エピソード

  • Ecosystem AI: An Executive Playbook for Shared Models, Data & Partnership Governance

    Ecosystem AI: An Executive Playbook for Shared Models, Data & Partnership Governance
    2026/03/02
    Strategic partnerships—joint ventures, channel integrations, data co-ops, and platform alliances—are where AI scale often happens, but they also create ambiguous ownership, data-usage friction, and misaligned incentives. In this 20-minute executive monologue Mirko opens with a concise vignette where an ungoverned marketplace integration created a revenue dispute and compliance exposure. He then delivers a non-technical playbook: classify partnership archetypes and executive stakes, draft minimal data-sharing and IP primitives executives can require, choose commercial models (revenue share, value-based pricing, credits), and assign operational responsibilities for monitoring, incident response, and exit. Listeners get board-ready KPIs (shared-value realization, data provenance completeness, partner incident MTTR), a prioritized 30–90 day pilot to structure one high-value partner integration, and negotiation language to bring to legal and procurement. Practical, decision-oriented guidance so leaders capture ecosystem scale while keeping accountability clear. Subscribe to DataScience.Show for more executive playbooks. That’s the difference between models and value.

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    12 分
  • Independent Assurance: An Executive Playbook to Commission, Fund, and Act on Third‑Party AI Audits

    Independent Assurance: An Executive Playbook to Commission, Fund, and Act on Third‑Party AI Audits
    2026/03/01
    Internal reviews are necessary but not sufficient: independent third‑party audits translate technical findings into credible, fundable actions for boards, auditors, and insurers. This 20‑minute decision-first monologue opens with a concise vignette where an internal check missed a vendor dependency that external auditors later flagged, producing weeks of costly remediation. Mirko then presents a non‑technical playbook: scoping audits (governance, data provenance, model behavior, security, procurement), choosing credible auditors and conflict‑of‑interest guards, defining minimum deliverables (reproducible tests, executive summary, severity bands), budgeting and procurement clauses to require audits, and converting results into prioritized remediation lanes, contract remedies, escrow triggers, and board‑ready scorecards. Listeners receive a prioritized 30–90 day pilot to commission an audit for one critical model, sample scope language for procurement, and actionable KPIs to demand from auditors. Practical, decision-focused steps so executives get independent assurance without drowning in implementation detail. Subscribe to DataScience.Show for more executive playbooks.

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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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    10 分
  • Insure the Unknown: An Executive Playbook for Transferring AI Risk with Insurance, Warranties & Bonds

    Insure the Unknown: An Executive Playbook for Transferring AI Risk with Insurance, Warranties & Bonds
    2026/02/28
    Many C-level leaders treat AI risk as internal control; few know how to transfer residual risk to insurance or structure warranties. This 20-minute executive monologue opens with a concise vignette where an algorithmic pricing error triggered a multimillion-dollar claim and insurer rejection. Mirko then presents a non-technical, decision-first playbook for AI Risk Transfer: inventory transferable exposures, convert SLOs into parametric triggers underwritten by insurers, design insurance-backed warranties and escrowed remediation funds, set measurable underwriting signals (loss-velocity, concentration, audit trails), choose between traditional liability, parametric policies, captive insurance, and performance bonds, and negotiate claims-ready contracts and premium models. Listeners get board-ready KPIs (insured-exposure ratio, claim-latency, premium-as-percent-of-TCO), a 30–90 day pilot to scope one insured product line, and negotiation language for procurement, legal, and treasury. Practical, fundable steps so executives can convert uninsured tail risk into priced, transferable instruments. Visit datascience.show/ai-insurance to download the AI Risk Transfer checklist. That’s the difference between models and value.

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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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    13 分
  • Model Freshness: An Executive Playbook for Recalibration, Seasonality, and Model Aging

    Model Freshness: An Executive Playbook for Recalibration, Seasonality, and Model Aging
    2026/02/23
    Models degrade for predictable reasons—seasonality, shifting customer behavior, pipeline changes, and calendar-driven promotions—but executives rarely fund sustained freshness practices until revenue drifts. In this 20‑minute monologue Mirko opens with a concise vignette where a forecasting model missed a seasonal peak and cost inventory millions, then lays out a non-technical, decision-first playbook: define board-ready freshness signals (performance decay curves, cohort slippage, feature drift rate), map business calendars and cadence dependencies (promotions, fiscal cycles, product launches) to recalibration policies, and create a financed 'retraining runway' with explicit budget buckets for routine recalibration, emergency retrains, and validation sampling. Listeners get a 30–90 day pilot to inventory top models, set trigger thresholds, run a controlled recalibration, and present a single-page funding request to finance. Practical governance language and procurement clauses are included so leaders convert model upkeep from an invisible technical cost into a funded strategic capability. Visit datascience.show/model-freshness to download the Freshness Checklist. That’s the difference between models and value.

