Is Your Data AI-Ready? The Semantic Layer and the Last Mile Problem

Getting Enterprise Agent Implementations Right: Completed Workflows, Not Just Smarter Models

Everyone is waiting for the next model to make their AI problems disappear. The teams getting real value already figured out the model was never the hard part. In this episode, the crew reacts to Nate B. Jones [https://www.youtube.com/@NateBJones] and his argument that the trillion dollar opportunity [https://youtu.be/jwtpMSRAPAQ?si=LcVx8JZr7PONmpyU] sits in completed workflows, not smarter chat. This is AI, Actually, the show that cuts through the hype and gets practical about putting AI to work. We dig into why the model alone will never get you there, what happens to SaaS in an agentic world, and how to spot the workflows actually worth automating. You'll learn: * Why completed workflows, not models, are where enterprise value actually lands * How to use evaluation and a clear definition of "what good looks like" as the starting point for any build * What forward deployed engineers really do, and why the business person beside them matters just as much * Why seat-based SaaS pricing is breaking and what replaces it * How to pick a first workflow to automate using repeatability, ROI, and human in the loop * What harnesses are and why they are becoming the next layer of value Learn more about AnswerRocket: https://answerrocket.com/ [https://answerrocket.com/]  Get Ethan Mollick’s book, “Co-Intelligence: Living and Working with AI” here: https://a.co/d/0jl6kAMd [https://a.co/d/0jl6kAMd]   Follow the Gang: * Shanti Greene, Head of Data Science and AI Innovation, AnswerRocket - https://www.linkedin.com/in/shantigreene/ [https://www.linkedin.com/in/shantigreene/]  * Mike Finley, Co-Founder, AnswerRocket & StellarIQ  - https://www.linkedin.com/in/mikefinley/ [https://www.linkedin.com/in/mikefinley/]  * Pete Reilly, Co-Founder, AnswerRocket & StellarIQ - https://www.linkedin.com/in/petereilly [https://www.linkedin.com/in/petereilly]  * Ada Gil, Director, AI Business Transformation - Practice Lead - https://www.linkedin.com/in/ada-gil-84837648/ [https://www.linkedin.com/in/ada-gil-84837648/]  Chapters: 00:00     Introduction to AI Business Transformation 03:54     The Model Alone Isn't Enough 08:21     AI Won't Be Implementing Itself 11:43     Rebuilding Workflows and Embracing Change 13:25     The Future of SaaS and AI Integration 18:24     Navigating the Expenses of SaaS Platforms 23:14     The Evolution of Standards in AI 25:34     Understanding Workflows for Automation 28:34     Defining Success in Automation 32:35     The Value of Forward Deployed Engineers 34:47     Identifying Valuable Workflows 38:41     Economic Considerations in Automation 40:30     Concluding Thoughts & Harnessing AI 43:56     Evaluating Agent Performance 45:55     Combining Domain Expertise with Technology #EnterpriseAI #AgenticAI #AIStrategy #AIAgents #CompletedWorkflows #ForwardDeployedEngineers #AIImplementation

Is Your Data AI-Ready? The Semantic Layer and the Last Mile Problem

Most enterprise AI projects don't fail because of the model. They fail because of data, specifically, the gap between having data and having data an AI can actually understand and act on. This is the last mile problem, and it's quietly killing AI ROI across the enterprise. That's the real story behind the stat: 87% of AI projects never reach production. This is Episode 20 of AI, Actually, the podcast that cuts through the hype to help business leaders get real value from AI. Jim Johnson is joined by Andy Sweet, Nicole Kosky, and Ben Titmus, who leads the data and infrastructure practice at AnswerRocket, to break down what it actually takes to make enterprise AI work at the data layer. You'll learn: * What "data readiness" actually means for AI, and why it's different from what your BI dashboards needed * How to define and build a semantic layer iteratively, without a massive multi-year initiative * Why throwing everything at an LLM produces confident-sounding wrong answers, and how guardrails prevent it * How Microsoft Fabric, Snowflake, Databricks, and BigQuery are each approaching semantic layer infrastructure * Why model-swappability, not model loyalty, is the right architecture posture right now * What Chief Data Officers should do in the next 90 days to lead AI transformation from the front This episode is designed for: Chief Data Officers, VP Analytics, data engineering leaders, and any executive responsible for making AI work inside a real business. Learn more about AnswerRocket's enterprise AI solutions: https://answerrocket.com/ [https://answerrocket.com/]  Speakers: * Andy Sweet, VP Enterprise AI Solutions, AnswerRocket - https://www.linkedin.com/in/andrewdsweet/ [https://www.linkedin.com/in/andrewdsweet/]  * Jim Johnson, President, AnswerRocket - https://www.linkedin.com/in/jameswjohnson/https://www.linkedin.com/in/jim-johnson-bb82451/ [https://www.linkedin.com/in/jim-johnson-bb82451/] * Nicole Kosky, Senior Director of Services, AnswerRocket - https://www.linkedin.com/in/petereilly/https://www.linkedin.com/in/nicole-kosky-5b9a3b6/ [https://www.linkedin.com/in/nicole-kosky-5b9a3b6/] * Ben Titmus, Senior Director, Practice Leader - AI Data, Platforms and Infrastructure - https://www.linkedin.com/in/benjamin-titmus-a2817626/ [https://www.linkedin.com/in/benjamin-titmus-a2817626/]  Chapters: 00:00     Introduction and Milestones 01:40     The Data Dilemma in AI 02:59     Understanding Data Readiness 05:50     Defining the Semantic Layer 08:46     The Importance of Context in AI 13:08     Navigating AI's Limitations 16:44     Building Guardrails for AI 21:12     Achieving ROI in AI Projects 26:45     Recommendations for Chief Data Officers #EnterpriseAI #AIStrategy #DataReadiness #SemanticLayer #AIActually #ChiefDataOfficer #AIAgents

