The first Contact Centre Network session of 2026 opened with a deceptively simple question: if we were designing the contact centre for 2029 (or even 2030), what would we build differently, and what habits would we finally leave behind?
With Andrew Hall and Mike Gale on the panel, the conversation quickly moved past “AI hype” and into something more useful: how leaders can rethink the operating model of the contact centre across people, process and technology, without defaulting to like-for-like replacements or “shiny tool” distractions.
The habit to retire in 2026: autopilot thinking
Rather than naming one specific practice to ban, both speakers targeted a mindset that quietly drives most transformation failures: the tendency to keep doing what’s familiar, then justify it with phrases like “we’ve always done it this way” or “we just need a like-for-like platform swap.” Mike made the point that real progress doesn’t start with stopping a tool, it starts with stopping automatic assumptions and restarting from first principles.
A few phrases the panel suggested leaders should challenge more aggressively this year:
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“Like-for-like replacement”
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“We have to do it this way because the process says so”
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“AI will solve it” (without defining what “it” actually is)
The underlying message was clear: reimagination isn’t reinvention for the sake of it. It’s the discipline of asking better questions before building anything new.
Noise is the real constraint, not technology
Andrew leaned into a theme he returned to repeatedly: disbelief. Not because leaders are negative, but because the market is noisy. Some teams are being hit so hard by vendor messaging and AI claims that they’ve tuned out altogether. In that environment, thinking gets constrained. People become cautious, defensive, and overly incremental.
The panel linked that noise directly to a pattern many contact centres recognise: upstream failures flow downstream into the contact centre, where teams “cope” instead of fixing the root cause. Over time, organisations build workarounds on top of workarounds, and the contact centre becomes a sophisticated sticking plaster.
If contact centres are serious about “reimagining”, the first job is to create space to think clearly: reduce noise, challenge assumptions, and give teams permission to imagine different workflows without immediately shutting the idea down.
“People are our most important asset”… are they?
A timely comment surfaced in the live chat from Nathan Dring, calling out the gap between what organisations say and what they fund: many leaders claim people are the priority while investment still flows disproportionately into tech.
Andrew’s response was balanced and practical. He argued that the industry often labels functions like recruitment, training, WFM and QA as “support”, when in reality they are practices that determine whether CX succeeds at all. The problem isn’t technology investment; it’s investing in the wrong way, buying premium tools while under-supporting the roles that make performance sustainable, especially team leaders and middle management.
His point was that agentic capability can genuinely help here, but only if it’s deployed to strengthen the people system, for example by giving team leaders usable insights, improving coaching loops, and making onboarding and role play more consistent. The long-term win is reduced stress and lower cognitive overload, but the short-term win is better operational confidence.
What “agentic AI” meant in this conversation
Agentic AI can mean different things depending on who’s selling it, so Andrew grounded the definition in plain operational language. GenAI can answer questions, but it isn’t built for reliable enterprise decision-making. Agentic AI, as Andrew described it, is about reasoning and action, with guardrails.
He explained it in a way most contact centre leaders will recognise: you wouldn’t give a brand-new advisor full autonomy on day one. You’d train them, supervise them, check their outputs, and gradually increase their responsibility. Agentic AI should be treated the same way.
To keep it clear, the panel’s view of “agentic” included:
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Reasoning beyond simple Q&A
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Orchestration (multiple specialist “agents” checking and balancing decisions, such as compliance, ethics, customer outcome)
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Progressive autonomy (turning the dial up only when confidence is proven)
That last point mattered because it directly addressed a common fear: that agentic means “we switch it on and hope for the best.” The panel’s position was the opposite, this is about controlled progression, not a leap into chaos.
Mike’s framework: the 3 W’s as a reset tool
Mike shared a simple but effective framework he uses to help teams break out of autopilot: Why, What, Where. It’s intentionally basic because most transformation problems aren’t caused by lack of cleverness, they’re caused by skipping the thinking.
The value of the 3 W’s is that it forces organisations to stop answering their own questions too quickly. Leaders often ask “why” and then immediately rationalise it away. Mike’s approach is to exhaust the “why” until the real logic reveals itself.
