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

Episode Overview

In this episode, Maribel Lopez sits down with David Singer, Global Vice President and Go-To-Market Strategy at Verint, to explore the rapid evolution from generative AI to agentic AI and how organizations can successfully implement AI solutions that deliver real business outcomes.

Key Topics Discussed

The Evolution from Generative to Agentic AI

• Generative AI: Excellent at answering questions and synthesizing information from knowledge sources
• Agentic AI: Takes the next step by actually executing actions autonomously, not just providing recommendations
• The critical difference: autonomous decision-making versus rules-based automation

Building Trust in Autonomous AI Systems

• Start with human-in-the-loop monitoring for training and validation
• Gradually reduce oversight from constant monitoring to spot checks
• Apply quality monitoring practices to AI agents similar to human agents
• Consider AI agents as "silicon-based employees" requiring training, access controls, and performance management

Successful AI Implementation Strategies

Start with Clear Outcomes: Define specific business goals before selecting technology

• Focus on solutions that deliver outcomes, not just impressive technology
• Begin with well-understood processes that can be enhanced rather than completely reimagined

Three Proven Starting Points:

1. Call Wrap-up Automation: AI-powered summarization reduces agent workload
2. IVR Modernization: Convert top call flows to agentic conversational AI
3. Quality Management: Scale from monitoring 1-3% of calls to near 100% coverage

Vendor Selection Criteria

• Proven outcomes at scale: Look for vendors with demonstrated success stories and customer references
• Technology adaptability: Choose providers who can evolve with the rapidly changing AI landscape
• Production readiness: "POCs are easy, production is hard" - prioritize vendors with production deployment experience

Change Management for AI Adoption

• Deploy solutions that genuinely help employees first
• Build internal champions through positive early experiences
• Scale gradually to maintain trust and adoption

Key Insights

• Employee Experience Drives Customer Experience: AI solutions that improve employee satisfaction often lead to better customer outcomes
• Observability is Critical: Comprehensive monitoring and quality management become essential as AI systems gain autonomy
• Outcomes Over Technology: Success comes from focusing on business results rather than being enamored with the latest AI capabilities

About the Guest

David Singer is the Global Vice President and Go-To-Market Strategy at Verint, where he focuses on delivering AI-powered outcomes for customer experience automation. Verint has been incorporating AI into their platform for over a decade, evolving from call recording and workforce management to comprehensive CX automation solutions.

You can follow David here: https://www.linkedin.com/in/dwsinger/

You can follow Maribel here:

Closing Thoughts

Singer emphasizes two crucial points for organizations embarking on AI initiatives:

1. Avoid spending significant resources on new technology only to use it exactly as you did before
2. Always start with outcomes first - let business goals drive vendor selection, implementation strategy, and change management approaches

In this episode from Cisco Live, Maribel Lopez sits down with two Cisco executives, Vijoy Pandey, SVP of Outshift at Cisco and Nathan Jokel, SVP of Corporate Strategy and Alliances at Cisco, to discuss how AI is fundamentally changing enterprise infrastructure over the next year. The conversation explores the evolution from deterministic to probabilistic computing, the emergence of agentic workflows, and practical advice for business leaders navigating the AI transformation.

Host: Maribel Lopez
Guests:

• Vijoy Pandey, SVP of Outshift at Cisco
• Nathan Jokel, SVP of Corporate Strategy and Alliances at Cisco

Recorded at: Cisco Live

Episode Overview

In this episode from Cisco Live, Maribel Lopez sits down with two Cisco executives to discuss how AI is fundamentally changing enterprise infrastructure over the next year. The conversation explores the evolution from deterministic to probabilistic computing, the emergence of agentic workflows, and practical advice for business leaders navigating the AI transformation.

Key Topics Discussed

The Three Waves of AI Infrastructure Evolution

• Wave 1: AI training in public cloud (mostly behind us)
• Wave 2: AI inference moving to enterprise data centers for control, security, and economic reasons
• Wave 3: AI moving to the edge with physical and embodied AI requiring new infrastructure for robots and devices

From Deterministic to Probabilistic Computing

Vijoy explains the fundamental shift happening in computing:

• Traditional computing: deterministic, machine-speed but limited
• Human intelligence: agentic but slow
• New paradigm: AI agents with human-like behavior operating at machine speed and scale

The Internet of Agents

A collaboration platform where AI agents from different vendors can:

• Get discovered and authenticated
• Compose workflows together
• Execute tasks collaboratively
• Be evaluated for performance

Real-world example: Building a sales funnel portal using agentic interfaces from Salesforce, ServiceNow, Microsoft, and Cisco security - all working together without manual UI clicking.

AI and Energy Challenges

• The Problem: By 2028, projected 63 gigawatt shortfall for new data center capacity
• Solutions:
  • Invest in diverse energy sources (nuclear, renewables, battery storage)
  • Build data centers near power sources (e.g., Cisco's Middle East partnerships)
  • Develop more energy-efficient infrastructure
  • Focus on smaller, specialized models instead of racing for maximum parameters

Cisco's Specialized AI Models

• Foundation SAC 8B: 8 billion parameter model specialized for security policy
• Deep Network Model: Expert model trained on network configurations

Outshift: Cisco's Innovation Engine

Cisco's internal incubator tackling problems adjacent to core business in:

• Space: Areas adjacent to networking, security, observability, collaboration
• Time/Risk: Higher-risk ventures that can't enter at Cisco scale initiallyCurrent Big Hairy Audacious Goals (BHAGs):

1. Internet of Agents
2. Quantum Internet - building quantum networks for distributed quantum computing

Description: In this episode from Google Cloud Next 2025, we dive deep into Best Buy's AI transformation with Ashley Daniels, VP of Product Management. Discover how one of America's largest retailers approached AI implementation strategically, moving from 93 contact center applications to a unified solution.

Ashley shares the real story behind Best Buy's AI journey - the quick wins, unexpected challenges, and why your foundation matters more than the technology itself. From gift finder tools to revolutionizing customer care, learn practical strategies for implementing AI that actually drives business outcomes.

Key insights covered:

• Why treating AI as a "tool in the toolbox" leads to better results
• The importance of starting with customer experience, not technology
• How to build strategic partnerships for AI implementation
• Why domain expertise becomes more critical in an AI world
• Real timeline: Getting AI summarization live in 6-8 weeks

Whether you're in retail, customer service, or leading digital transformation initiatives, this conversation offers actionable insights for your AI strategy.

Hosted by Maribel Lopez, founder and principal analyst at Lopez Research who interviewed Ashley Daniels, the VP of Product Management at Best Buy.

You can follow Ashley here https://www.linkedin.com/in/ashley-daniels1219/ and Maribel here https://www.linkedin.com/in/maribellopez/