Steve Hind
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Updated
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Fact-checked against Gartner & Forrester data
To reduce customer service costs with AI, move the 50 to 60 percent of contacts that are still transactional, per McKinsey analysis of millions of interactions, onto an AI agent that resolves them end to end, and pay $0.90 to $0.99 per resolution, plus a plan fee, instead of the $8.01 per live contact recorded in a Gartner poll of service leaders. On a 10,000-contact queue that is about a 35% cut in monthly support cost when half the contacts are resolved, and about 21% when regulatory carve-outs push the resolved share down to 35%. Per-resolution platforms such as Lorikeet publish the price of each resolution, which makes that arithmetic checkable before you sign. Below: the cost model, the break-even point, and what fintech, healthcare and insurance teams cannot automate.
Key takeaways
Unit economics: a live-channel contact averaged $8.01 in Gartner's 2019 poll, while published per-resolution rates for chat, email and SMS run $0.90 to $0.99.
Break-even comes early: with $8.01 avoided per contact, a $5,100 monthly plan pays for itself at about 720 resolutions a month; on a wage-only $3.60 contact it takes about 1,890.
Savings track completed work. Assist lifted output 14% in the NBER field study; Gartner projects 30% lower operating costs only where agentic AI resolves 80% of common issues, by 2029.
Regulated carve-outs shrink the resolvable share, not the method. Dispute decisions, hardship, clinical judgment and claims decisions stay human, so model them as human cost from day one.
AI costs are not fixed. Gartner predicts GenAI cost per resolution will exceed $3 by 2030, so lock per-resolution rates and escalation billing terms into the contract.
Which AI platforms reduce support costs today?
Several AI agent platforms now price per outcome, which is what makes a cost model like the one below possible. In no particular order:
Lorikeet resolves chat, email, SMS and voice tickets end to end at a published $0.99 or $0.90 per chat, email or SMS resolution on top of a $2,100 or $5,100 monthly plan, and does not charge for escalations or unresolved tickets.
Fin (now part of Salesforce) charges $0.99 per outcome on an existing helpdesk; a Procedure that ends in a handoff to a human counts as a billable outcome.
Zendesk includes AI agents in its Suite and Support plans and bills per automated resolution, listed at $2.00 pay-as-you-go, alongside per-agent seat pricing.
Decagon publishes no price list; it offers per-conversation pricing, or per-resolution pricing at a higher rate.
How much can AI reduce customer service costs?
The published range runs from a 14% productivity gain when AI assists a human to a projected 30% cut in operating costs when AI resolves the ticket itself. Where you land depends on how much of each ticket the AI completes.
The most rigorous measurement is the NBER working paper Generative AI at Work, which tracked an assist tool across 5,179 support agents: issues resolved per hour rose 14% on average and 34% for novices. Headcount stays; handle time falls. At the other end, Gartner predicted in March 2025 that agentic AI will autonomously resolve 80% of common customer service issues by 2029, cutting operational costs by 30%. Treat that as a ceiling, not a budget line.
The volume is there to automate. McKinsey's March 2025 analysis found that 50 to 60 percent of customer interactions remain transactional across more than 30 organizations, around 50 percent of call volume at one European bank, and that an energy company cut billing call volume by about 20 percent by wiring an AI voice assistant into its back-end workflow. Klarna's February 2024 release reported its assistant handled two-thirds of chats in its first month and cut repeat inquiries by 25%, self-reported and first-month, but the repeat-contact figure is the one to copy into your model.
One counterweight belongs in every business case. In January 2026 Gartner predicted that GenAI cost per resolution will exceed $3 by 2030, higher than many B2C offshore human agents, as vendors move from subsidized growth to profitability. Its analyst put it bluntly: "Full automation will be prohibitively expensive for most organizations." The answer is not to avoid AI; it is to automate the tickets where the margin is wide and to contract the rate.
What does a human support ticket cost?
Two public anchors bracket it. Gartner's 2019 poll of service leaders put live channels (phone, chat and email) at an average of $8.01 per contact, against about $0.10 for self-service. The US Bureau of Labor Statistics reports a median customer service wage of $21.53 an hour in May 2025, so a 10-minute contact costs about $3.60 in base wage and a 20-minute call about $7.20, before benefits, software, supervision and QA. The gap between the two numbers is overhead, and it is real.
Your own figure comes from one formula: cost per ticket equals labor plus tooling plus overhead, divided by tickets handled. Ask finance for the loaded number, then split it by channel and handle time, because phone and multi-system tickets cost several times a simple chat. Our guide to customer service cost per ticket gives industry benchmarks and the repeat-contact multiplier to apply.
