Agentic AI is emerging as the next evolution of artificial intelligence in customer experience (CX), moving beyond chatbots to systems that can take real action on behalf of customers. In this episode of AI with Maribel Lopez, Maribel Lopez speaks with Jarrod Johnson, Chief Customer Officer at TaskUs, about how enterprises are actually deploying AI in customer experience today. The conversation covers real-world CX use cases, where AI delivers measurable ROI, why data and process design remain the biggest bottlenecks, and how organizations should manage risk, governance, and human handoffs as agentic AI scales. This episode is designed for enterprise leaders evaluating AI strategies for customer experience transformation.

Bio: Jarrod Johnson, Chief Customer Officer, TaskUs
Jarrod Johnson is the Chief Customer Officer of TaskUs. He is responsible for TaskUs' go-to-market strategy and execution across all client-facing and market-facing functions. Jarrod leads the "Client Organization" at TaskUs, including client success, sales, product and service management, and TaskUs’ consulting function, which includes the Agentic AI Consulting Practice. Jarrod is responsible for all aspects of revenue management and growth for TaskUs. He brings over 20 years of experience in enterprise technology-enabled services and business management.

Show notes
00:00 – AI in Customer Experience (CX): What This Episode Covers

01:31 – What a Chief Customer Officer Does in AI-Driven Customer Experience

03:46 – Top Customer Experience (CX) Bottlenecks Blocking AI Adoption

05:56 – Chatbots vs. Agentic AI: What’s the Difference in Customer Experience?

09:31 – How to Start with Agentic AI in Customer Experience (Real ROI Use Cases)

12:46 – When AI Should Hand Off to Humans in Customer Experience

15:41 – AI in Customer Experience: Cost Reduction vs. Revenue Growth

18:21 – Voice AI in Customer Service: Why It Finally Works

22:01 – AI Guardrails, Safety, and Brand Risk in Customer Experience

26:31 – Measuring AI-Driven Customer Experience (CX Metrics That Matter)

29:46 – AI for Customer Experience: Market Fragmentation and Vendor Landscape

33:46 – Agentic AI Pitfalls to Avoid in Customer Experience Transformation

CES 2026 Quick Take: Physical AI, Ambient AI, and the Reality of Adoption

In this episode, Maribel Lopez, founder and principal analyst at Lopez Research, is joined by Julie Ask, founder of Ask Advisory, for a candid, unscripted conversation on what CES 2026 actually revealed about the state of AI.

Rather than focusing on flashy demos or speculative promises, Maribel and Julie examine where AI is delivering real value today—and where expectations are running ahead of reality.

Julie's bio

Julie is a prominent customer experience analyst, technology futurist, and digital product strategist who has advised hundreds of global brands on the impact emerging technologies (e.g., mobile, sensors, extended reality, networks, AI) can and will have on customer experiences. She actively works with enterprises and vendors to understand how technology and consumer trends will impact their business with a deep focus on customer engagement strategies.

For more than 25 years, her work has defined the evolution of consumer digital experiences and inspired brands to take action. Her combined background in engineering and business gives her a unique ability to help business leaders understand what is possible and leverage technology to drive business outcomes. She has appeared frequently on Bloomberg while her research has been cited by the Wall Street Journal, New York Times, Financial Times, and a breadth of marketing publications. She co-authored The Mobile Mind Shift book in 2014. She founded Julie Ask Advisory in 2024 to pursue her passion for helping business leaders understand the impact of AI on experiences.

Maribel Lopez reports live from AWS re:Invent 2025 in Las Vegas, unpacking why the AI experimentation phase is officially over. With statistics that say 95% of AI projects are failing and enterprise budgets tightening, 2026 demands production-quality AI—not more proof-of-concepts. This episode explores the critical shift from building agents to deploying them safely at scale.

Key Themes

The Reality Check (2025 Recap)

• MIT study reveals 95% AI project failure rate
• McKinsey and BCG document widespread implementation struggles
• Board-level AI initiatives now demand real ROI, not just innovation theater
• The POC gold rush is over—experimentation budgets are drying up

Agentic AI Grows Up The conversation has evolved from "can we build agents?" to "can we trust them in production?" Three critical roadblocks:

• Security & Orchestration: How agents interact without creating vulnerabilities
• Policy & Governance: Preventing rogue agents and establishing guardrails
• Observability: Real-time monitoring to ensure agents perform as intended

AWS re:Invent 2025 Highlights

Agent Core Improvements

• Enhanced policy frameworks defining agent boundaries and permissions
• Human-in-the-loop controls for high-stakes decisions
• Better cross-stack orchestration for multi-agent workflows

The Discoverability Problem

• AWS Marketplace now features natural language search
• Upload requirements documents instead of filling rigid forms
• AI-suggested prompts help non-technical users navigate complex decisions
• Smarter filtering for nuanced needs (performance vs. cost vs. compliance)

The Full-Stack Maturity

• Recognition that AI "takes a village"—no single vendor owns the entire stack
• Growing emphasis on open standards (A2A, MCP) for SaaS integration
• Tools designed for all skill levels, not just data scientists

Key Takeaway

Enterprise AI in 2026 isn't about doing more—it's about doing it right. The winners will be organizations that prioritize governance, observability, and practical deployment over flashy demos.

