Customer Support
Take the repeat questions off your queue, give your reps better answers, and cut resolution times.
Updated 4 days ago · 10 sources
Who already did it
- Learn from thisEnterprise
Commonwealth Bank of Australia
The bank wanted lower call centre costs after rolling out an AI voice bot.
The bank reversed the decision to cut all 45 roles.
So: Count call volume yourself for a full quarter after go-live, overtime and managers on phones included, before you cut a single role.
How they did it
It cut 45 customer service roles after saying an AI voice bot had reduced call volumes. The union said volumes were actually rising, with overtime and managers answering phones. The bank apologised to the staff it let go.
- Learn from thisEnterprise
Klarna
Klarna replaced hundreds of support agents with an AI assistant to cut cost.
Support and operations cost $50M in Q3 2025, up from $42M.
So: Send complicated questions to a person from day one, and price what rehiring would cost before you cut agent numbers.
How they did it
The AI assistant handled two thirds of chats, and Klarna said it did the work of 853 people. Customers complained about generic answers on complicated questions. Klarna started hiring human agents again in May 2025.
- Enterprise
Salesforce
Salesforce ran a 9,000-person support team and wanted its own AI agents to carry more.
Support headcount went from about 9,000 to about 5,000.
How they did it
It put AI agents on its own help site and let them take routine customer questions first. People took the escalations. Chief executive Marc Benioff said half of customer conversations now go to AI agents and half to humans.
Tool used Agentforce (Salesforce)
- Enterprise
Home Depot
Customers calling a store got stuck in phone menus before they reached anyone.
Reaches a solution four times faster than the old phone menus.
How they did it
Home Depot put AI voice agents on store phone lines in a 50-store pilot, then started rolling them out to every US store. The agents work out why someone is calling, then answer or route the call.
- Enterprise
SiriusXM
SiriusXM had heavy chat volume from subscribers asking about billing and account changes.
Sierra company blog (vendor) · Dec 2025
How they did it
SiriusXM built a chat agent called Harmony with Sierra, then extended the work. Sierra says Harmony is now the highest-rated and lowest-effort service channel SiriusXM runs.
Tool used Sierra
What to use, who to call
Fin
Answers customer questions in chat and email from your help centre and past tickets, then hands off when stuck.
pay per resolution, about $0.99 eachWeeksSeparate software to buyIT sign-offIs this your first move?
What it fixes. Your team retypes the same twenty answers all day while the hard tickets sit in the queue.
Good fit when. Most of your volume is repeat questions and your help centre articles are already decent.
Skip it if. Your help centre is thin or out of date. It answers from your content, so weak content gives weak answers.
Start with. Pull last month's tickets and count how many repeat the same ten questions — that count is your ceiling.
Take 7 questions to the call
Why call them. You want something live in weeks, sitting on top of the help desk you already run.
What they fix. Repeat questions eat the queue, so your team never gets to the tickets that need them.
Also used by. Software and subscription businesses with a large self-serve customer base
- What exactly counts as a billable resolution, and what happens when the customer comes straight back?
- Show me the resolution rate — the share of conversations the bot closes on its own — for a customer whose help centre is as thin as mine.
- When Fin does not know the answer, what does the customer see and what does my agent see?
- How does the handoff to a human work, and does that person get the whole conversation?
- If Fin tells a customer something wrong and we honour it, who carries that cost?
- What does my bill look like in a month where volume doubles, and is there a cap?
- Which customers switched Fin off, and what reason did they give?
Sierra
Runs branded voice and chat agents that follow your policies, act in your systems, and escalate to people.
enterprise, priced on outcomesMonthsSeparate software to buyIT sign-offIs this your first move?
What it fixes. Phone queues that hold customers, and a chat bot that cannot actually change anything on an account.
Good fit when. You have high phone volume and the calls need real account changes, not just answers.
Skip it if. Small teams. Setup is a build project run with the vendor, and the starting price is high.
Start with. Listen to twenty recorded calls. Mark which ones needed a system change and which only needed an answer.