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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 分
  • Model Marketplace: An Executive Playbook to Catalog, Certify, and Monetize Reusable Models

    Model Marketplace: An Executive Playbook to Catalog, Certify, and Monetize Reusable Models
    2026/02/20
    Enterprises waste time, money, and trust when every team rebuilds similar models or reuses uncertified artifacts. This 20‑minute executive monologue opens with a concise vignette where duplicated churn-detection models produced inconsistent customer outcomes and ballooning costs. Mirko then delivers a non-technical playbook for building an internal Model Marketplace: how to inventory candidate models, set certification gates (performance, lineage, data-provenance, SLOs), design internal pricing or showback, and create a lightweight catalog and governance board to approve reuse. The episode includes pragmatic artifacts executives can commission immediately—catalog taxonomy, certification checklist, contract snippets for internal SLAs, and a 30–90 day pilot to certify the top 10 reuse candidates. Listeners get board-ready KPIs (reuse rate, cost-saved-per-model, certification latency) and negotiation language to align product, platform, procurement, and legal. CTA: download the Model Marketplace Starter Kit at datascience.show/model-marketplace. That’s the difference between models and value.

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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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    10 分
  • The Label Economy: An Executive Playbook to Treat Labeling as a Strategic Asset

    The Label Economy: An Executive Playbook to Treat Labeling as a Strategic Asset
    2026/02/19
    High-quality labels are the unsung input that determines whether models deliver predictable business outcomes—or unpredictable risk. This 20‑minute executive monologue opens with a concise vignette where poor labeling inflated a fraud model’s false positives and cost the business millions in churn. Mirko then delivers a non-technical, decision-first playbook: how to treat labeling as a product (ownership, SLAs, unit economics), practical sourcing options (in-house teams, managed vendors, verified crowd, synthetic augmentation), measurable label-quality SLIs and sampling protocols executives can read, procurement clauses to guarantee provenance and remediation, and a simple budgeting rubric to convert label needs into funded line items. Listeners receive board-ready KPIs (label accuracy variance, labeling velocity, parity vs baseline, detection-to-fix latency), and a prioritized 30–90 day checklist to inventory high-impact labeling lanes, run a quality audit, and secure funding. Practical artifacts and negotiation language so leaders stop losing model value to invisible label debt. CTA: download the Label Economy Playbook at datascience.show/label-economy. That’s the difference between models and 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 分
  • Adoption Heatmaps: An Executive Playbook to Map Friction and Prioritize AI Rollouts

    Adoption Heatmaps: An Executive Playbook to Map Friction and Prioritize AI Rollouts
    2026/02/19
    Large technical proofs-of-concept fail not for lack of accuracy but because they collide with organizational friction: unclear decision owners, brittle data flows, regulatory constraints, and operational bottlenecks. This 20-minute executive monologue opens with a concise vignette where a successful pilot stalled because three business units couldn’t agree on ownership. Mirko then delivers a practical playbook: a compact Adoption Heatmap (visibility, data readiness, decision ownership, regulatory exposure, value potential), a simple scoring rubric to convert heat into priority tiers, and a lightweight discovery protocol that executives can run in 72 hours. Listeners get board-ready signals (friction concentration, go/no-go thresholds, expected time-to-value), a prioritized 30–90 day pilot to unblock the top lane, and negotiation language for procurement and legal. CTA: download the Adoption Heatmap Template at datascience.show/adoption-heatmap. That’s the difference between models and 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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    8 分
  • Human-in-the-Loop at Scale: An Executive Playbook to Fund, Staff, and Govern Human Oversight for High‑Stakes AI

    Human-in-the-Loop at Scale: An Executive Playbook to Fund, Staff, and Govern Human Oversight for High‑Stakes AI
    2026/02/14
    High-stakes AI still needs human judgment: content moderation, high-risk approvals, exception review, and safety triage all require reliable human oversight. Yet most organizations treat human review as ad hoc, underfunded, and invisible to risk reporting. This 20‑minute executive monologue gives leaders a compact, non-technical playbook to make HITL a measurable service: define service tiers and SLAs for reviewers, cost and staffing models (in-house, blended, vendor), error-budget accounting, fatigue and quality controls, training and certification, procurement clauses for reviewer obligations and confidentiality, and reporting metrics that belong on the executive dashboard. Mirko opens with a short vignette where missing reviewer SLAs caused a regulatory complaint and lost customers, then lays out a 30–90 day checklist executives can use to inventory high-impact HITL flows, budget remediation, and assign accountable owners. Practical, decision-focused guidance so oversight protects customers without collapsing velocity. CTA: download the Human‑in‑the‑Loop Playbook at datascience.show/hitl. That’s the difference between models and 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 分