Outsourcing QA Doesn't Remove the Judgment Calls — It Just Moves Them
CX Today published an interview on August 28, 2026 with Ty Given, Founder and CEO of CX Collective, laying out the case for what she calls Quality as a Service — an outsourced alternative to buying and running a QA platform in-house. Given's pitch, aimed at support teams roughly five to 20 agents in size, is that most small teams can't staff a proper quality function, so CX Collective supplies monthly calibration sessions, human-led review of conversations, an agent dispute process, and coaching notes, then hands leaders the output rather than a login. The interview frames this against a wider market trend she describes: vendors racing to advertise AI review of 100 percent of customer interactions, which she argues still can't substitute for a human reading context and deciding what actually matters for coaching.
What is Quality as a Service, and how does it differ from a QA platform?
It's a managed service, not software — CX Collective's staff score and calibrate conversations for you instead of selling you tools to do it yourself.
That distinction matters more than the interview lets on. A platform is something you evaluate, configure, and can compare against a competitor's. A managed service is something you trust — the quality of your QA becomes a function of CX Collective's own staffing, training, and consistency, none of which is described in measurable terms here. Buyers considering this model are effectively outsourcing a management function, not licensing a capability.
Does AI reviewing 100 percent of interactions actually solve the coverage problem?
Not on its own — Given argues coverage without judgment just produces more data leaders still have to interpret and act on.
That's a fair point, but it's also an easy one for a services vendor to make, since it's precisely the argument for buying more human hours. Nobody in this interview says who defines "100 percent" review, what counts as a reviewed interaction, or how any vendor's AI accuracy on that claim has been tested. Readers who've followed this site's earlier scepticism toward vendor benchmarking — including the point that when every vendor sounds excellent, polish stops being evidence — should treat "100 percent coverage" the same way: a marketing figure until someone shows the methodology.
Who is this actually built for?
Growing teams of five to 20 agents that lack the budget, headcount, or time to run an internal QA function themselves.
That's a narrow, specific segment, and it's worth taking at face value: this isn't pitched as an enterprise contact-centre replacement for existing QA suites, it's aimed at teams currently doing no formal QA at all. For that buyer, any structured calibration and coaching loop is likely an improvement over nothing. For a team that already owns a QA or QM tool, the pitch is less about capability and more about who does the labour.
What should you ask your own QA vendor before signing?
Ask exactly what "reviewed" means, who scores disputes, and how coaching notes get from a call to an agent's next shift.
Given's own point about CSAT is useful here regardless of vendor: an agent can follow process correctly and still get a bad score because a customer disliked a policy. Any QA approach — AI, human, or outsourced — should be able to separate agent performance from company policy in its scoring, and leaders should ask to see that separation before buying.
Frequently asked questions
Is Quality as a Service the same as an AI QA tool?
No. It's a human-delivered service built around calibration sessions and manual review, positioned by CX Collective as an alternative to buying AI-only QA software.
What size team is this aimed at?
Given describes it as most valuable for teams of roughly five to 20 agents that lack the time or budget for a dedicated internal QA function.
Does this replace human coaching?
No — the model is explicitly built around human review and coaching notes; Given's argument is that AI-only review still needs a person to interpret nuance and act on it.
Source: Why AI-Only QA Still Leaves Support Leaders Doing the Heavy Lifting, CX Today, interview by Rhys Fisher with Ty Given, published August 28, 2026.
Support leaders are under pressure to improve customer experience, coach agents, manage technology, and keep operations moving. Yet quality assurance often becomes another task on an already overloaded list. In this CX Today interview, Rhys Fisher speaks with Ty Given, Founder and CEO at CX Collective, about why Quality as a Service could offer a…