Take 7 questions to the call
Why call them. Your call volume is large, the calls are complex, and you can staff a real project.
What they fix. Phone queues where the caller needs an actual account change, not a link to an article.
Also used by. SiriusXM and other large consumer subscription and services businesses
- How do you define an outcome I get billed for, and who checks that number?
- What does the agent say on the phone when it cannot do what the caller asked?
- How long before the agent can change something in my billing system, not just talk about it?
- What did your last customer of my size have to staff, in people and in weeks?
- How do you stop the agent promising a refund or a policy we do not offer?
- When the agent escalates mid-call, does the caller have to repeat everything to my person?
- Which deployments underperformed, and what was different about them?
Decagon
An AI agent — software that answers customers without a person — across chat, email and phone, run by your support managers.
mid-market to enterprise, annual contractWeeksSeparate software to buyIT sign-offIs this your first move?
What it fixes. Every change to how the bot behaves sits in an engineering backlog for six weeks.
Good fit when. You have several product lines and your support policies change often.
Skip it if. You have one simple product and one help centre. You would pay for flexibility you never use.
Start with. Name the person on your team who will own the agent's rules. If nobody has time, stop here.
Take 6 questions to the call
Why call them. You have several product lines, policies that change monthly, and nobody spare in engineering.
What they fix. Bot behaviour you cannot change without filing an engineering ticket and waiting a sprint.
- Who on my team writes and changes the agent's rules, and how long is the training?
- Is the number you just quoted deflection — tickets the bot ended — or resolution, and how do you tell them apart?
- How do you handle one product line whose policy differs from all the others?
- What does the agent do with an angry customer, and how does it detect one?
- What does the contract say about accuracy, and what do I get when the agent is wrong?
- How does the price move if my ticket volume drops because the agent is working?
Zendesk
AI agents built into Zendesk that answer, sort, and route tickets, billed only for resolutions Zendesk verifies.
per verified resolution, plus Zendesk seatsUnder a weekAlready in software you ownIT sign-offIs this your first move?
What it fixes. You do not want a second system, a second login, and a second set of reports.
Good fit when. Zendesk is already your help desk and you want the shortest path to something live.
Skip it if. Your product is complex and your answers live in many systems. Test what it resolves before you commit.
Start with. Ask your Zendesk rep what counts as a billable resolution, and get the definition in writing.
Take 6 questions to the call
Why call them. Zendesk is your system of record and you want the shortest path to something working.
What they fix. You already run Zendesk and do not want a second vendor bolted on top of it.
- What does your verification model actually check, and can I see the cases it rejected?
- How does a verified resolution differ from a ticket that simply closed itself?
- Now that you own Forethought, which product am I buying and how long is it supported?
- What resolution rate do customers on my plan and my ticket mix actually reach?
- What does my bill look like if resolutions double, and where is the ceiling?
- When the agent escalates, what does my person see, and does the customer wait again?
What everyone is asking
- NewJul 2026
Best AI for ticket deflection (tickets a bot ends without a person)?
It depends on where your answers already live. Fin and Zendesk agents sit on your help desk and go live fast. Sierra and Decagon build deeper into your systems and cost more.
The short answer
Trade press turned sceptical of deflection in 2026, because a customer who gave up still counts as deflected.
Also worth a look. Fin, Sierra, Decagon, Zendesk AI agents
- NewJul 2026
Does AI support actually cut costs or just move them?
Both happen. Salesforce cut support headcount from about 9,000 to about 5,000. Klarna cut agents, hired people back, and its support and operations cost rose year over year.
The short answer
The companies that kept the savings kept people on the hard tickets. The one that cut deepest ended up rehiring.
Also worth a look. Salesforce, Klarna
- NewJul 2026
What resolution rate (share of chats a bot closes alone) should I actually expect?
Ask for resolution, not deflection. Klarna's assistant handled two thirds of chats. Salesforce says half of customer conversations go to AI agents. Both companies reported those numbers themselves.