Host: Maribel Lopez
Recorded: AWS re:Invent, Las Vegas, December 2025
Follow-up: Stay tuned for next week's deep-dive episode with demos and vendor interviews

In this episode of AI with Maribel Lopez, Maribel sits down with Ian Bramson, Vice President of Global Industrial Cybersecurity at Black & Veatch, to explore the growing intersection between artificial intelligence and operational technology (OT) security.

From power grids and oil refineries to manufacturing plants, critical infrastructure systems are becoming increasingly connected—and therefore more vulnerable. Ian shares how Black & Veatch is helping industrial organizations rethink cybersecurity from the ground up, integrating protection early in the design and build process rather than bolting it on later.

Together, Maribel and Ian discuss the evolution of OT threats, the rise of AI in both defense and attack scenarios, and why cybersecurity must be seen as a core business function, not an afterthought.

🧩 Key Discussion Topics

1. The Evolution of Industrial Cybersecurity

• Ian’s unconventional career path—from Coca-Cola to futurist consulting with Alvin Toffler to leading cybersecurity initiatives.
• Why Black & Veatch launched its dedicated industrial cybersecurity practice and how it’s integrated across engineering, procurement, and construction (EPC).

2. IT vs. OT Cybersecurity: What’s the Difference?

• IT focuses on data protection; OT focuses on physical safety and uptime.
• The rising threat of cyber-physical attacks on power, water, and manufacturing systems.
• How the increasing connectivity of devices—from pumps to sensors to AI controllers—creates new risks.

3. Foundational Security: Basics Still Matter

• Start with asset inventory—knowing what you need to protect.
• Identify vulnerabilities and train your “human layer.”
• Build security in from day one instead of bolting it on later.

4. The Expanding Threat Landscape

• Why ransomware is still relevant but no longer the only concern.
• The growing risks of supply chain attacks, remote operations, and super dependencies (as seen in the CrowdStrike outage).
• How attackers are weaponizing AI to accelerate attacks—and how defenders can use AI for faster detection and response.

5. AI and OT: A Double-Edged Sword

• How AI is reshaping the attack surface for industrial systems.
• Why every company is already “in the AI game,” whether they realize it or not.
• The three layers of AI to consider: AI used in cybersecurity, AI inside your operations, and AI in the wild used by partners and adversaries.

6. The Biggest Misconceptions About OT Security

• The “myth of the air gap”—why physical isolation no longer guarantees safety.
• Common organizational blind spots: board confusion between IT and OT, fragmented responsibility, and lack of lifecycle thinking.
• The need for Cyber Asset Lifecycle Management (CALM) to ensure long-term resilience.

7. Building a Resilient Future

• Why early planning and a holistic approach are key to managing future risks.
• The importance of embedding security, governance, and ethics into every new AI or industrial project.

About This Episode
Daniel Ziv, Global VP of AI and Analytics at Verint, reveals why experienced executives are making their worst decisions in decades—and how AI analytics is rewriting the rules of business intelligence. Learn the two critical frameworks that separate AI winners from losers, and why the biggest risk isn't picking the wrong technology—it's doing nothing at all.
Guest Bio
Daniel Ziv leads AI and analytics product management and go-to-market strategy at Verint, where he helps global enterprises transform customer experience through data-driven decision-making. With two decades in the analytics space, Daniel has witnessed firsthand how AI is fundamentally changing what's possible in customer insights.
Key Timestamps
[00:00] - Why change is happening faster than ever before
[03:04] - The Macro vs. Micro Analytics Framework explained
[06:19] - Two flawed decision-making patterns destroying value
[09:20] - Real ROI: $80M saved, $10M found in 48 hours
[15:32] - Generative AI vs. Agentic AI: What's the difference?
[21:03] - The hybrid cloud advantage (why on-prem isn't dead)
[26:35] - Common misconceptions about Verint
[28:49] - Daniel's advice for making AI decisions today
[32:17] - Final thoughts: "Ride the dragon"
Key Takeaways
The Two Fatal Mistakes:

Gut-based decisions without data - Your experience is becoming less reliable as change accelerates
Analysis paralysis - Waiting weeks for insights while competitors move in hours

