In tech companies, the best LLM automation bet is the full technical-support resolution loop
Asked:
“Whats a a business process that as it currently stands could benefit most from AI automation with LLMs? So like the largest pain and the largest market”
Asked (follow-up):
“what about processes that occur in digital/tech companies”
The ranking below synthesizes eight evidence rows from eight sources — vendor case studies, an NBER working paper, an AWS SRE evaluation, IBM’s 2025 breach study, G2’s 2026 survey of 1,038 B2B buyers, McKinsey’s gen-AI sizing, and METR’s developer-productivity experiments — covering support, SRE and security operations, software engineering, and enterprise buying friction.
Opportunity landscape: five tech-company processes across six lenses
Band words (Large, High, Contested…) are our qualitative synthesis of the sources, not measured scores. Green = favorable for a builder; for competition and execution risk, lower is greener. Hover or tap a row name for the headline evidence.
Support automation has the cleanest proven ROI: Docebo reports 35% automated chat resolution, 58% faster resolutions, 20% lower ticket volume and >$250K annual savings across a 122-agent organization — vendor-reported estimates.
zendesk.com Rigorous field evidence elsewhere shows AI augmentation moving frontline outcomes: late deliveries −11%, bad ratings −22%, attrition −21% for AI-assisted couriers.
nber.org
Incident investigation is the richest per-case prize: one AWS Enterprise Support SRE team found roughly one-third of quarterly case-effort hours fully addressable by an agent and two-fifths partially; an hours-long investigation finished in minutes — one representative team, composite data.
repost.aws On the security side, extensive AI and automation correlated with breaches 80 days shorter and $1.9M cheaper against a $4.44M global ($10.22M US) average.
www-api.ibm.com
Software engineering is the biggest pool and the shakiest wedge: McKinsey sizes gen-AI potential at 20–45% of software-engineering spend
mckinsey.com, yet METR measured experienced maintainers 19% slower with early-2025 tools, and its rerun was inconclusive.
metr.org Even GitHub finds that too many tools degrade agent performance by 2–5 points on benchmarks.
github.blog
Security review is where B2B revenue actually stalls: IT security review is the single biggest post-selection delay for 39% of buyers and 50% of enterprise buyers — the best narrow, revenue-linked wedge, though a smaller labor pool than support or engineering.
sell.g2.com
Ranked decision table
| # | Process | Verdict | Headline evidence | Source |
|---|
Product wedge: an AI resolution engineer for one stack
1 · IntegrateTicketing, product analytics, logs and traces, CRM and account data, docs, status history, incident systems
2 · Read-only resolutionTriage, retrieve context, search prior incidents, diagnose likely causes, cite sources, draft the reply
3 · Approved actionsReversible, allow-listed actions with human approval and full audit logs; escalate with an evidence packet
4 · Outcome pricingCharge on verified resolutions, engineering hours saved, or reduced MTTR — never seats or messages
5 · MoatResolution and outcome data, deep integrations, stack-specific diagnostics, permissions, evals, action safety
Start narrow: one technology stack or software vertical, read-only first, actions later.
Read the numbers with these caveats
• Docebo’s savings are the vendor’s own estimates, time-bound (35% applies to chats in the first three months), published by Zendesk.
• The AWS SRE addressability figures come from one representative team using composite case data, not a customer environment.
• Coding-productivity evidence conflicts: McKinsey cites 56% faster task completion with Copilot, while METR measured a 19% slowdown for experienced maintainers and calls its own rerun unreliable.
• IBM’s 80-day / $1.9M figures are correlations across breached organizations, not a causal estimate.
Method: 8 evidence rows from 8 source hosts (vendor case studies, NBER w35372, an AWS re:Post SRE evaluation, IBM/Ponemon 2025, G2’s June 2026 survey of 1,038 B2B decision-makers, McKinsey June 2023, METR 2025–26), gathered for this brief. Landscape bands are qualitative synthesis, not measured scores; dollar figures measure annual savings or breach costs as reported by each source. Full study-scope text trimmed for space.