Discover What Seperates AI Buzzwords From Business Impact
AI has become the dominant topic in contact centers, yet for many leaders it represents a significant budget challenge. While demonstrations appear compelling and pilot programs show initial promise, organizations frequently encounter obstacles when attempting to scale. Current data indicates that 70% of AI initiatives fail to progress beyond the pilot stage.
This pattern reflects not a shortage of capable technology, but rather a gap in governance structures. Organizations that achieve sustained success with AI distinguish themselves not through vendor selection, but through their insistence on measurable outcomes, vendor accountability protocols, and disciplined change management processes.
In this on-demand webinar, contact center experts Jim Iyoob and Manu Dwievedi examine how to implement frameworks that convert AI investments into quantifiable returns.
What You’ll Learn
This webinar addresses the operational and strategic challenges that determine AI implementation success:
- The Blog-Pilot Reality Check
Understand why demonstration environments overestimate performance, pilot programs create misleading benchmarks, and production deployment reveals the actual operational requirements. - The Three Scaling Challenges
Identify how architectural limitations, inadequate data governance, and organizational resistance create barriers to successful AI expansion. - The Iceberg Cost of AI
Examine the complete cost structure of AI implementations, including the often-underestimated expenses of integration, training, and change management that typically represent 80% of total investment. - The ROI Framework That Works
Establish measurement methodologies that extend beyond automation metrics to encompass efficiency gains, compliance improvements, customer experience enhancement, and revenue impact. - Vendor Accountability 2.0
Apply a structured 25-point evaluation system that transforms vendor relationships from transactional arrangements into outcome-based partnerships. - Scale-Right Roadmap
Implement a phased approach to AI expansion that manages risk and cost while building organizational capability.
Meet the Speakers
Jim Iyoob
President, ETS Labs | Chief Customer Officer, Etech Global Services
Jim Iyoob directs AI implementation strategies focused on delivering quantifiable returns in operational contact center environments. As President of ETS Labs and Chief Customer Officer at Etech Global Services, he connects AI innovation with proven operational frameworks.
His 35-year tenure in contact center operations established a core observation: AI implementations typically fail when developed in isolated laboratory settings rather than operational environments. ETS Labs addresses this gap through QEval, an AI-powered quality management platform that provides 100% interaction coverage, real-time coaching capabilities, and deployment timelines measured in days rather than months.
At Etech, Jim oversees global sales and quality assurance operations, directing the company’s transition from traditional BPO services to data-driven operational models. His approach analyzes insights from over one billion customer interactions to identify competitive advantages for client organizations. His operational principle: implementations must demonstrate tangible improvements in customer experience and operational efficiency to merit deployment.
Jim has co-authored five books addressing customer experience and AI applications, presents at industry conferences, and contributes insights to trade publications.
Manu Dwievedi
AVP, Product Strategy & Innovation, ETSLabs
Manu Dwievedi directs product strategy at ETSLabs, developing AI platforms designed to address operational contact center requirements. He oversees QEval’s conversational analytics architecture and ICE’s agentic AI orchestration platform—systems that process billions of interactions annually while maintaining enterprise implementation timelines under 30 days.
With more than ten years of experience in enterprise AI deployment, Manu concentrates on developing solutions that address the operational adoption challenges that often limit AI capability utilization. At ETSLabs, he leads development of platforms engineered to resolve data fragmentation and integration obstacles that frequently compromise enterprise AI initiatives.
His methodology emphasizes practical deployment protocols and measurable outcomes, partnering with Fortune 500 organizations to deliver AI implementations that produce quantifiable returns while establishing operational confidence.
Don’t Miss out
FAQs
This webinar explains why 70% of AI initiatives fail beyond the pilot stage and introduces a proven governance framework to turn AI investments into measurable profit within 90 days. Learn the three scaling stoppers, the hidden 80% of AI costs, vendor accountability strategies, and the Scale-Right Methodology.
- Contact Center Leaders and Operations Directors managing AI investments
- CX Executives and VPs of Customer Experience seeking measurable ROI
- CIOs and CTOs evaluating AI vendors and platforms
- Quality Assurance Leaders scaling QA operations with AI
- BPO Executives balancing innovation and profitability
- Procurement and Vendor Management teams negotiating AI contracts
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A comprehensive framework to hold AI vendors accountable for measurable outcomes — including performance metrics, implementation accountability, and data-protection standards. All viewers receive a downloadable PDF version.
For questions or additional details, please email CX@etechgs.com..