Disambiguation

The AI Tax: Why Your Agents Cost More Than Your People and What That Means for Scale

In this episode of the Disambiguation podcast, host Michael Fauscette talks with Joshua Gould, CEO of The BigWord, about the hidden economics of enterprise AI deployment and why AI agents often cost more than the humans they are meant to augment. Joshua has spent over 20 years in language services, co-founded TBB Global, and now runs one of the world's largest language service providers operating in 80 countries across 250+ languages. The BigWord has been navigating AI disruption since the late 1990s, from machine learning-driven translation memory to neural machine translation to today's large language models. The conversation covers the real math behind AI agent deployment in call centers, why integration and infrastructure costs dwarf license fees, why the AI industry is negatively scaling at the macro level, the parallel between today's AI hype and the dot-com boom and bust, how regulated industries like courts and healthcare are deploying AI methodically versus recklessly, why governance by design matters when errors scale at machine speed, and why the companies built like cockroaches will outlast the hype cycle. Timestamps: 00:00 - Introduction 00:42 - Joshua's background: from selling beer to Wall Street language services 03:40 - The first AI disruption: machine learning and translation memory in the 1990s 05:23 - Integrations and automated workflows for banks 06:54 - Pivoting to government contracting after the Great Recession 08:25 - Building a defense contracting company from scratch to $20M 10:49 - The 2019 vision: multilingual communications platform 11:45 - Covid's devastating impact: losing 47% of revenue overnight 12:46 - Selling to Susquehanna private equity in 2021 13:06 - LLMs arrive: the realization that AI is not free 15:43 - The real math: why AI agents cost more than human agents 18:07 - Hidden costs: integrations, infrastructure, tuning, and orchestration 19:05 - AI can only do 70% of what a human does, 70% of the time 19:54 - Why AI costs will not come down as fast as people expect 21:10 - Data center rebuild cycles and the $1.4 trillion CapEx problem 22:21 - Why deploy AI if it is not cheaper? Stability, speed, and service quality 25:08 - The FOMO driving boards and the CEO firing wave 30:03 - The coming correction: dot-com parallels and who will survive 31:29 - Why enterprise SaaS is not going away 32:19 - Staging AI deployment to protect against confidence collapse 35:16 - Be a cockroach: companies built for survival versus hype 37:01 - Governance by design: when errors happen 30,000 times in three milliseconds 39:57 - Testing at scale and the danger of AI policing AI 44:11 - Lessons from three waves of AI: watch regulated industries 47:59 - Unintended consequences: data saturation and content noise 48:40 - Recommendation: Gold with Gold podcast (Larry Gould, Cornell University) Guest: Joshua Gould, CEO, The BigWord Host: Michael Fauscette, CEO & Chief Analyst, Arion Research Subscribe and turn on notifications so you never miss an episode.

Governance Is Functions: Why Your AI Won't Scale Without Discipline by Design

In this episode of the Disambiguation podcast, host Michael Fauscette sits down with Chris Morancie, Fractional CTO and Founder of Digital Operations Factory, for a deeply technical and practical conversation about why AI governance has to be engineered into your architecture, not bolted on after the fact. Chris brings a unique combination of computer information systems, an MBA in business strategy, and a master's in data science to the problem of getting AI into production safely. His core argument: if your governance cannot stop your model from doing something wrong in real time, then it is not governance, it is just documentation. The conversation covers his three-part scalability test (design for scale, make sure it doesn't break at scale, don't go broke at scale), the Goldilocks zone for model selection, why agents should be treated through a microservices security lens with least-privilege access and short-term tokens, the firewall pattern for policy enforcement, real-time semantic interceptors for customer-facing AI, operational sovereignty and vendor SLA inheritance, IP leakage through model training, and a practical trust-vs-reasoning quadrant for managing hybrid human-agent teams. Timestamps: 00:00 - Introduction 00:44 - Chris's background: Caribbean upbringing, CIS + MBA + Data Science 03:48 - The AI production framework: design for scale, don't break at scale, don't go broke at scale 07:17 - The Goldilocks zone: model selection and cost benchmarking 09:28 - Assertion testing vs. evaluation testing for model quality 10:25 - "If your governance can't stop your model in real time, it's just documentation" 13:26 - The firewall pattern: policy agents with least-privilege, short-term tokens 16:09 - AI governance as good old-fashioned software hygiene 17:49 - Real-time semantic interceptors for customer-facing agents 21:15 - Competing goals: why prompts alone cannot prevent policy violations 24:02 - Agent security: every ingress and egress point is a vector 27:55 - RAG poisoning and downstream injection attacks 29:00 - Operational sovereignty: SLA inheritance and vendor risk 34:56 - IP leakage: when your feedback trains a competitor's model 36:16 - Trust vs. reasoning: a quadrant for managing hybrid teams 41:37 - Advice by company size: economics for SMEs, security for enterprise 45:25 - Recommendation: DALI Research Labs (YouTube) Guest: Chris Morancie, Fractional CTO and Founder, Digital Operations Factory Host: Michael Fauscette, CEO & Chief Analyst, Arion Research Subscribe and turn on notifications so you never miss an episode.

