How to Benchmark Readiness Before You Scale GenAI

redk's CX strategist breaks down the gap between AI experimentation and real-world ROI – and what it actually takes to scale Gen AI in customer service

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Published: April 22, 2026

Francesca Roche

Francesca Roche

Technology Journalist, Francesca Roche, sits down with Hideki Hashimura, CRM and CX Strategist at redk.

With MIT research showing 95% of enterprise Gen AI pilots failing to deliver measurable ROI, this conversation cuts through the hype to unpack what’s really going wrong – and what genuine AI maturity looks like in customer service. If your organization has launched an AI chatbot and wondered why nothing has really changed, this one’s for you.

Most enterprise Gen AI pilots don’t fail because of bad technology; they fail because of everything surrounding it. Hideki Hashimura of redk shares a no-nonsense breakdown of where organizations go wrong and how to build AI-powered customer service that actually scales.

The isolation problem: Most AI deployments are siloed – a chatbot here, a translation tool there – with no contextual learning or connection to wider service processes, which kills ROI before it starts.

AI maturity is an org problem, not a tech problem: True readiness means aligning people, process, and technology together. Agents are evolving into service architects, and closing that skills gap is the most critical step leaders are currently missing.

False positives are everywhere: Deploying an AI bot that handles surface-level queries isn’t transformation. If customers still can’t change a flight or request a refund, the foundation underneath the bot simply isn’t built.

Pilot success must be tied to business KPIs: Define your north star metrics first – NPS, resolution rates, handling time – then build the pilot around impacting those specific numbers. Speed without strategic alignment is just expensive experimentation.

Find out more about redk’s AI-readiness workshops here.
For more Customer Experience tech news visit CX Today.

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