The Macro-Micro Framework:

Macro Analytics: Understand patterns across ALL interactions (the 30,000-foot view)
Micro Analytics: Apply insights to individual interactions in real-time
Companies that excel at both create significant competitive advantage

Real Results:

Large telecom: $80M saved + 11% sales increase
Typical deployment: $5-10M in insights found within 1-2 days
UK financial services: $5M additional revenue from loan process improvements
Energy supplier: $2M saved through increased agent capacity

Generative → Agentic Evolution:

Generative AI responds to prompts (you ask, it answers)
Agentic AI breaks down goals and executes multi-step workflows autonomously
Example: Genie Bot evolved from answering questions to analyzing, quantifying, and exporting results automatically

Action Items for Listeners

Audit your decision-making speed - Are you making gut calls or waiting too long for data?
Identify one quick-win AI deployment - What could you turn on this week without changing infrastructure?
Evaluate your analytics gaps - Do you have macro insights, micro operationalization, or both?
Test before scaling - Start with 300 users, validate, then scale to 30,000
Connect with Daniel - Reach out on LinkedIn to discuss your specific use case

Connect With Daniel Ziv
LinkedIn: https://www.linkedin.com/in/dziv1/
About the Host
Maribel Lopez brings decades of technology industry analysis experience, helping business leaders cut through hype to understand what actually works in AI, cloud, and digital transformation. https://www.linkedin.com/in/maribellopez/
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Tags: #AI #Analytics #CustomerExperience #GenAI #AgenticAI #BusinessIntelligence #CXAutomation #DataDriven #DigitalTransformation #Verint

Episode Overview

Host Maribel Lopez sits down with Kerrie Jordan, the newly appointed Chief Marketing Officer at Epicor, to discuss the evolution of ERP systems and the transformative power of cognitive ERP in manufacturing, distribution, and supply chain industries.

Guest Bio and social links

Kerrie Jordan - Chief Marketing Officer, Epicor

Kerrie Jordan, Chief Marketing Officer at Epicor, leads the global go-to-market efforts, bringing together her deep product innovation and strategic marketing experience to drive brand growth and customer engagement across the make, move, and sell industry communities.

https://www.linkedin.com/in/kerriejordan/

Key Topics Discussed

Cognitive ERP: From System of Record to System of Action

• Definition: Transforming ERP from passive data storage to intelligent, proactive decision-making systems
• Key capabilities:
  • Sensing signals in data noise
  • Serving up actionable insights when needed
  • Connecting organizations across supply chains
  • Creating intelligent business communities

Epicor Prism: Agentic AI Technology

• What it is: Conversational ERP experience launched last year
• Key features:
  • Natural language interaction (type or speak)
  • Information querying without knowing system screens/reports
  • Automated actions with human approval (semi-autonomous approach)
  • Multiple specialized agents (Knowledge Agent, RFP Agent, Business Communications Agent)

Real-World Success Stories

Measuring AI ROI

• Focus on specific business outcomes, not just AI implementation
• Apply fundamental business case principles
• "Nail it before you scale it" approach
• Baseline analysis and clear success metrics

Future Vision (Next 1-2 Years)

Data Platform Evolution

• Explosion of structured and unstructured data
• Critical need for data normalization and health
• Open, secure connections as "good cloud citizens"

AI Development Trajectory

• Current: Pre-trained models and agentic AI
• Future: Self-service pipelines for custom AI model creation
• Model-agnostic strategy with patented inference pipeline
• Community-based insights and collaboration

Quotable Moments

• "We are an organization that is really focused on our core industries... making, moving, selling the things that we use every day"
• "It's all about accelerated value... How can we get as close to zero as possible?"
• "This era that we're in [is] like the modem dial-up era of AI"
• "Nail it before you scale it

Overview

Maribel Lopez interviews Kathleen Peters, Experian's Chief Innovation Officer, about AI's evolution in fraud detection, the shift to generative and agentic AI, and balancing innovation with security in financial services.

