Getting Started with AI-First Customer Support

Who is this guide for?

• A Customer Support Leader (Head or Director of) OR

• Leading a support transformation project in your organization OR

• An enthusiastic AI early adopter, Operations Manager or Product Manager trying to help your Customer Support team out

What does it mean to be ‘AI-first’ with Customer Support?

What does itnotmean?

‘AI-first’ Support won’t work for us…

1. “We’ll do it later when AI is more advanced and reliable”
Like with most things in life, the sooner you startdoingthe faster you learn and the better you can make the experience for your customers.
Improvements in AI won’t fix most of the things that will cause poor AI agent performance, like gaps in your knowledge base or how your users will familiarise themselves with the AI agent.
There are lots of ways you can start passively using AI agents right nowto assist your human agents, while you get things up to the standards you would be comfortable with deploying en masse.
Don’t wait, just start, future you will thank you.

2. “AI makes things up”/”AI can’t be trusted”
While stories of AI ‘hallucinations’telling people to eat rocksorlawyers presenting made-up casesin court populate the headlines, the reality, especially for AI support agents is very different.
These stories come from general-purpose chatbots that are required to answer just about any question.
Your AI support agent will likely be trained on a very specific, finite set of information you provide to it, meaningit will only answer questions using that information, nothing else.
Most AI agents will have some form of guardrails to prevent them from ‘hallucinating’,referring to competitors’ productsor answering outside of their knowledge base (if they don’t you should probably look elsewhere…).
Incorrect responses generally result as a consequence of unclear documentation provided to the AI, the AI agent is in effect a ‘mirror’ being held up to your knowledge base, so if its answers are wrong there is a good chance a person reading them would also have misunderstood.

3. “Our customers won’t like it”/”Our customers will leave us”
A portion of people hate change, even when it benefits them.
They are also often the ‘loud minority’ of customers rather than the ‘silent majority’.
This shouldn’t prevent you from doing what is in the interest of your entire customer base.
People don’t hate AI agents (chatbots) they hatebadAI chatbots.
They are experiencing the hangover of 10-15 years of poorly executed, non-generative AI agents, so who can blame them?
But not utilizing AI isn’t the answer, like most things you have to introduce it to them carefully and build up trust in it over time.
The longer you wait, the longer it’ll take.

4. “We don’t have the time to set it up”
Gone are the days of painstakingly mapping out customer queries and converting them into chatflows.
Now to set up an AI agent it is oftenas easy adding a URL, connecting a knowledge base and a few minutes later, asking it a few questions.
It really can be that simple to get up and running.
Over time you can improve the set-up, refine the training knowledge, increase the deflection rate, but you’ll get 70-80% of the way there in less than a day.

5. “It doesn’t feel very personal”
People use products to solve their problems.
People don’t sign up for products or services to make friends with the people who run them.
Thisdoesn’tmean an AI agent should be impolite, or that the customer shouldn’t feel listened to and be empathised with.
But it does mean people will be happy with any agent who can answer their questions, fast, and allow them to get on with their day or job.
AI agents are now much better at sounding empathetic, and reacting to customers’ frustrations.
And the time saved will allow you to focus on other ways to add that ‘personal touch’ to their user experience.

6. “It’ll be expensive”
There are AI agent pricing models suited to most businesses nowadays:
• Pay per successful resolution or deflection
• Pay per question,pay per conversationor
• Pay per agent
to name just a few.
In almost every case, it will be cheaper than using a person to do the same task, with prices ranging from $0.05 to $1.99 per interaction depending on the AI agent you choose.
The upfront ‘cost’ of setup is also negligible (see 4).
Add to this that costs will likely continue to fall, and AI competence will continue to improve, making the return on investment today the worst you will likely ever experience.

What are the benefits of AI support agents?

1. Handle more queries, faster
One of the biggest benefits of AI support agents is their near-instant response times. They can theoretically respond to all your customers, simultaneously, in seconds.
Just think how many human agents you would need to do this, or even ensure a sub-minute response time to all queries.
It just wouldn’t be economical.
AI agents scale up and down with demand, meaning they are there only as and when you need them, whether you suddenly get a spike in traffic or it’s a quiet holiday.
Even if your AI agent is unable to answer every question, each question it does answer is one less your human agents have to.

2. 24/7 availability
Humans need sleep (whether you like it or not).
But customers for most software businesses can come from all over the world.
Why limit yourself to a single location because of slow support replies when you can use an AI agent that doesn’t sleep?

3. Reduced costs
However cheap people are, technology is and will almost always be cheaper.
Instead of driving down the costs of your people, if you assume a skilled human support agent can deal with 50-100 tickets per day, and, at their cheapest is c. $1,500/mo, then (assuming 21 working days/mo), their cost per ticket will be somewhere between $0.71 and $1.43.
But for this you need:
• High-quality, skilled agents
• Who are also very cheap
• Dealing with relatively simple tickets
• Are also available 21 working days/mo
• Don’t need time off
• Don’t need training days
• Don’t need to attend meetings
• …
Do you see where I am going with this?
Your best-case,cheapestsituation is somewhere around the $1 mark per ticket when using people.
This is the price of themost expensiveAI.
AI agents on the market today are pretty much all somewhere between2-10x cheaper per ticketthan this.

4. Consistent and accurate responses
People are great, we love people.
But people are not machines.
We are not built for consistency and memory.
We say things in different ways depending on how we feel and we forget things from time to time.
Instead of training people to be more “machine”-like with their responses by using shortcuts, quick replies and canned responses, why not cut the middle-person and just… use a machine (or an AI agent, in this case) to answer questions consistently and accurately?

5. Improved customer satisfaction and experience
You may raise your eyebrow at this one.
Rightfully so, in some circumstances, people don’t like dealing with ‘bots’ (largely because of bad previous experiences).
But if they are set up well and improved upon over time, they do improve customer experience.
Who doesn’t like getting fast, helpful answers to questions so you can get on with your day?
There may be a small (but loud) minority of users initially who speak out against your new “robotic” approach, but they are also probably the same users who complain when it takes you hours to respond to their basic questions that you have answered in your docs.
Focus on the largely silent majority, focus on the data and commit to improving each aspect of your AI agent’s performance.

6. Freeing up human agents for more complex issues
It’s going to be a long time before AI is capable of taking entire jobs away from people (if it ever will).
AI is better at assuming ‘tasks’ from people.
Let it take on the ‘simple’, repetitive tasks, queries and questions from users.
Leave people to deal with themore complex, bespoke, edge-case issuesthat require more consideration, empathy and things only a person can provide.
Your team will thank you for making their role far less monotonous.

Are they better or worse at anything in particular?

• You have detailed documentation that your AI agent can be trained on

• Your queries can often be answered using your documentation without needing to access a user’s account or other databases

• You have a very high volume of queries

• You have a ‘long tail’ of unique, account-specific or trouble-shooting type questions that take a person multiple steps to resolve

• Your users expect a high-touch, personal service as part of your offering e.g. a concierge service

• You have very specific, defined and deterministic actions you need a user to perform each time they use the live chat or you need to collect specific data

Where is AI-first support headed?

• Easily andseamlessly integrate any data sourceto give our AI agents complete knowledge of our business and users to answer their questions.

• Have our AI agents work alongside users to identify, debug and even fix their issues live on their screens, maybe even before they ask.

• Allow our AI agents to autonomously perform actions within our platforms to solve issues and perform account actions (refunds, upgrades and more).

• Instantaneously generate live documentation, perpetually, as you update your product screens.