New Year’s Resolutions: Getting Your Contact Centre ‘AI Ready’ in 2026
Most contact centres spent 2025 talking about AI. Plenty of vendor demos. A handful of pilot programmes. Maybe a chatbot that handled three simple customer requests before handing off to an agent who had to start from scratch. The conversations were well intentioned, but the outcomes were mixed.
The problem was the order of operations. Many organisations made decisions about platforms before they had worked out what they were trying to improve, or whether their operation could even support it. Like buying an electric car before working out where to charge it.
2026 could be different, but only if contact centres stop treating AI as a headline and start treating it as pipework. The window for getting this right is narrowing. The teams that approach it as serious operational work will move ahead, while those still scheduling vendor demos in Q4 will be there in December, nodding politely at the same slides.
Readiness matters more than capability
There’s a pattern that plays out so reliably you could run a book on it.
A contact centre buys an AI tool, runs a limited pilot, sees patchy results, blames the technology and quietly shelves it. Six months later, they start again with a different vendor. Same tune, new verses.
Technology was rarely the issue. Everything beneath it was.
Knowledge bases that haven’t been updated in years. Processes that vary depending on which agent picks up the contact. CRMs full of conflicting notes because five people interpreted the same policy five different ways. Leadership measures “AI adoption” without defining what success looks like, which is like measuring how much paint you’ve bought without checking if the walls are straight.
Automating unreliable processes simply shows what’s wrong operationally. You get the same problems, just at scale and with a bigger spotlight.
Jason Roos, CEO of Cirrus, sees this across the industry.
“Most programmes start with a technology decision and discover the day-to-day constraints later,” he says. “By then, they’ve bought tools that don’t fit the work, trained people on platforms they don’t trust, and still can’t answer the question: what were we trying to improve?”
The contact centres that make progress in 2026 will be the ones that fix the foundations first. Skipping that step is exactly why most AI pilots fail to show a positive return.
Readiness isn’t glamorous
It’s the unshowy work of fixing knowledge, simplifying processes, agreeing outcomes, and making sure people understand what the tools are meant to do. AI doesn’t compensate for weak foundations. It amplifies whatever you feed it. That’s why the contact centres making progress are starting small, fixing the basics, and sequencing change carefully.
Five resolutions worth keeping
If 2026 is the year your contact centre moves from talking about AI to using it with confidence, here’s what needs to happen.
1. Audit your knowledge with clear eyes
How many versions of the truth exist in your operation right now? Who owns accuracy? Can an agent find the right answer in under ten seconds, or do they put the customer on hold while they check multiple systems and ask around?
If the answer is vague, your knowledge needs work. Fix findability and accuracy first. Otherwise you’re automating the wrong answers faster, which customers notice immediately and remember for a long time.
2. Start with one high-impact use case
Pick a single intent. High volume. Clear steps. Low regulatory risk. Prove the full path works, including exceptions and escalation. Measure containment, quality, and customer satisfaction.
If it works, expand. If it doesn’t, you’ve learned something cheaply and contained, rather than failing expensively across the whole operation.
Roos sees this pattern repeatedly.
“The fastest wins are often the least exciting,” he says. “Automatic summaries save 30 to 90 seconds per interaction immediately and improve documentation accuracy without needing perfect knowledge. That creates free capacity you can reinvest elsewhere.”
3. Measure outcomes, not activity
Adoption rates mean nothing. What matters is what changed.
Did handle time fall without quality suffering? Did first contact resolution improve? Did compliance strengthen? Did the experience improve in a way you can accurately measure?
Set clear KPIs. Assign ownership. Set timeframes. Vague ownership produces vague results.
4. Check five things before you scale
Knowledge quality, API maturity, process standardisation, policy compliance, and coaching capacity all need to be solid before scaling AI.
Weak spots simply become expensive problems later. Sequence the work so early wins fund harder structural changes, rather than burning budget and goodwill on initiatives that were never ready.
5. Train people on what the tools do, not what they promise
Agents need to understand what the tool does, why it’s there, and how it changes their work.
AI provides answers faster. It drafts responses. It fills forms. It flags exceptions. It documents interactions. Humans still coach, govern, handle nuance, and own outcomes.
Make that clear from day one, or adoption becomes the next problem you’re solving.
As Roos puts it, “AI should be about progress, not presentation.”
Progress or performance
The contact centres that make real progress in 2026 won’t be the ones with the biggest budgets or the flashiest pilots. They’ll be the ones that treated AI as operational discipline rather than performance.
They fixed the foundations. They measured what mattered. They scaled what worked.
The difference in 2026 will be simple. Some teams will still be talking about AI. Others will be quietly benefiting from it.
Cirrus is an AI-enabled cloud contact centre solution that enables organisations to deliver exceptional customer experiences. Built with scalability, security, and simplicity in mind, Cirrus offers omni-channel capabilities, workforce optimisation tools, and intelligent automation – all delivered through an intuitive interface. Cirrus works closely with channel partners to help businesses across the UK connect with customers in more meaningful and efficient ways.