Used well, the 3 W’s becomes a practical foundation for roadmap thinking:
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Why are we doing this at all, and why does it matter?
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What outcomes are we aiming for, beyond short-term metrics?
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Where are we today, where do we need to be, and where will we land if we change nothing?
Mike’s consultative CX framework is built around three deceptively simple questions:
🔎 Why?
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Why are we doing it this way?
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Why does it matter?
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Why does this problem exist upstream?
🎯 What?
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What outcome are we actually trying to achieve?
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What does success look like two or three years from now?
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What are we solving — the symptom or the root cause?
🌍 Where?
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Where are we today?
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Where do we want to be?
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Where will we be if we do nothing?
The power of the framework lies in exhausting the “why” before moving on — not rationalising it away with habitual answers.
“If you answer your own homework, you’re not achieving anything.”
It’s a surprisingly powerful way to expose whether a programme is genuinely strategic, or just a reaction to noise.
Andrew’s DREAM model: how to create permission to imagine
Andrew then introduced the framework he’s using with organisations through: DREAM, Discovery, Reimagine, Educate, Apply, Mobilise. It’s designed to do one main thing: remove constraints long enough for teams to picture a better operating model, then bring structure back in so the vision becomes executable.
D – Discovery
Understand how the organisation really feels about itself.
Where are we? Where do we aspire to be? What happens if we do nothing?
R – Reimagine
Remove constraints.
No technology excuses. No “we can’t because…” statements.
(Yes, there’s a metaphorical pound-in-the-jar rule for every constraint mentioned.)
E – Educate
Create understanding around what agentic AI, orchestration, and decision intelligence truly mean.
A – Apply
Translate ambition into right-to-left planning:
If that’s our future state, what constraints must we remove?
M – Mobilise
Turn vision into a phased roadmap — progressive, measurable, iterative.
Andrew’s key belief:
“AI isn’t the problem. Organisations are.”
In practice, DREAM starts with honest discovery (how the organisation feels today and where it wants to be), then moves into a constraint-free workshop where teams are encouraged to think without defaulting to “we can’t.” Only after that does the process flip into reality: identify the few constraints that genuinely matter, then build a plan left-to-right.
A memorable detail from Andrew was the “pound in the jar” idea: if someone mentions a constraint too early, they pay a pound. It’s a light-touch way to stop teams from shutting down creativity before it has a chance to form.
What’s really holding leaders back from doing this themselves?
When asked why these kinds of reimagining sessions aren’t happening naturally inside contact centres, Mike pointed to one word: fear. Fear of making the wrong call. Fear of being the person who backed the “risky” option. Fear of stepping outside accepted vendor patterns.
Andrew added a sharper perspective: some executive teams are underprepared for the scale of change. If senior leaders can’t clearly articulate the capabilities and limits of modern AI, they won’t be able to guide the organisation through the trade-offs. That gap creates hesitation, and hesitation turns into delay.
Both agreed this is why curiosity matters so much. The future belongs to teams who keep asking, “What if?”, and who are comfortable experimenting in controlled ways rather than waiting for perfect certainty.
Looking ahead to 2029: what changes first?
When the conversation jumped forward to 2029, Mike’s view was that organisations embracing these approaches will simply outpace their competitors. They’ll be designing for the customer experience they want to deliver, not just operating the contact centre they inherited. Andrew went further, suggesting that by that point it won’t even be “the contact centre” that looks different; it will be the enterprise model itself, with intelligence and automation woven across workflows rather than bolted on as tools.
The shared message was optimistic but blunt: those who start now will have compounding advantage. Those who wait may find the jump becomes too big.
Closing thought
This webinar wasn’t a debate about whether AI is coming. The panel treated that as settled. The real question was whether contact centre leaders will create space to think clearly, challenge inherited processes, and invest in the people system as much as the tech stack.
Reimagining the contact centre isn’t one big leap. It’s a series of better questions, tested decisions, and progressive automation, done with confidence rather than noise-driven panic.