What does an AI resolution actually cost?
On per-resolution pricing, the effective cost of each resolution is the monthly plan fee plus resolutions times the rate, plus any QA, divided by resolutions. Lorikeet's published pricing: Start at $2,100 a month and Scale at $5,100 a month, paid annually; chat, email and SMS resolutions at $0.99 or $0.90; voice at $1.50 or $1.20 on a 3-minute average; automated QA at $0.30 or $0.27 per conversation. Unresolved or unsatisfactory tickets and escalations to a person cost nothing.
1,500 chat resolutions a month on Start: ($2,100 + $1,485) / 1,500 = about $2.39 per resolution.
5,000 chat resolutions a month on Scale: ($5,100 + $4,500) / 5,000 = about $1.92 per resolution.
Because the plan fee is fixed, the effective cost falls as volume rises. The pricing trap is per-conversation billing, which charges for tickets the AI touched but did not finish.
Where is the break-even point?
Break-even resolutions per month equal the plan fee divided by the difference between the human cost you avoid per contact and the rate you pay per resolution.
Start plan, $8.01 avoided: $2,100 / ($8.01 - $0.99) = about 300 resolutions a month.
Scale plan, $8.01 avoided: $5,100 / ($8.01 - $0.90) = about 720 resolutions a month.
Start plan, $3.60 wage-only cost: $2,100 / $2.61 = about 805 resolutions a month.
Scale plan, $3.60 wage-only cost: $5,100 / $2.70 = about 1,890 resolutions a month.
One caveat decides whether those savings are cash. Avoided cost is only real when the freed hours stop a hire, a temp contract or overtime. Gartner found only 20% of service leaders had reduced staffing because of AI, so count savings as avoided hiring unless you have a plan to reduce headcount. The mechanics of that are in our guide to scaling customer support without hiring.
Worked example: a 10,000-contact consumer lender
A consumer lender handles 10,000 contacts a month across chat, email and phone: payment dates, balances, identity checks, card issues, with disputes, hardship and complaints mixed in. At $8.01 per contact the baseline is $80,100 a month. It runs on the Scale plan. Substitute your own loaded cost.
Base case, 50% resolved end to end. That is below the 60% of inbound that Carmoola, an FCA-regulated UK car finance lender, publishes. 5,000 resolutions at $0.90 is $4,500, plus the $5,100 plan, plus automated QA on all 10,000 conversations at $0.27, $2,700: $12,300 in total. Avoided human cost is $40,050. Net saving: $27,750 a month, about 35% of the baseline.
Regulated case, 35% resolved, because disputes, hardship and complaints route to people even when the conversation is simple. 3,500 resolutions cost $3,150, plus $5,100 and $2,700: $10,950. Avoided cost is $28,035. Net saving: $17,085 a month, about 21%.
The carve-outs cost about $10,700 a month in savings; they do not break the case. Both outcomes sit near Gartner's 30% projection, which is a useful sanity check. The 50% is an assumption: Lorikeet does not publish a platform-wide resolution rate, so replay your historical tickets in simulations to get your own resolved share before the number goes in a budget.
What can't you automate in fintech, healthcare and insurance?
Decisions with legal consequences, and anything that needs clinical or underwriting judgment. The AI can take the intake and do the arithmetic; a person makes the call. That moves cost rather than removing it, which is why these tickets belong on the human side of the model.
Fintech. Under Regulation E, a financial institution must determine whether an electronic transfer error occurred within 10 business days of the notice, or take up to 45 days if it provisionally credits the account. An AI agent can collect the details and start the clock; the decision stays with a person. Carmoola's story treats affordability and missed-repayment questions in FCA-regulated credit as decisions rather than lookups. See automating dispute intake for the workflow.
Healthcare. easykind's agent never names a product, in line with Australian government rules, and when a patient reports concerning side effects it tells them to stop the medication, call emergency services, and escalates to a human. Eucalyptus routes medically urgent tickets to its clinical team.
Insurance. First notice of loss intake, claim status and policy servicing can be resolved end to end; coverage questions that need underwriting judgment and sensitive claims decisions escalate to people with full context, as the insurance page describes.
Everywhere. Gartner predicts that by 2028, regulation on the right to talk to a human will raise assisted service volume by 30%. Budget a human floor that grows with your customer base.