The short answer
Every published rate is self-reported. Nobody audits these the way an auditor would check a financial figure.
Also worth a look. Klarna, Salesforce
- NewJul 2026
Will customers hate it?
They mind far less when a person is one click away. Five9 research reported by CX Dive found four in five people will use AI support when that route exists.
The short answer
The same research says 41% are less likely to use a company that uses AI support, rising to 53% with no human option.
Also worth a look. AI-only support, AI with a visible route to a human
- NewJul 2026
Should I cut support headcount when I turn this on?
Do not cut on a forecast. Commonwealth Bank cut 45 roles on a call-volume claim that turned out to be wrong, then apologised and reversed the decision.
The short answer
A union and a tribunal forced those numbers into the open. Most companies never have to show that data.
Also worth a look. Cut headcount first, Hold headcount and measure for a quarter
Try this today
Group last month's tickets by real cause
20 minYou see the handful of reasons behind most of your volume, and which ones a help article prevents.
Copy the prompt
You are a support operations analyst. Below are subject lines and first messages from recent tickets. Customer names, emails and account numbers have been removed. Group them by the underlying reason the customer got in touch, not the words they used. For each group give: the reason in one sentence, the number of tickets, and whether a help centre article could have prevented it. Sort by ticket count, highest first. Put anything you cannot place confidently under 'Unclear' rather than forcing it into a group. Return the result as a plain table. Tickets: [PASTE TICKETS]
One check first. Strip names and account numbers first. Ask your security team before putting customer data into a consumer AI tool.
Rewrite the help article customers still ask about
30 minA shorter article your customers can follow, plus the questions it never answered.
Copy the prompt
You are a support content editor. Below is one help centre article, then five real customer questions it was meant to answer. First, list every question the article does not answer. Then rewrite the article so a customer with no product knowledge can follow it: one task per section, numbered steps, no more than 15 words a step, and no internal terms. Keep every fact and every warning from the original. Where a step needs information the original does not give, write [NEEDS CHECK] instead of guessing. Article: [PASTE ARTICLE] Questions: [PASTE FIVE QUESTIONS]
One check first. The model fills gaps if you let it. Read every [NEEDS CHECK] and confirm the steps yourself before publishing.
Draft a scoring guide for AI answers
25 minA one-page checklist your team can use to grade what the bot sent your customers.
Copy the prompt
You are a customer support quality lead. Build a one-page scoring guide for reviewing answers that AI sent to our customers with no person checking them. Cover five things: factual accuracy, whether it followed our policy, tone, whether it handed off to a person at the right moment, and whether the customer had to come back. For each one give a 1 to 5 scale, plus a plain sentence describing what a 1, a 3 and a 5 look like in a real reply. Then list the kinds of answer a person must always read before it goes out. Our product is [WHAT YOU SELL]. Our customers get in touch most often about [TOP THREE REASONS].
One check first. This is a first draft. Have your policy owner and two senior agents mark it up before you score anyone against it.
Worth following
Support Driven
A Slack community of customer support professionals, with events and a salary database.
daily · community
Why them
Practitioners compare notes on what AI tooling does to their queues and their jobs.
Shep Hyken
Customer service speaker and author who runs an annual customer experience research report.
weekly · newsletter
Why them
He publishes what customers say they want from AI service, not what vendors say.
CX Today
Trade publication covering contact centre technology, vendors, and AI product news.
daily · publication
Why them
It catches vendor changes and acquisitions early, and those move your contract terms.
CX Dive
News site from Informa TechTarget covering customer experience and service operations.
daily · publication
Why them
Original reporting on named companies with real numbers, not recycled vendor claims.
Jeff Toister
Customer service consultant, author, and LinkedIn Learning instructor on service culture.
weekly · blog
Why them
Practical writing on what happens to your team once the easy tickets disappear.
Fin AI research
The engineering research blog of Fin, the vendor that used to be called Intercom.
monthly · vendor research blog
Why them
Detailed write-ups on why support agents fail. This is a vendor, so read it that way.