943%), Wiley (213%), Drift (9×, 30×). Percentage multipliers with undefined baselines dominate; absolute $ figures (Wiley's $230K, Liberty's $21K, Ada/Indigo's $150K) appear mostly in smaller or older cases.

8. **Volume-scaling stories are replacing cost-cutting stories.** Synthesia's 690% spike absorbed at flat headcount, Revolut's 1.2M tickets/month, Heathrow's 83M passengers — the "growth without hiring" narrative is more prominent than "replace 50% of agents."

9. **Vertical-specialization cases produce higher headline numbers.** Airport concierge (Heathrow, 90%), clinical intake (Oscar), financial crime ops (Revolut, ~80%) outperform generic SaaS support — a consistent pattern suggesting scope narrowing correlates with claimed human-likeness.

10. **Hyperscaler stories lean infrastructure-first; SaaS stories lean outcome-first.** Microsoft + Google Cloud cases emphasize platform capabilities (Vertex AI, Copilot Studio, MCP) with fewer discrete conversion metrics; Intercom/Ada/Drift/HubSpot lead with conversion/resolution/ROI. The former are courting builders; the latter are courting buyers.

11. **Empathy is becoming an explicit product metric (2025–2026).** Salesforce Agentforce's published "lessons from 500,000 conversations" frames empathetic acknowledgment as the single biggest CSAT lever — above raw resolution speed. This is convergent with Cresta's empathy pipeline (B-industry, study #12) and with the academic literature (A-academic, study #3 Crolic et al., study #11 Ayers et al.). A pattern that was anecdotal in 2024 is now appearing in vendor data at scale.

12. **Voice humanization is commercially material but evidentially thin.** Sierra ($150M ARR, January 2026; voice surpassing text as primary channel by October 2025), Decagon (voice positioned for mortgage servicing), and Fin Voice (Intercom Pioneer 2025) represent commercial traction in voice humanization at scale. None has published peer-reviewed or A/B-test data on what specifically makes voice feel human.

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## Gaps in the Commercial Record

1. **No perceived-humanness measurement.** Across 39 cases, zero publish a direct score for "did users think they were talking to a human?" or "did users prefer the AI response blind to a human one?" — the exact question this project is investigating. The commercial record cannot tell you whether any of these systems actually feel human; it can only tell you they deflected tickets.

2. **CSAT lifts are often absent or single-digit.** Where CSAT is reported (Liberty +9, Wealthsimple +10, Synthesia +33), the baselines are never shared. A +9 on a 70 baseline and a +9 on a 20 baseline are very different claims. Most cases omit CSAT entirely in favor of deflection.

3. **No adversarial or bad-path disclosures.** No case reports hallucination rates, mis-routing rates, or what happened on the 20–50% of conversations the AI *didn't* resolve. Fin's "99.9% accuracy" and Ada's "fine-tuning to reduce hallucinations" are asserted without methodology.

4. **Tone-of-voice effectiveness is unverified.** Every major vendor now offers brand-voice tuning, but no case publishes A/B data on whether tone-matching drove the reported CSAT/resolution gains or whether raw accuracy did.

5. **Voice AI cases are rare relative to text.** Only Callers, Nsure, and (indirectly) Oscar cover voice. The "human-like" claim is far softer in voice commercial literature than the underlying 2026 tech would suggest.

6. **Cross-vendor comparability is zero.** "Resolution" means different things at Fin (full auto-close), Zendesk (AI-completed without handoff), Ada (reasoning-engine decided), and Breeze (confidence-gated auto-send). Vendors have not adopted a shared definition, so the 51–90% spread is not directly comparable.

7. **Failed or abandoned deployments are now partly visible — but only Klarna went public.** Klarna's CEO acknowledged the reversal publicly in May 2025 (see B-industry, case study #2). But the vendor library as a whole remains selection-biased to successes. The Klarna case is the exception, not the norm.

8. **Absent from the corpus where you'd expect them.** Drift has gone quiet on pure conversational-intelligence claims post-Salesloft acquisition — more pipeline language, less "chatbot feels human" language. HubSpot Breeze cases skew SMB with few enterprise names. No major LLM-era case study from a top-tier consumer bank, airline, or telecom has a "feels human" public metric — possibly a trust/regulatory chilling effect.

9. **"AI slop" backlash is not reflected in vendor literature at all.** Merriam-Webster named "AI slop" Word of the Year 2025. Search volume for "AI slop" increased 9× from 2024. Pinterest and YouTube introduced user controls to limit AI-generated content. None of this consumer/platform sentiment appears in the vendor case-study corpus — vendors are not publishing data on how they detect or address slop-like output from their own systems.

