Tech companies are under intense pressure. Renewals are harder to secure, customers expect instant solutions and AI-native competitors are moving fast.

Customer experience and customer success teams are tackling more complex interactions than ever – whilst being told to do more with less.

Yet, according to the latest CallMiner CX Landscape Report, a paradox is emerging: AI adoption is surging, but manual processes in CX are actually increasing.

AI adoption is rising – but readiness isn’t

Eighty-one percent of tech organisations have implemented AI in some form, up from 58% last year. Nearly all see it as critical for both CX and employee performance.

However, 70% admit they’re using AI without mature governance structures. Without strong frameworks to ensure data quality, accuracy and compliance, execution lags behind intent.

Manual CX analysis is still the norm

Surprisingly, manual CX data analysis has increased 17% year on year, while automated analysis has fallen. This slows down:

Real-time agent assistance
Predictive churn detection
Faster product issue identification

Despite having advanced tools, many teams still struggle with adoption, integration and aligning data across departments.

Survey-heavy feedback creates blind spots

Most tech companies still rely on solicited feedback, Net Promoter Scores, CSAT (customer satisfaction score) and structured surveys, often overlooking unsolicited data from calls, chats, reviews and social media – early warning signs that could prevent churn. Leaders see potential in pairing smarter, personalised surveys with these unsolicited signals.

How AI is helping today

Even with these challenges, AI is already delivering value. The top use cases include:

Enabling self-service support to resolve issues faster;
Improving agent training and coaching; and
Personalising customer outreach.

Encouragingly, nine in ten leaders say they can already measure ROI from AI.

Governance, risk and employee experience are key

Concerns persist over siloed data, compliance risks and whether AI can capture nuance in customer interactions. Governance structures often lack clear accountability and risk management.

Leaders also recognise that employee experience directly influences CX. Real-time guidance, training and AI-powered performance scoring can free managers from manual review and enable tailored coaching at scale.

The path forward

The most effective organisations are:

Automating CX insights with conversation intelligence;
Enhancing coaching via AI scoring and real-time tools;
Combining solicited and unsolicited feedback for a complete customer view; and
Sharing insights across all customer-facing teams.

AI can help tech companies work faster and smarter – but only with strong governance, robust data foundations and a commitment to empowering employees.

The leaders who close the gap between AI ambition and operational readiness will be the ones delivering faster, smarter, and more human customer experiences.

Learn more

Tech sector leads in AI investment, yet many still rely on manual analysis, solicited feedback, and disconnected systems. Learn more by downloading Tech Leads in AI Adoption, Lags in Turning CX Data into Action.