Two adjustments follow. Take regulated ticket types out of the resolvable share before you run break-even, and check how the contract bills handoffs, because an escalated ticket billed as an outcome is paid twice. And note what McKinsey found among the few organizations that cut interactions by 10 to 15 percent or more a year since 2022: they solved data and system integration, fixed broken processes and addressed risk concerns first. Security review is the first gate in these industries; Lorikeet's trust page lists SOC 2 Type II, ISO 27001:2022, HIPAA and GDPR, with BAAs signed for healthcare customers.
Seven levers that move the bill
Resolve the ticket end to end. Verify the customer, read the account, apply the policy, take the action, confirm the outcome. Answering without acting leaves the expensive part on your queue.
Take voice off the human queue. Phone is usually the costliest channel because one agent handles one call at a time. A voice agent that cannot take actions is an IVR with better manners.
Prevent the repeat contact. Every second contact is a full-price ticket. Track reopen and second-contact rates on AI-handled tickets from week one.
Score every conversation. Manual QA samples; automated QA such as Coach reviews all of them for cents each and catches the drift that creates repeat contacts.
Assist the humans who remain. NBER measured 14% more throughput, 34% for novices, and McKinsey reports 20 to 30 percent shorter time to proficiency from simulation-led onboarding.
Absorb peaks without temporary hiring. AI capacity scales both ways, so a billing run or tax deadline stops triggering a hiring cycle.
Pay per outcome. Define resolution in the contract and exclude escalations. See resolution versus deflection for the definition to use.
Where do the savings not show up?
On the headcount line in year one, in customer trust when the exit to a person is hidden, and in tickets the AI touches but does not finish. Gartner expects half of the companies that cut service staff because of AI to rehire by 2027, and found 95% of service leaders plan to retain human agents. A survey of 5,728 consumers found 64% would prefer companies did not use AI in customer service, with difficulty reaching a person the top concern. Human handle time rises after launch because the easy tickets leave the queue; that is expected, not failure. And Gartner predicts none of the Fortune 500 will have fully eliminated human customer service by 2028.
Reducing customer service costs with AI comes down to three numbers you can check: your loaded cost per contact, your contracted cost per resolution, and the share of tickets the AI actually finishes once regulated work is carved out. Get the third one from your own tickets, not a vendor average. To run this model on your queue, book a demo and bring a month of tickets.
Frequently asked questions
How can I reduce customer service costs with AI?
Move the transactional contacts, which McKinsey finds are still 50 to 60 percent of interactions, onto an AI agent that resolves them end to end, and pay per resolution rather than per seat or per conversation. Compare your loaded cost per contact (Gartner's poll put live channels at $8.01) with the effective cost per AI resolution, including the plan fee, and count savings only on tickets confirmed resolved. Keep disputes, hardship, clinical and claims decisions with people and model them as human cost.
How much can AI reduce customer support costs?
Published evidence runs from a 14% productivity gain when AI assists agents (NBER, 5,179 agents) to Gartner's projected 30% cut in operating costs by 2029 when agentic AI resolves 80% of common issues. In a worked example of 10,000 contacts at $8.01 each, resolving 50% end to end on a $5,100 monthly plan saves about 35% of monthly cost; resolving 35%, after regulated carve-outs, saves about 21%.
What does a human-handled support ticket cost?
Gartner's 2019 poll of service leaders put live channels at an average of $8.01 per contact, against about $0.10 for self-service. From wages alone, the BLS median of $21.53 an hour means a 10-minute contact costs about $3.60 and a 20-minute call about $7.20 before benefits, software, supervision and QA. Use your own loaded cost: labor plus tooling plus overhead, divided by tickets handled, split by channel.
How many AI resolutions does it take to break even?
Divide the monthly plan fee by the human cost avoided per contact minus the rate per resolution. At $8.01 avoided, a $2,100 plan at $0.99 per resolution breaks even at about 300 resolutions a month, and a $5,100 plan at $0.90 at about 720. At a wage-only $3.60 per contact, the same plans need about 805 and 1,890 resolutions a month.
What can't AI automate in fintech, healthcare and insurance?
Decisions with legal or clinical consequences. Under Regulation E a bank must determine whether an error occurred within 10 business days, or up to 45 days with provisional credit; AI can take the intake but a person decides. Clinical judgment, side-effect reports and sensitive claims or coverage decisions also go to people. Gartner predicts right-to-human regulation will raise assisted service volume by 30% by 2028, so budget a human floor.
Does AI customer support reduce headcount?
Rarely in the first year. Gartner found only 20% of service leaders had reduced staffing because of AI, and expects half of the companies that cut staff because of AI to rehire by 2027. The realistic outcome is flat headcount absorbing more volume, with savings arriving as avoided hires, temp staff and overtime, and a human team that shifts toward judgment, exceptions and supervising the AI.
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