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## Sources

- salesforce.com/salesforce-stories/artificial-intelligence-closes-deals-faster — Salesforce internal sales ops.
- salesforce.com/customer-stories/wiley — Wiley Agentforce case.
- salesforce.com/customer-stories/opentable — OpenTable Agentforce.
- salesforce.com/customer-stories/heathrow-airport — Heathrow "Hallie."
- gen25.com/cases/bijenkorf-einstein — de Bijenkorf Einstein (Salesforce partner).
- intercom.com/customers/anthropic — Anthropic Fin.
- intercom.com/customers/synthesia-pioneer — Synthesia 690% spike case.
- intercom.com/customers/fundrise — Fundrise Fin.
- intercom.com/customers/lightspeed — Lightspeed Fin + Copilot.
- intercom.com/blog/whats-new-with-fin-3 — Fin aggregate benchmarks.
- zendesk.com/customer/new-look — New Look.
- zendesk.com/customer/weroad — WeRoad "Bob."
- zendesk.com/customer/liberty-london — Liberty London.
- zendesk.com/blog/zip1-how-zendesk-uses-agentic-ai — Zendesk agentic AI platform framing.
- ada.cx/case-study/wealthsimple — Wealthsimple Ada.
- ada.cx/case-study/loop-earplugs — Loop Earplugs Ada.
- ada.cx/case-study/indigo — Indigo Ada + Convey.
- ada.cx/case-studies — Ada case library (Tilt, IPSY, Neptune Flood, Wave).
- ainews.com/p/ada-uses-gpt-4 — Ada GPT-4 resolution-rate lift.
- hubspot.com/case-studies/agicap-1 — Agicap Breeze.
- hubspot.com/case-studies/kaplan — Kaplan Early Learning Breeze.
- hubspot.com/breeze-ai-use-case-library — Xeople + library.
- addaxlab.com/blog/how-hubspot-breeze-ai-cuts-time-to-first-response-by-40-this-month — Breeze aggregate benchmarks.
- drift.com/case-studies/okta (salesloft.com mirror) — Okta Drift.
- drift.com/blog/tenable-conversational-ai — Tenable Drift.
- salesloft.com/resources/case-studies/eab — EAB Drift.
- salesloft.com/resources/case-studies/emerson — Emerson Drift.
- lift-ai.com/case-studies/drift-9x-conversions — 21-client Drift+Lift cohort.
- microsoft.com/customers/story/26318-virtua-health — Virtua Health Copilot.
- microsoft.com/customers/story/26333-morningstar-inc — Morningstar Copilot.
- microsoft.com/customers/story/26166-microsoft-microsoft-copilot-studio — "Ask Microsoft."
- microsoft.com/customers/story/25324-jcb — JCB Copilot.
- microsoft.com/customers/story/1728829430186194098-nsure — Nsure.com Power Platform.
- microsoft.com/customers/story/1771760434465986810-lumen — Lumen Copilot.
- cloud.google.com/customers/callers — Callers Gemini (voice).
- cloud.google.com/customers/bestbuy — Best Buy Gemini "Gift Finder."
- medium.com/oscar-tech — Oscar Clinical Intake Bot.
- nebius.com/customer-stories/revolut — Revolut AI agents.
- cloud.google.com/blog/products/ai-machine-learning/introducing-conversational-commerce-agent-on-vertex-ai — Albertsons conversational commerce agent.
- salesforce.com/news/stories/agentforce-customer-support-lessons-learned/ — 500,000 Agentforce conversations; empathy as explicit product spec.
- salesforce.com/blog/support-requests-agentforce/ — 2M+ Agentforce conversations milestone.
- hbs.edu/faculty/Pages/item.aspx?num=67220 — HBS Agentforce "Limitless Workforce" case (April 2025).
- intercom.com/blog/headlines-from-pioneer-2025/ — Fin 3, Fin Voice, Procedures launch.
- sacra.com/c/sierra/ — Sierra $150M ARR (January 2026); voice surpasses text by October 2025.
- pbs.org/newshour/nation/merriam-websters-word-of-the-year-for-2025-is-ais-slop — "AI slop" Word of the Year 2025.
- webpronews.com/ai-slop-floods-social-media-in-2025-backlash-spurs-2026-reforms/ — Platform responses to AI slop.
