Observations · AI and Business Since 2022
Customer support
The first business function with documented, at-scale labor substitution. Klarna's assistant doing the work of 700 agents (2024) and Salesforce cutting support from 9,000 to ~5,000 roles (2025) made the new economics undeniable: AI handles the routine majority, humans handle exceptions and high-value moments.
What drove it
GPT-4-class models via API, Salesforce Agentforce, purpose-built support platforms (Intercom Fin, Decagon, Sierra), and the Brynjolfsson field study showing novice agents gained the most from AI assistance.
The evolution
2022
The first obvious application: ChatGPT could already answer most tier-one questions. The open question was who would productize it.
- OpenAI launches ChatGPT — the generative AI era begins
It turned years of lab research into a mass-market product overnight and forced every major technology company to respond within weeks. Google declared an internal code red.
2023
Claude and GPT-4 reached production via API, Klarna shipped one of the first ChatGPT plugins, and every support platform started building.
- ChatGPT hits 100M users — fastest-growing consumer app in history
The statistic became the single most-cited proof that generative AI was a mainstream consumer phenomenon, not a tech-insider toy.
- Microsoft ships AI Bing, then puts Copilot inside Office
The first time an incumbent shipped frontier AI directly into products used by billions, and an open assault on Google's core business.
- The first enterprise wave: Salesforce, Morgan Stanley, Bloomberg
Regulated, brand-sensitive industries moved from curiosity to production deployments within four months of ChatGPT's launch.
- GPT-4: AI passes the bar exam
GPT-4 reset expectations of what AI could do in professional domains — law, medicine, finance, coding — and became the benchmark every rival measured against for over a year.
- Anthropic launches Claude; Claude 2 goes public in July
It established a credible safety-focused rival to OpenAI and made long-context document processing a competitive differentiator.
- China answers: Baidu's Ernie Bot, Alibaba's Tongyi Qianwen
It opened the parallel Chinese LLM race under a distinct regulatory regime, confirming generative AI as a US–China strategic competition.
- Amazon commits up to $4B to Anthropic
It completed the alignment of every frontier lab with a hyperscaler patron — frontier AI economics now required Big Tech capital and compute.
- OpenAI DevDay: GPT-4 Turbo, custom GPTs, and the platform play
OpenAI pivoted from model vendor to platform company, aiming to own the application layer the way app stores owned mobile.
2024
Klarna's '700 agents' disclosure made the new economics public, Salesforce launched Agentforce, and GPT-4o's real-time voice opened phone support.
- Klarna: our AI assistant does the work of 700 agents
One of the first widely cited corporate claims of large-scale labor substitution by generative AI, with hard numbers attached.
- Claude 3: Anthropic reaches the frontier
It made Anthropic a credible frontier competitor and introduced the tiered price-performance lineup that became an industry pattern.
- GPT-4o: real-time multimodal AI goes free
Real-time, natural multimodal interaction reached a mass-market free product, resetting the price-performance bar.
- AI goes on-device: Apple Intelligence and Copilot+ PCs
Generative AI became a default operating-system feature on billions of devices, with privacy-preserving local inference as the selling point.
- Salesforce launches Agentforce: enterprise software goes agentic
A major enterprise vendor pivoted its entire strategy from copilots that assist to agents that act.
2025
From assistant to agent: Salesforce cut support from 9,000 to ~5,000 roles, and Stanford documented employment decline among young workers in exposed support occupations.
- MIT: 95% of enterprise GenAI pilots show no P&L impact
The '95% fail' statistic became the most-cited data point in the AI bubble debate.
- AI reaches the workforce: Amazon cuts 14,000 as the evidence mounts
AI-driven workforce reduction moved from prediction to documented practice, with major employers explicitly linking headcount to AI.
2026
AI-first support became the default posture as the layoff wave continued; reliability gains like GPT-5.5's halved hallucination rate pushed containment higher.
- The AI layoff wave: payroll becomes capex
The first sustained period in which profitable companies explicitly tied workforce reductions to AI adoption and capex funding.
- GPT-5.5: OpenAI's flagship becomes an agent
OpenAI's flagship line moved decisively from chat toward computer-operating agents — with reliability, not capability, as the headline metric.
- Salesforce buys Fin for $3.6B on a 76% resolution claim
The largest consolidation yet in AI customer support, and the number at the centre of it deserves reading carefully. A resolution rate measures volume that never reached a human. It does not measure whether the customer's problem was solved, whether they came back three days later, or whether they simply gave up. Those are different questions, and only the first one is easy to instrument — which is precisely why it is the one that gets quoted.
- DeepL buys Mixhalo, moving translation toward live interpretation
Machine translation has been encroaching on written work for a decade. Live simultaneous interpretation has held out, because it runs in real time, under social pressure, with no edit pass and no second attempt — the conditions under which tacit skill matters most. Buying a live-event audio platform is a statement about which direction the frontier is moving.
- Concentrix cuts guidance while AI deals grow 400%
Read the two halves of the release against each other. The AI product line is growing fast in percentage terms off a small base; the services business still sets the guidance, and the guidance came down. This is what the middle of a service-to-software transition looks like on an actual income statement — not a clean pivot, but a fast-compounding new line that cannot yet carry the company, disclosed in the same document as a cut.
Key sources
The papers, announcements, and reports that document this industry's shift. Each also lives in the Library.
What businesses do differently
Support became a deflection-rate and resolution-quality discipline rather than a headcount discipline. Companies route by complexity, measure AI containment honestly, and rebuild knowledge bases as machine-readable sources of truth.
What this means for founders and leaders
Support economics changed permanently — plan for AI-first support from day one, with human escalation as a designed experience rather than a fallback. For BPO and CX businesses, the move up the value chain (quality, judgment, integration) is existential.