AI Without Compromise: Why Data Sovereignty Is the Next Enterprise Battleground

In this episode of the Disambiguation podcast, host Michael Fauscette talks with Clayton Bryan, Head of Enterprise at Quill, about why data sovereignty is becoming the defining issue for enterprise AI adoption and why most companies are on the wrong side of the trend. Clayton spent a decade as an early-stage investor at 500 Global before joining Quill, where he leads enterprise strategy. Quill's architecture is built local-first: audio transcription never leaves your device, and enterprise clients can bring their own LLM stack so that all data stays under their control. Clayton explains why this matters for regulated industries from defense to healthcare to financial services, how CISOs are becoming advocates once they understand the architecture, and why bolt-on governance will always leave gaps. The conversation covers why ChatGPT has a "professional trust deficit," why the line between enterprise and personal AI is dissolving, how Quill's agent (Quilliam) automates post-meeting workflows like CRM updates and project management tickets, and why data sovereignty is on the same trajectory as HTTPS -- optional today for some, table stakes tomorrow for all. Timestamps: 00:00 - Introduction 00:44 - Clayton's journey from 500 Global investor to joining Quill 03:48 - "AI without compromise" -- what that actually means 04:22 - Local-first architecture: audio never leaves your device 06:45 - Air-gapped deployments and who needs them 08:17 - GDPR demand and the EU enterprise tour 09:28 - Convenience vs. compliance: the real tradeoff 10:38 - Bottom-up adoption: when CISOs investigate and become advocates 12:34 - Why bolt-on governance is broken 14:28 - Governance by design at machine speed 14:57 - Investor-founders who understand what enterprise buyers actually need 17:11 - ChatGPT's "professional trust deficit" 19:31 - The dissolving line between enterprise and personal AI 20:48 - Beyond transcription: automating post-meeting workflows with Quilliam 24:27 - AI and the future of work: new skills, new opportunities 27:18 - Vibe coding: prototypes vs. production 30:13 - The future: local-first as minimum standard, not premium option 31:57 - Data sovereignty is the next HTTPS 33:12 - Recommendation: Matthew Berman Guest: Clayton Bryan, Head of Enterprise, Quill Host: Michael Fauscette, CEO & Chief Analyst, Arion Research Subscribe and turn on notifications so you never miss an episode.

