It’s no secret the contact centre landscape is changing faster than ever. Many teams now have AI budgets and innovation initiatives to explore, yet often struggle to know where to focus. Analyst research suggests this confusion is widespread: Gartner reports that over 80% of customer service leaders are exploring or piloting AI initiatives, but far fewer have embedded them into core operational workflows.
The organisations seeing the most value are those embedding conversational insight into everyday decision-making - and for leaders in regulated environments, this shift is no longer optional. Gartner and Forrester both point to a clear trend: AI is moving from experimentation to infrastructure in customer operations, particularly in financial services, insurance and member-based organisations.
Based on what Daisee is seeing across these sectors, a few clear themes are emerging as we head into 2026:
Automated QA will become the default
Sampling a small percentage of calls is increasingly misaligned with regulatory and operational reality. Industry benchmarks show that most contact centres still review only 1–3% of interactions, leaving significant compliance, conduct and experience risk unmanaged.
Gartner notes that organisations adopting AI-driven quality management are shifting toward 100% interaction analysis, significantly improving audit confidence and consistency while reducing reliance on manual reviewers. Forrester further estimates that QA automation can reduce manual evaluation effort by 60–75%, allowing teams to redirect effort toward coaching and risk prevention rather than retroactive scoring.
“One of the biggest wins we’re hearing from customers is time. Daisee’s QA AI insights have removed the need for manual call reviews, giving teams the space to focus on improving performance instead of barely just keeping up with it,” says Daisee’s Customer Success Manager, Abby Webster.
As expectations around fairness, consistency and evidentiary audit trails continue to rise — particularly under frameworks like CPS 230 and RG 271 — full conversation coverage will become standard practice rather than a competitive differentiator.
AI-generated summaries will quietly become essential
AI-generated summaries are often positioned as a productivity “nice to have,” but the data suggests they are becoming operationally foundational. Gartner research shows that agent assist and summarisation tools reduce after-call work by 30–50%, directly improving handle time, accuracy of records and agent satisfaction.
“One customer who recently adopted Daisee’s AI-generated call summaries told us they’re already saving up to 15 minutes per call in after-call work. That time (and the call centre cost reductions!) adds up quickly enabling agents to rely on consistent, accurate call notes that highlight exactly what matters,” shared Daisee’s CS Manager Abby Webster.
In regulated environments, the value goes further. Consistent summaries improve downstream processes such as claims handling, case management and dispute resolution — reducing rework and improving defensibility. Rather than replacing human judgment, summaries create a shared, structured view of each interaction that improves continuity across teams.
In 2026, summaries won’t feel like AI features — they’ll simply be how work gets done.
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