The Forward Deployed Engineer: What the Role Really Means (And What We Should Actually Call It)

Popularized by Palantir, the term "Forward Deployed Engineer" is everywhere right now.But what does it actually mean, and is it even the right label? In Episode 19, the AI, Actually crew digs into one of the hottest buzzwords in enterprise tech, separating the signal from the noise and getting real about the skills, structures, and organizational shifts that matter. This is a candid conversation about how AI is collapsing traditional role boundaries, and why the ability to understand a business problem may now be more valuable than the ability to write code. The crew also tackles why large enterprises are structurally misaligned with how this work actually gets done, and what education, apprenticeship, and org change need to look like going forward. Topics covered: * What "Forward Deployed Engineer" really means, and why "Forward Deployed Consultant" might be more accurate * Why senior engineers are thriving and junior roles are evolving, not disappearing * How AI is inverting the old software architecture model: solve fast, clean up later * Organizational bottlenecks: why most companies are still structured around the wrong constraints * The SAP paradox and why business process knowledge is now worth its weight in gold * What universities and apprenticeship models need to look like for the AI era Speakers: * Nicole Kosky, Senior Director of Services, AnswerRocket - https://www.linkedin.com/in/petereilly/https://www.linkedin.com/in/nicole-kosky-5b9a3b6/ [https://www.linkedin.com/in/nicole-kosky-5b9a3b6/] * Stew Chisam, Operating Partner, StellarIQ - https://www.linkedin.com/in/stewart-chisam-7242543/ [https://www.linkedin.com/in/stewart-chisam-7242543/]  * Jim Johnson, Managing Partner, AnswerRocket - https://www.linkedin.com/in/jameswjohnson/https://www.linkedin.com/in/jim-johnson-bb82451/ [https://www.linkedin.com/in/jim-johnson-bb82451/] * Shanti Greene, Head of Data Science and AI Innovation, AnswerRocket - https://www.linkedin.com/in/shantigreene/ [https://www.linkedin.com/in/shantigreene/] Chapters:  00:00     Introduction 01:43     Understanding the Role of Forward Deployed Engineers 04:16     The Evolution of Software Engineering Roles 07:22     The Business Analyst vs. Forward Deployed Engineer 10:47     Organizational Challenges in Adapting to New Roles 12:10     The Importance of Clarity in Problem Solving 17:43     Navigating Change Management in Organizations 20:44     The Role of AI in Redefining Business Processes 28:42     The Future of Software Engineering and Business Skills 32:25     The Need for Educational Reform in AI Skills 37:58     Conclusion: Embracing the Renaissance Person in Tech #ForwardDeployedEngineer #EnterpriseAI #AIRoles #BusinessAnalyst #TechnicalConsultant #AIOrgChange #AIWorkforce #AgenticDevelopment #EnterpriseSoftware #AIAdoption