AI Is the Biggest Distraction in Sales: Why the Hard Work Is Still Human

In this episode of the Disambiguation podcast, host Michael Fauscette sits down with Dr. Deepak Bhootra, Founder of RISEUP Career Studio, for a candid conversation about why AI is creating an illusion of progress in sales while the real, hard work remains deeply human. With 30 years in sales, a doctoral degree studying job satisfaction and organizational commitment, and an ICF coaching certification, Deepak brings a unique lens to the collision between AI hype and sales reality. He explains why salespeople use AI for the easy stuff like drafting emails but avoid using it for the hard stuff like self-reflection and honest deal analysis. He unpacks the "seductive" nature of AI output that makes activity feel like progress, the rise of individual shadow IT stacks where top reps spend $300 a month on personal tools they refuse to share, and why automating a broken process just scales the brokenness faster. Deepak also introduces RISEUP Career Studio, his platform designed to help early-career professionals (ages 21-35) build the judgment, self-reflection, and career navigation skills that no college degree teaches and no AI can replace. Timestamps: 00:00 - Introduction 00:45 - Deepak's 30-year sales journey and why he founded RISEUP 04:08 - "AI is the biggest distraction" in sales 06:37 - Why salespeople will never admit AI made them better 07:58 - How sales leaders should reframe AI adoption 10:16 - The cold email nightmare: 12,000 to 62,000 emails, same revenue 12:05 - AI-written LinkedIn profiles are sending false signals 14:35 - Shadow IT goes personal: reps building their own AI stacks 18:35 - Why top reps refuse to share their prompts 20:23 - The ethics of presenting AI output as your own work 23:42 - 70% transformation failure and the vision-to-execution gap 26:31 - "Scaling stupidity": when AI automates broken processes 29:13 - The black box trust problem in sales AI 31:31 - Using generative AI to demystify predictive AI 36:01 - RISEUP Career Studio: structured guidance for early careers 44:56 - The future of sales will be more human, not less 48:20 - Generic sellers are the next geriatrics 50:07 - Recommendations: Suresh Vasu, Mark Finnick, Ethan Mollick Guest: Dr. Deepak Bhootra, Founder, RISEUP Career Studio Host: Michael Fauscette, CEO & Chief Analyst, Arion Research Subscribe and turn on notifications so you never miss an episode.

From Human in the Loop to Human in the Lead: The Road to Autonomic IT

Most enterprises think they are ready for autonomous IT. Most are not. And frankly, they should not pretend they are. In this episode, Michael Fauscette sits down with Brian Amaro, Vice President of Customer Value and Partner Strategy at ScienceLogic, to map the real journey from reactive, siloed IT operations to autonomic IT. Brian shares the maturity progression his team built from hundreds of Fortune 500 engagements, the 15% adoption rate story that exposes the biggest misconception about AI in IT ops, and why the first win is never self-healing. It is better judgment under pressure. TIMESTAMPS: 00:00 - Introduction 01:03 - Brian's Background and What ScienceLogic Does 02:51 - Why AI Can't Be Bolted On: ScienceLogic's Ground-Up Rebuild 04:55 - Autonomic IT: Where Are We Really on the Journey? 07:20 - Assisted Autonomy Is Real; Broad Autonomy Is Not a Day One Strategy 09:23 - Human in the Loop to Human in the Lead: The Trust Progression 10:05 - Trust Formation, Not Speed: Where Most AI Adoption Goes Wrong 10:53 - The 15% Adoption Rate Story: Why Engineers Resisted AI 12:19 - Human on the Loop: Supervising Outcomes, Not Approving Actions 12:41 - Human in the Lead: Defining Intent, Not Controlling Tasks 13:59 - Moving Past the Approval Trap: Policy-Based Control 16:19 - Skylar Advisor: From "What Fired" to "What Matters" 19:31 - Why Observability, AI, Automation and Compliance Must Be One Platform 22:05 - What Analyst Recognition Tells Us About Where the Market Is Heading 24:09 - AI Governance by Design: Guardrails, Auditability, and Transparency 27:13 - Real-World Customer Journey: From Reactive Ops to Governed Automation 30:17 - The First Win Is Not Self-Healing: It Is Better Judgment Under Pressure 31:00 - The Hybrid Workforce in IT Ops: Better Leverage, Not Fewer Engineers 33:56 - The 2-3 Year Outlook: AI as Operating Model, Not Feature Rollout 36:13 - Don't Wait for Perfect Data: Start Where the Pain Is High 37:15 - Brian's Recommendation: Ethan Mollick's Co-Intelligence 38:30 - Wrap-Up ABOUT THE GUEST: Brian Amaro is the Vice President of Customer Value and Partner Strategy at ScienceLogic, where he has spent years working across customer strategy, advisory, and operational transformation. A certified Project Management Professional (PMP) with 30 years of experience, Brian helped build ScienceLogic's maturity model drawn from over 300 Fortune 500 customer engagements. ABOUT DISAMBIGUATION: AI clarity for business leaders. New episodes every Wednesday. Host: Michael Fauscette, CEO & Chief Analyst at Arion Research Author of "Building the Digital Workforce" SUBSCRIBE & follow for weekly episodes on AI strategy, agentic AI, and enterprise technology. Website: https://www.disambiguationpod.com/ Arion Research: https://www.arionresearch.com/ LinkedIn: https://www.linkedin.com/in/mfauscette/