Key Topics

AI Evolution at Experian

• 15-year AI journey: Using machine learning for fraud detection long before generative AI
• Democratization shift: Public LLMs like ChatGPT and Claude made AI accessible beyond data scientists
• Innovation labs: 15-year-old team of PhDs and researchers finding insights in vast datasets

Responsible AI Implementation

• Risk Council: Cross-functional team ensuring responsible AI adoption
• Security-first approach: Enterprise tools with guardrails protecting sensitive credit data
• Custom AI stack: Proprietary systems maintaining data privacy while leveraging AI

Agentic AI Applications

• EVA Experian Virtual Assistant (Consumer Assistant): Evolved from chatbot to personalized agent that can take actions like unlocking credit scores
• Business Assistant: Democratizes data science, enabling rapid model development through natural language
• Real-time capabilities: Shifted from batch to real-time fraud detection

AI-Powered Fraud Threats

• Fraudster empowerment: Bad actors adopting AI faster than security measures
• Deep fake risks: Sophisticated impersonation for identity theft and account takeover
• Agent authentication: Challenge distinguishing legitimate vs. fraudulent AI agents
• Industry urgency: Can't wait for regulation; must develop solutions proactively

Key Achievements

• Fast, safe adoption: Chose innovation over waiting, with proper security guardrails
• Product success: Launched consumer EVA and business AI assistants
• Industry leadership: Staying ahead of evolving fraud landscape

Advice for Organizations

1. Establish Risk Council: Cross-functional leadership team for AI governance
2. Define values first: Determine organizational risk tolerance before technical implementation
3. Support curiosity safely: Enable experimentation within secure boundaries
4. Don't wait: Move quickly but responsibly - the technology won't slow down

Key Quote

"If you set up the infrastructure right, then you can let them hack away. You can let people be very curious."

Participants: Maribel Lopez (Host), Kathleen (CIO, Experian)
Focus: #AI #FraudDetection #GenerativeAI #AgenticAI #FinancialServices #Security

Kathleen Peters Chief Innovation Officer NA Fraud, Innovation & Commercialization

Kathleen Peters leads innovation and strategy for Experian’s Fraud and Identity business in North America, continuously exploring new ways to solve market challenges in identity, risk, and fraud detection. She and her team define business strategies and investment priorities while incubating new products, analyzing industry trends and leveraging the latest technologies to bring ideas to life. Kathleen joined Experian in 2013 to lead business development and global product management for Experian’s newest fraud products. She later served as the Head of the North America Fraud & Identity business, until being named Chief Innovation Officer for Decision Analytics in 2020. Kathleen has twice been named a “Top 100 Influencer in Identity” by One World Identity (now Liminal), an exclusive list that annually recognizes influencers and leaders from across the globe, showcasing a who’s who of people to know in the identity space.For nearly two decades, she has lived in

Episode Summary

Kevin Dunbar joins Maribel Lopez to discuss how AI is revolutionizing commercial fleet management through Ford Pro Intelligence. With nearly two decades of experience at companies like Cisco and Palo Alto Networks, Kevin shares insights on how Ford's commercial division is processing over a billion data points daily to help fleet operators optimize operations, reduce costs, and improve safety.AI with Maribel Lopez: Transforming Fleet Management with Kevin Dunbar

Guest: Kevin Dunbar, General Manager of Ford Pro Intelligence
Host: Maribel Lopez, Founder of the Data for Betterment Foundation and Lopez Research

Key Topics Covered

Ford Pro Intelligence Platform

• Commercial division serving business and government customers
• Comprehensive ecosystem from vehicle upfitting to fleet management
• Data services, telematics software, and fleet controls
• Updated from last earnings to 757,000 and 24% yoy growth. (vs. 675,000+ subscribers with 20% growth rate.)

Data at Scale

• Processing over 1 billion connected vehicle data points daily
• Sensor data ranging from tire pressure and GPS to seatbelt activity and driver behavior
• Clean, structured data transformation into actionable insights

AI Applications in Action

• Digital vehicle walkarounds replacing 20-minute manual processes
• Predictive maintenance moving customers from reactive to proactive service
• E-switch assist tool using machine learning for electrification decisions
• Connected uptime system achieving 98% vehicle availability

Tangible Business Impact

• 10% reduction in insurance costs through safer driving coaching
• 20% improvement in driver safety metrics
• 25% reduction in speeding incidents
• 80% reduction in cost downtime
• 10-20% total cost of ownership reduction

Notable Quotes

"We want to make sure that their Ford vehicle works as hard for their business digitally as it does mechanically." - Kevin Dunbar

"It's not just about having data. It's about having clean, structured data." - Kevin Dunbar

For more episodes of "AI with Maribel Lopez," visit Lopez Research and follow our latest insights on AI transformation across industries.

About Ford Pro and Ford Pro Intelligence

Ford Pro is helping commercial customers transform and expand their businesses with vehicles and services tailored to their needs. Ford Pro Intelligence is Ford’s comprehensive solution for fleet digitalization and operational efficiency, combining connected vehicle data, telematics tools, and smart management software under one platform

Follow Kevin at https://www.linkedin.com/in/kevin-dunbar-78343558/

Follow Maribel at https://www.linkedin.com/in/maribellopez/

#FordProIntelligence #FordPro #FleetManagement #Fleets #DataSecurity