How to 10x Your Individual Productivity with AI

Most companies are announcing AI strategies and running pilots that go nowhere. Meanwhile, individuals using AI every day are quietly getting 10x leverage on their work, and the gap is widening. The real story isn't about tools or models. It's about people, habits, resistance, and what it actually takes to build a culture where AI creates compounding value. In this episode of AI, Actually, host Pete Reilly is joined by Mike Finley, Nicole Kosky, and new AnswerRocket team member Michelle Hamilton, Director of AI Adoption and Change Management, for a candid conversation on how to move past fear, shadow AI, unused licenses, and the "is this going to replace me?" question that's quietly stalling enterprise adoption everywhere. You'll learn: * Why a people-first approach to AI matters more than which model you pick * How to use "meta prompting" to get dramatically better outputs across any model * What a personal AI "corpus" is and why it becomes your most valuable competitive asset * Why the most successful AI adopters are building tools, not just using tools * How to think about the crawl/walk/run framework for individuals and organizations * What forward deployed engineers are and why everyone can be one now This episode is designed for: Business leaders, team managers, and anyone who knows they should be using AI more but isn't sure where to start. AnswerRocket: https://answerrocket.com/ [https://answerrocket.com/] Speakers: * Nicole Kosky, Senior Director of Services, AnswerRocket | https://www.linkedin.com/in/petereilly/https://www.linkedin.com/in/nicole-kosky-5b9a3b6/ [https://www.linkedin.com/in/nicole-kosky-5b9a3b6/] * Mike Finley, CTO, AnswerRocket  - https://www.linkedin.com/in/mikefinley/ [https://www.linkedin.com/in/mikefinley/]  * Pete Reilly, COO, AnswerRocket - https://www.linkedin.com/in/petereilly [https://www.linkedin.com/in/petereilly]  * Michelle Hamilton, Director, AI Adoption and Change Management - https://www.linkedin.com/in/michellehamiltonai/ [https://www.linkedin.com/in/michellehamiltonai/]  Chapters:  00:00 Navigating the AI Landscape 01:25     Embracing a People-First Approach to AI 05:45     Tools and Techniques for AI Adoption 08:36     Meta Prompting and Leveraging AI Models 11:38     The Challenge of Change in AI Integration 14:33     Collaboration and Knowledge Sharing in AI 17:06     Empowering Non-Technical Users with AI 20:18     The Future of AI and Human Collaboration 27:58     Using AI for Office Tasks 33:18     The Role of AI in Education 36:42     Evolving Workflows with AI 45:35     Getting Started with AI #AIAdoption #EnterpriseAI #AIActually #ChangeManagement #GenerativeAI #AIStrategy #FutureOfWork

AI Consulting Isn't Dead, The Hourly Rate Is & And Why POCs Aren't Enough

Every week, someone declares that AI will make consultants obsolete. What we actually see is AI breathing new life into consulting, with practically every model maker teaming up with consulting firms for delivery support. The real story isn't about whether consulting is dead. It's about whether the consulting model your company is paying for is built for this era or the last one. In this episode of AI, Actually, Jim Johnson hosts Evan Gatch, Nicole Kosky, and Andy Sweet for a candid conversation on what enterprise AI consulting actually looks like right now: what's working, what's failing, and what clients should be demanding from their partners. You'll learn: * Why IT-led AI initiatives consistently underperform and what the Fortune 500 failures have in common * How the consulting business model is shifting from hourly rates to outcome-based and gain-share agreements * Why prototypes are easier to build than ever and why that makes the POC-to-production gap more dangerous, not less * What "enterprise grade" actually means when it comes to agentic AI solutions * How to structure a use case prioritization framework before you start building * Why organizational change management is the constraint that technology alone can't solve This episode is designed for: CDOs, VP-level analytics and data science leaders, AI transformation leads, and enterprise consulting buyers navigating AI strategy decisions. Learn more about AnswerRocket's enterprise AI solutions: https://answerrocket.com/ [https://answerrocket.com/] Speakers * Andy Sweet, VP Enterprise AI Solutions, AnswerRocket - https://www.linkedin.com/in/andrewdsweet/ [https://www.linkedin.com/in/andrewdsweet/]  * Jim Johnson, President, AnswerRocket | https://www.linkedin.com/in/jameswjohnson/https://www.linkedin.com/in/jim-johnson-bb82451/ [https://www.linkedin.com/in/jim-johnson-bb82451/] * Nicole Kosky, Senior Director of Services, AnswerRocket | https://www.linkedin.com/in/petereilly/https://www.linkedin.com/in/nicole-kosky-5b9a3b6/ [https://www.linkedin.com/in/nicole-kosky-5b9a3b6/] * Evan Gatch, VP Consulting Sales, AnswerRocket - https://www.linkedin.com/in/evan-gatch-1531482/ [https://www.linkedin.com/in/evan-gatch-1531482/]  Chapters 00:00 Introduction and Meet the Experts 02:10 Consulting in the Rapidly Evolving AI Landscape 04:14 The Changing Nature of Consulting Services 07:18 Aligning AI Solutions with Business Goals 14:02 The Role of Software Engineering Skills in AI 17:17 Organizational Change and AI Adoption Challenges 21:42 Enterprise-Grade AI Solutions and Production Readiness 29:28 Structured Approaches to AI Opportunities 32:45 Outcome-Based Pricing and Trust in Consulting 38:29 Closing Remarks and Future Outlook #AIConsulting #EnterpriseAI #AIStrategy #OutcomeBased #AgenticAI #AITransformation #AIActually