# Independent, not assisted

## The words we use

Almost every company in customer support now describes its people in the same terms: agents are "AI-assisted", the model is "human-in-the-loop", and humans are "empowered" by the technology. I have used all of these phrases myself, and I understand why they are popular.

![](https://cdn.hashnode.com/uploads/covers/67c1b1c6313ccbb4a8ec7d06/2ff9b5c2-e842-4fd2-9164-80cbc930a1cd.png align="center")

They are comfortable precisely because they are vague. They suggest that the AI does the heavy lifting while the human checks its work, without ever saying how much of the work each side actually does, or what happens to the people involved as that balance shifts.

In this piece I want to set that vocabulary aside, because what AI is actually replacing is the scripted, repetitive part of support work, the part few people ever wanted to do. At Onepilot, our AI platform and a network of more than 2,000 freelancers each handle part of our clients' customer support, and I don't think the freelancers are assisting anything. **They are independent professionals doing a different job from the machine**, and that job will keep changing as automation grows, which is worth saying openly.

## What the AI actually does today

Among the brands that use our AI-native product alongside our freelance network, the AI now **takes part in about half of customer conversations**. On the five best-performing of these accounts, it resolves close to 70% of conversations entirely on its own, with no human involved.

The curve is fairly predictable. Every new brand starts with immature workflows and a lot of human handling, and as playbooks stabilise and integrations deepen, the automated share climbs account after account. The accounts that have been live the longest give a good idea of where the others are heading.

Customers seem to notice the difference: conversations resolved fully by the AI **receive a 96% CSAT**. That number needs context: the AI is given the requests where its playbook is mature, not every request that comes in. The fair claim is not that it beats people in general, but that on the work it is given, it holds up, and is anyway often better than a disengaged agent reading a script, because it is fast, consistent and just as patient at 3am as at noon.

Over time, I expect simple, repetitive requests to be handled almost entirely by AI. That shift is already under way, and it is changing what the human side of the work looks like.

It is not happening at the same pace everywhere, though. Mid-market brands tend to move quickly, while larger enterprises are still held back by security, governance and procurement concerns around AI, a gap I wrote about in [Why AI-native CX is widening the gap between mid-market and enterprise](https://robinmonnier.com/ai-native-cx-mid-market-enterprise-gap).

## Who the 2,000+ are

The freelancers who work with Onepilot are far from a temporary workforce. Among those active in the last quarter, **almost half have been working with us for more than a year and nearly a quarter for more than two**, which matters in an industry where call centre attrition tends to be measured in months.

![](https://cdn.hashnode.com/uploads/covers/67c1b1c6313ccbb4a8ec7d06/85a860d1-5e25-45fc-8903-86caca9113fd.png align="center")

Most of them are based in France, with others across the UK, Germany and the rest of Europe, as well as in the United States and beyond. They are registered as independent businesses, invoice us monthly and choose their own shifts in two-hour blocks opened two weeks ahead. They are paid per resolved ticket, with a quality bonus on top, rather than per hour of presence.

Getting in is selective: more than 140,000 people have applied over the years, and each goes through role plays, attention-to-detail tests and a recorded video before anyone speaks to them. Once they join, they are trained on each brand they work with using our Academy product. Training is automated and self-service, so the knowledge they need for each client stays accessible whenever they need it, and they can work across several clients. Over the last 90 days, they resolved around three million tickets for more than 200 brands and escalated roughly one in a thousand.

## A different job, not an assisted one

I think the most accurate way to describe the split is not "AI plus humans" but **two different jobs**, even when they share the same queues. Today, freelancers still handle a large share of everyday requests alongside the AI. What changes is the direction: account by account, the AI takes on more of the informational and transactional requests support teams usually call levels 1 and 2, and the work left to people shifts with it.

![](https://cdn.hashnode.com/uploads/covers/67c1b1c6313ccbb4a8ec7d06/f460b998-427b-4ff5-862d-c1b34b2264a8.png align="center")

As that happens, more of their time goes to the complaint that is really about something else, the customer who has already been let down twice, or the case that sits between two policies and needs someone to make a decision. It includes VIP requests, legal risks and the edge cases no playbook anticipated. The way freelancers resolve these cases also ends up improving the playbooks the AI runs on, though that is a by-product of their work rather than its purpose.

It is becoming a level 3 job, one that needs judgment, context and the confidence to make a call, and it should be evaluated on outcomes rather than handling time. Calling that person "assisted" doesn't really describe what they do. They are independent professionals taking care of the part of the work that machines are not built for, and the part we most need to get right.

Put simply, the split is moving towards what each side does best: the AI taking on more of the routine work, where speed and consistency matter most, and people spending more of their time where judgment matters more than any script. Their work becomes more skilled, not less important.

## What this means for the people doing the work

As automation keeps climbing, **we will need fewer humans per ticket than we do today**. That follows directly from the numbers, and I don't think anyone running a support operation can honestly claim otherwise while automating at the same time.

What changes is how many people the work needs, not whether people matter. If fewer people are doing harder work, they should be well trained and free to choose when and how much they work. The freelance model makes the transition more transparent than a call centre can: nobody is sold a lifetime job, the terms are explicit from the start, and the work is chosen shift by shift.

The transition will not be easy for everyone in the industry, given how many support jobs around the world exist mostly to answer level 1 and 2 questions. Suggesting that AI will simply "augment" all of them may sound kinder, but in practice it only postpones a conversation the industry needs to have.

## Say what each side does

The industry doesn't need another slogan about humans and AI working together. What it needs are operators willing to describe what each side actually does, and to design their organisations around where that split is going.

For us, that means measuring and publishing how much the AI really resolves, treating the human role as a job in its own right with its own skills, pay logic and progression rather than as a fallback, and being clear with the people who work with us about where the work is heading before it gets there.

**The call centre job built on repetition is coming to an end.** What replaces it is still being shaped, and I believe the operators best placed to shape it are the ones willing to describe it as it really is.