2026: Brands Will Make or Break Customer Experiences with AI
2026 is a defining phase for UK contact centres. Advanced AI, higher customer expectations and shifting skills are converging. The CCMA has outlined 10 predictions that will set the pace this year. Here's what matters and how support leaders can act fast.
1) The contact centre becomes a strategic asset
Contact centres are moving further away from "cost centre" thinking. Exec teams will lean on you for customer insight, demand reduction and revenue resilience.
- Show the board the money: tie demand drivers to cost, churn and retention.
- Feed product and policy teams with issue trends and impact sizes, weekly.
- Fund improvements via benefits cases linked to NPS/CSAT, AHT avoided and revenue saved.
2) First line of cyber defence
Social engineering, phishing and fraud attempts are rising. Frontline teams are the human firewall.
- Run quarterly red-team style simulations and refresher microlearning.
- Deploy real-time fraud cues in agent desktops; default to "verify or decline."
- Follow best practice such as the NCSC guidance on phishing.
3) New success measures challenge old KPIs
Traditional metrics (AHT, calls per hour) won't tell the whole story. Expect a shift to outcome metrics that link service to business value.
- Adopt measures such as first-contact resolution, preventable demand reduced and post-contact digital adoption.
- Track "agent value add" on complex cases, not speed alone.
- Publish a simple, shared scorecard across Ops, Product and Finance.
4) UK BPOs adapt to new global realities
As AI takes transactional work, organisations will lean on UK partners for nuanced cases and regulated interactions. Onshore quality will matter more than offshore volume.
- Reframe outsourcing deals around complexity tiers and outcome SLAs.
- Include knowledge management, agent-assist and QA automation in scope.
- Build flexible surge models for incidents and product launches.
5) New career paths open up
AI handles routine. People handle context, exceptions and emotion. Roles expand into AI facilitation, knowledge engineering and customer insight.
- Map skills by role: data literacy, prompt-quality, journey design, vulnerability handling.
- Create "AI buddy" champions on each team. Reward peer coaching.
- Offer clear pathways from frontline to QA, WFM, product, and ops analytics.
6) Multi-dimensional leaders grow their remit
Leaders are being asked to span operations, CX, digital and risk. The job is more cross-functional than ever.
- Run a monthly triad with Product and Tech to kill repeat demand at source.
- Own a customer-outcome OKR that all functions contribute to.
- Build a simple governance for AI changes: intake, risk review, pilot, scale.
7) Demonstrable support for vulnerable customers
Stating you care isn't enough. You'll need proof of better outcomes and fair treatment.
- Define clear vulnerability flags and disclosure flows across channels.
- Audit outcomes against standards such as the FCA guidance.
- Measure agent capability with targeted QA forms and scenario drills.
8) Proactive service goes mainstream
With better data and AI, more issues will be prevented before customers feel the pain. Proactive beats reactive.
- Stand up event-based triggers (late delivery, failed payment, outage risk) with clear playbooks.
- Use explainable notifications and easy self-serve next steps.
- Report prevented contacts and saved time, not just send volume.
9) Customers' own AI agents force strategy changes
Customers will bring their own bots to negotiate bills, compare deals and handle admin. Your systems must recognise and handle machine-to-machine interactions safely.
- Set policy for bot interactions, rate limits and verification.
- Expose fair, consistent offers and clear APIs to reduce gaming.
- Design flows for fast-track resolution when a bot has valid consent.
10) Brands will make or break experiences with AI
This year, haste will hurt. Rushed deployments will dent trust and create avoidable demand. Thoughtful rollouts will improve speed, accuracy and sentiment.
- Ship small: limited scope, clear guardrails, easy escape to a person.
- Label AI clearly. Log every handoff and failure. Learn weekly.
- Evaluate with human-in-the-loop QA, scenario coverage and red-team tests.
- Track impact on trust indicators, repeat contact and complaint rates.
What to do in the next 90 days
- Publish a 1-page AI policy: use cases, risk levels, approval steps, human fallback.
- Refresh KPI stack to include outcome and prevention metrics.
- Run a fraud and vulnerability drill across voice, chat and email.
- Stand up one proactive trigger that prevents a top-3 demand driver.
- Launch a skills sprint: AI-assisted workflows, data basics and empathy refreshers.
- Set a joint backlog with Product to remove two repeat failure points.
Why this matters
AI will amplify whatever you already are. Strong processes, clean knowledge and skilled people get stronger. Weak signals, rushed changes and unclear policies get exposed.
The CCMA's view is clear: technology helps, but people decide the experience. Invest in skills, measure what matters and move in small, safe increments. That's how you protect trust and deliver value.
Industry support that's available
The CCMA continues to support leaders with member groups, accreditation against the Contact Centre Standards Framework and the annual Benchmark to compare operations across 25+ KPIs. The CCMA Academy offers structured training, and industry awards showcase what "good" looks like so teams can learn from it.
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