Welcome to "AI or Not," the podcast where we explore the intersection of digital transformation and real-world wisdom, hosted by the accomplished Pamela Isom. With over 25 years of experience guiding leaders in corporate, public, and private sectors, Pamela, the CEO and Founder of IsAdvice & Consulting LLC, is a veteran in successfully navigating the complex realms of artificial intelligence, innovation, cyber issues, governance, data management, and ethical decision-making.

Trust is not a buzzword in AI-driven finance; it’s the product. We sit down with Anusha Nerella, a senior fintech leader to unpack how explainability, compliance, and human-centered design turn models into systems people can rely on. From reason codes in trading recommendations to precision-focused fraud detection, you’ll hear how building for auditability and clarity unlocks adoption with regulators, clients, and frontline teams.

We start with career roots in large banks and regulated environments, then tackle real-world use cases: liquidity routing that justifies every decision, fraud models that reduce false alarms by adding behavioral context, and governance workflows that keep shipping honest. You’ll learn why dashboards aren’t enough, why lineage and documentation must be embedded in the pipeline, and how to make “accountability by design” a team habit. The conversation also does no pull punches on bias, outlining how a high-accuracy credit model still drifted toward unfair outcomes until the data pipeline was rebuilt with fairness checks, feature audits, and human review steps.

We also look at representation and leadership. Women are shaping core AI work, yet often lack access to high-stakes projects and senior roles. Sponsorship, clear role maps, and culture that rewards bias-aware engineering are not nice-to-haves; they’re risk controls. The guiding question runs through the entire episode: Can we build it? Should we build it? For whom? Purpose informs thresholds, monitoring, and the definition of “good enough” when real money, safety, and trust are on the line.

If you care about AI in fintech, fraud prevention, compliant deployment, and building systems that earn confidence, this conversation is your playbook. Subscribe, share with a colleague who owns model risk or data platforms, and leave a review to tell us how you design for trust.

Welcome to "AI or Not," the podcast where we explore the intersection of digital transformation and real-world wisdom, hosted by the accomplished Pamela Isom. With over 25 years of experience guiding leaders in corporate, public, and private sectors, Pamela, the CEO and Founder of IsAdvice & Consulting LLC, is a veteran in successfully navigating the complex realms of artificial intelligence, innovation, cyber issues, governance, data management, and ethical decision-making.

Think your team is “AI ready”? We take a clear-eyed look at why most organizations overestimate their capabilities and how to move from buzzwords to measurable maturity. With returning guest Evan Benjamin—AI governance practitioner and tireless “AI nuggets” educator—we unpack what readiness really means for enterprises, agencies, startups, and solo builders, and why context matters more than any one-size framework.

We connect proven disciplines like CMMI and ITIL to the AI era, showing how capability-based maturity, lightweight governance, and resilient practices can accelerate outcomes without drowning teams in bureaucracy. From POCs inside a single business unit to repeatable processes across the org, we share practical steps for building systems that are safe, auditable, and effective. We also dive into the messy realities of today’s tools: agentic AI browsers, prompt injection, tracking pixels, and data retention defaults that quietly expand your risk surface.

Privacy and security get the spotlight. We walk through how to read terms of service and privacy policies, manage consent, and control data sharing with ad networks and brokers. Then we layer on hardening steps: MFA and passkeys, VPNs, mobile EDR, disk encryption, safe travel habits on public Wi‑Fi, and decluttering apps that over-collect. You’ll hear why fairness testing is not the same as bias checks, why evaluations must happen at multiple lifecycle stages, and why it pays to red team not just models, but the evaluations and governance themselves.

We close with a call to action: co-create a practical AI maturity model aligned to sector and use case, and stand up a train‑the‑trainer effort so consultants, attorneys, and project leads can deliver consistent, effective education. If you’re ready to swap hype for real capability—and build AI that lasts—hit play, share this with your team, and leave a review with the one control you plan to implement this week.

Welcome to "AI or Not," the podcast where we explore the intersection of digital transformation and real-world wisdom, hosted by the accomplished Pamela Isom. With over 25 years of experience guiding leaders in corporate, public, and private sectors, Pamela, the CEO and Founder of IsAdvice & Consulting LLC, is a veteran in successfully navigating the complex realms of artificial intelligence, innovation, cyber issues, governance, data management, and ethical decision-making.

A dark cloud can teach us how to lead AI. We unpack the link between everyday intuition and model design—when probabilistic signals are “good enough,” when deterministic rules must take over, and how a hybrid approach powers safer, more useful agentic systems. Joshua Linard, a former senior geospatial and data leader at the Department of Energy, joins me to trace a path from environmental physics and national-scale modeling to practical enterprise AI, where community and governance make or break outcomes.

We dig into the real work of governance inside flat, federated organizations: building communities of interest that surface experiments, evolving into communities of practice that standardize methods, and guiding executive boards that set policy and unlock funding. You’ll hear why lean rituals—weekly accomplishments, risks, and issues—create more clarity with less burden, and how time-boxed best practices keep pace with fast-moving tech. We also explore enterprise risk beyond cyber, pulling in IP, compliance, operations, finance, and public trust to shape smarter priorities.

On the technical side, we break down agentic AI as a modular, hybrid architecture. Deterministic guardrails handle sensitive boundaries like PII and export controls, while probabilistic components accelerate discovery, summarization, and pattern detection. The key is domain-aware metadata and explicit error tolerances so models stay grounded. We compare precision needs across contexts—from programs counting pennies to portfolios rounding to the nearest half-million—and map process templates to tool selection so AI fits the job, not the other way around.

The leadership thread across it all is humility, curiosity, and courage: admitting none of us knows it all, asking hard questions about why processes exist, and starting small so we can learn quickly and iterate. If you’re navigating responsible AI, digital transformation, or the leap to agentic systems, this conversation offers a clear, field-tested playbook. If it resonates, subscribe, share with a colleague, and leave a review telling us the one guardrail you’ll implement next.