Episodes

  • Shadow AI at Scale: An Executive Playbook to Discover, Assess, and Integrate Unsanctioned AI

    Shadow AI at Scale: An Executive Playbook to Discover, Assess, and Integrate Unsanctioned AI
    Jul 5 2026
    Many enterprises now face a proliferation of employee-led AI: external LLMs, purpose-built scripts, and small automations that operate outside formal governance. This episode gives C‑level leaders a practical, non-technical playbook to discover shadow AI, assess business impact and risk, and choose when to assimilate, standardize, or retire informal systems. I walk through discovery techniques, rapid risk stratification, incentives to surface useful tools, procurement and integration options, and lightweight governance patterns that preserve innovation while protecting data, compliance, and brand. The monologue balances leadership, operational realism, and governance—showing how to convert rogue productivity into governed capability without hampering speed. Listeners leave with concrete steps to map current shadow AI, prioritize actions by business value and risk, and establish policies and operating models that scale. This episode is aimed at leaders who must bridge strategy and execution to safely capture emergent value from grassroots AI adoption.

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    I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
    Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.
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    8 mins
  • AI Investment Portfolio: A C‑Level Playbook to Prioritize, Stage‑Gate, and Measure Value

    AI Investment Portfolio: A C‑Level Playbook to Prioritize, Stage‑Gate, and Measure Value
    Jul 4 2026
    Many organizations fund AI as a set of isolated projects rather than as a strategic investment portfolio. This episode gives C‑level leaders a step‑by‑step playbook to treat AI like a product portfolio: prioritize by expected economic value and strategic fit, apply stage‑gates and small‑bet financing, define risk budgets and governance, and build measurable success metrics that link model outcomes to business KPIs. Mirko frames the playbook through concrete frameworks—scoring rubrics, cost-of-delay calculus, stage exit criteria, and lightweight experiment accounting—so you can stop chasing vanity metrics and start funding outcomes. Listeners will get a reproducible process for triaging requests, allocating capital across discovery, scaling, and run phases, and aligning incentives between business owners, data teams, and finance. Practical examples and signal checks show what to stop, where to accelerate, and how to make portfolio decisions defensible to boards and investors.

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    I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
    Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.
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    9 mins
  • Productizing Enterprise AI: A C-Level Playbook for AI Product Management

    Productizing Enterprise AI: A C-Level Playbook for AI Product Management
    Jul 3 2026
    Many enterprises treat AI as experiments rather than products. This episode gives C-level leaders a pragmatic playbook for productizing AI—installing roles, metrics, roadmaps, and processes that convert models into repeatable, revenue-driving products. Mirko outlines how to set clear outcome-aligned KPIs, structure AI product roadmaps that link to business OKRs, define the AI product manager role and accountability model, and design launch and adoption strategies for internal and external AI offerings. The episode covers trade-offs between centralization and federated models, pricing and cost-allocation approaches, lifecycle governance from discovery to sunset, and how to measure ROI beyond accuracy: adoption, process automation, and customer impact. Packed with concrete checklists, decision gates, and real-world examples, leaders will leave with an actionable roadmap to move from pilots to production products that deliver measurable value.

    Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

    I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
    Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.
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    9 mins
  • Buying AI Wisely: An Executive Playbook for Procurement, Contracts, and Vendor Risk

    Buying AI Wisely: An Executive Playbook for Procurement, Contracts, and Vendor Risk
    Jul 2 2026
    Many executives treat AI vendors like technology purchases instead of strategic, operational partnerships—resulting in hidden costs, brittle integrations, unclear accountability, and regulatory blind spots. This episode offers a practical, vendor-agnostic playbook for C-level leaders and senior data executives on buying AI with rigor: how to define outcome-oriented SLAs, negotiate data and model audit rights, design phased pilots that validate business metrics, enforce security and compliance clauses, and plan exit and portability terms to avoid vendor lock-in. The monologue translates procurement theory into actionable negotiation levers, decision gates, and governance checkpoints that preserve business value while reducing technical and legal risk. Listeners will leave with a checklist they can apply immediately when evaluating proposals, running vendor pilots, and aligning procurement, legal, and data teams around measurable success criteria.

    Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

    I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
    Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.
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    8 mins
  • DecisionOps: An Executive Playbook to Turn Models into Repeatable Business Decisions

    DecisionOps: An Executive Playbook to Turn Models into Repeatable Business Decisions
    Jul 1 2026
    Many organizations build models but fail to convert predictions into repeatable, measurable decisions. This episode presents a pragmatic DecisionOps playbook for executives: how to design decision contracts, embed model outputs into business workflows, assign decision ownership, instrument outcomes for ROI, and create closed-loop feedback that improves both models and processes. Mirko walks listeners through concrete operational patterns, real trade-offs between automation and human oversight, governance guardrails that preserve agility, and metrics executives must track to tie AI to business value. The monologue balances strategy and execution—what to centralize, what to federate, how to de-risk early deployments, and how to scale decision-making without losing trust. Listeners will leave with a clear checklist to move from isolated models to production decisions that are auditable, measurable, and tightly aligned with executive priorities.

    Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

    I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
    Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.
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    8 mins
  • Human-in-the-Loop AI: An Executive Playbook to Scale Expert–AI Collaboration

    Human-in-the-Loop AI: An Executive Playbook to Scale Expert–AI Collaboration
    Jun 30 2026
    This episode equips C-level leaders and senior data practitioners with a practical playbook for operationalizing human-in-the-loop (HITL) AI across the enterprise. Mirko walks listeners through why deliberate HITL design is not a temporary patch but a strategic capability: it improves decision quality, accelerates model learning, and builds organizational trust while containing risk. The monologue covers organizational patterns for pairing humans and models, routing logic for when to automate vs. escalate, measurable KPIs that link human interventions to business outcomes, staffing and skill mixes for sustainable review loops, and governance guardrails to prevent bias and liability. Listeners get concrete frameworks for cost-benefit trade-offs, sample metrics to track ROI, and a step-by-step rollout plan that moves teams from pilot experiments to reliable, auditable decision systems.

    Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

    I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
    Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.
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    7 mins
  • Data Contracts and Federated Data Ownership: An Executive Playbook to Build Trust and Scale Decision-Ready Data

    Data Contracts and Federated Data Ownership: An Executive Playbook to Build Trust and Scale Decision-Ready Data
    Jun 29 2026
    Enterprises struggle not from lack of data but from friction: unclear ownership, brittle integrations, and recurring trust issues that stall AI initiatives. This episode is a strategic, executive-focused monologue that translates the mechanics of data contracts and federated ownership into boardroom actions. You’ll get a pragmatic playbook for defining minimally sufficient contracts, aligning incentives across product, engineering, and analytics, and balancing central guardrails with local autonomy. The episode unpacks concrete governance primitives, measurable SLAs (freshness, lineage, schema stability), interoperability patterns, and rollout strategies tied to business KPIs. Designed for C-level leaders and senior data practitioners, the conversation emphasizes practical trade-offs, organizational levers that unlock scale, and how to measure the ROI of reduced friction — turning data-sharing from ad hoc firefighting into a repeatable capability that accelerates trustworthy AI adoption.

    Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

    I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
    Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.
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    8 mins
  • Business-Driven Model Observability: Linking Model Signals to ROI

    Business-Driven Model Observability: Linking Model Signals to ROI
    Jun 28 2026
    Many organizations instrument models for accuracy and latency but fail to connect those signals to business impact. This episode gives C-level leaders and senior data practitioners a practical, repeatable framework to align model observability with business KPIs, decision processes, and governance. In a focused executive monologue Mirko explains how to (1) map model signals to commercial outcomes, (2) design tiered alerts and runbooks that reflect business risk, and (3) structure accountability and investment decisions around observable business impact. Listeners will get a three-part checklist to stop chasing noisy alerts, prioritize interventions that move revenue or reduce cost, and measure observability ROI. The episode emphasizes organizational change, lightweight governance, and pragmatic trade-offs between signal fidelity, cost, and speed—actionable advice a leader can apply in the next 12–24 months to protect and grow AI value.

    Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

    I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
    Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.
    Show More Show Less
    8 mins