The contact center stories enterprise IT leaders actually read.
Volume 343, Issue 1 · 7 articles from 4 issues
Contact centers must balance cybersecurity threats with customer experience while protecting vulnerable populations.
Contact centers face escalating cybersecurity risks including soft fraud, agent manipulation, and credential compromise, yet often operate outside enterprise security defenses. AI-powered threats like deepfakes and synthetic identities complicate verification processes.
Effective defense requires integrated approaches combining real-time conversational analytics, behavioral biometrics, and agent-assist tools alongside strong hiring practices and supportive work cultures.
Global regulations increasingly demand transparency and rapid breach disclosure. Organizations must prioritize end-to-end security verification while maintaining trust and empathetic customer interactions.
Contact centers need formal AI governance frameworks to manage automated systems that act at scale without human oversight.
Andrew Froehlich of West Gate Networks argues contact center leaders need formal AI governance frameworks to manage risks from automated systems operating at scale without human oversight.
The recommended framework addresses data usage, model behavior monitoring, customer disclosure requirements, and clear handoff procedures to human agents.
Implementation requires establishing decision rights, categorizing AI systems by risk level, and maintaining comprehensive audit trails.
Following structured governance pillars and repeatable implementation steps, from proposal through production operations, lets CX leaders scale AI capabilities while protecting customer trust and regulatory compliance.
Contact Center Pipeline's October issue marks Customer Service Week with features on AI, VOC, metrics and data.
Contact Center Pipeline previews its October 2026 magazine issue, which opens by celebrating Customer Service Week and urging leaders to recognize staff all year, and features a profile of how Home Telecom transformed its business through CX.
Other articles cover setting rules for going the extra mile, implementing AI so it does not become the next IVR, building a voice-of-the-customer process, why deflection metrics fail when the audience is not human, and replacing legacy CRM.
Further pieces address conversation intelligence, contact center AI's inherited data crisis and treating conversations as strategic assets.
Contact Center Pipeline recaps its most-read September posts, from 9/11's legacy to deepfake voice threats.
Contact Center Pipeline's blog rounds up its five most-read posts of September 2026.
They include an advisory board reflection on how the 9/11 attacks changed the contact center industry on the 25th anniversary, and a guide to integrating contact center AI and managing its risks.
Other picks cover defending against deepfake voice attacks and identity spoofing with emotion AI and behavioral detection, the widening U.S.-Canada compliance gap around customer email, and why platform integrity matters for both customers and frontline agents.
eWeek ranks seven AI call center platforms, naming RingCX best overall.
eWeek's Liz Ticong evaluates popular AI call center software on features, pricing and integrations, noting that AI and ML help automate routine tasks, enable 24/7 support, personalize interactions and improve agent efficiency.
RingCX is named best overall, HubSpot best for sales and marketing teams, Freshcaller for omnichannel support, Nextiva for large contact centers, Dialpad for remote teams, Talkdesk for service automation and CloudTalk for call monitoring.
Starting prices range from about $18 to $100 per user per month, and the guide explains how to choose a platform.
theCUBE's contact center summit found customer service shifting from speed and deflection metrics toward agentic AI that resolves issues.
SiliconANGLE recaps theCUBE's coverage of The AI ROI in Contact Center Summit, where success metrics are moving from call speed and deflection toward actually resolving customer issues.
Bob Laliberte of theCUBE Research called contact centers an ideal proving ground for agentic AI because of their large interaction volumes, labor costs and highly visible failures.
Joined by ZK Research's Zeus Kerravala and experts from Talkdesk, Cisco and Five9, the discussion covered blending humans and AI agents and orchestrating interactions between customers, agents and employees rather than automating isolated tasks.
Regulated contact centers lag in AI adoption (58% vs 92% in tech) as security, compliance and privacy checkpoints gate deployment.
This Contact Center Pipeline blog argues that despite the hype around autonomous AI agents, support operations must first clear security, compliance and data privacy checkpoints.
Its State of AI in Support Operations report finds 92% of technology companies use some AI in support versus only 58% in regulated industries, a gap reflecting requirements that public cloud-only AI offerings cannot meet.
AI-specific threats such as prompt injection, OWASP's top LLM risk, are among three primary barriers to contact center AI maturity.
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