Épisodes

  • AI Investment Portfolio: A C-Level Playbook to Prioritize and Fund AI Initiatives

    AI Investment Portfolio: A C-Level Playbook to Prioritize and Fund AI Initiatives
    May 4 2026
    Executives face a steady stream of AI proposals but rarely a disciplined method to prioritize, fund, and scale the ones that produce measurable business value. This episode introduces a pragmatic AI investment portfolio framework for C-level leaders: define expected value and risk profiles, adopt stage-gated funding, balance short-term operational wins with strategic bets, and align capacity across data, engineering, and governance. I unpack concrete metrics—expected value, time-to-impact, cost-to-production—and a simple scoring model plus an executive review cadence that converts pilots into a diversified portfolio. Through concise, real-world examples I show common trade-offs (double down, pivot, or sunset), resource reallocation strategies, and how to avoid “pilot trap” churn. The monologue closes with governance templates, scoring pitfalls to avoid, and a repeatable 90-day playbook for prioritization and funding decisions that help leaders maximize ROI and institutionalize sustained AI 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 min
  • Building the AI Runway: Executive Capacity Planning to Sustain AI at Scale

    Building the AI Runway: Executive Capacity Planning to Sustain AI at Scale
    May 3 2026
    Many AI initiatives stall not because the models are weak but because organizations run out of runway: data availability, compute, talent, or governance capacity. This episode gives C-level leaders a concise, operational framework to build a multi-year AI runway that aligns strategy, budget, and operational reality. Mirko walks through how to quantify dataset velocity, forecast feature engineering throughput, size compute and storage for production workloads, plan hiring and skill shifts, and bake governance and compliance into capacity decisions. The approach focuses on decision-driven metrics, cross-functional slos, and sanity checks that separate optimistic experiments from fundable, repeatable programs. Listeners will get an executive checklist, three realistic forecasting templates, and example trade-offs—so you can present a defensible three-year AI capacity plan to your board or executive committee.

    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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    10 min
  • Data Contracts and SLO-Driven Data Products: An Executive Playbook to Treat Data as a Measurable Service

    Data Contracts and SLO-Driven Data Products: An Executive Playbook to Treat Data as a Measurable Service
    May 2 2026
    Many organizations struggle not for lack of models but for a lack of predictable, trustworthy data. This episode gives C-level leaders a practical playbook for treating data as a product governed by lightweight contracts, service-level objectives (SLOs), and measurable SLAs. Mirko walks listeners through translating business KPIs into enforceable data SLOs, defining producer-consumer contracts, and building the observability and governance needed to reduce downstream surprises. The monologue covers decision frameworks for strict versus flexible contracts, trade-offs between agility and reliability, incentive models to align teams, and a step-by-step roadmap to roll out SLO-driven data products. Expect concrete examples, a sample minimal contract template, and metrics that tie data reliability improvements to business ROI—onboarding time, incident reduction, and model trust. Designed for CEOs, CTOs, Chief Data Officers and senior data leaders, this episode focuses on executable leadership moves that close the loop from strategic outcomes to engineering delivery.

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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 min
  • From Pilot to Product: A C-Level Playbook for Packaging and Selling Enterprise AI

    From Pilot to Product: A C-Level Playbook for Packaging and Selling Enterprise AI
    May 1 2026
    Many AI initiatives stall at pilot or PoC because leaders treat models as technical artefacts instead of products. This episode gives C-level leaders a concrete playbook for productizing AI in enterprises: how to define the customer value proposition, choose commercialization models (embedded features, platform, API, managed service), price on value not cost, structure data and IP contracts, align sales and engineering motions, and guarantee operational SLAs post-sale. I draw on cross-industry examples and pragmatic trade-offs—when to productize vs. keep bespoke, how to measure product-market fit for algorithmic outputs, and the governance checkpoints required to maintain trust and compliance after launch. Listeners will walk away with a step-by-step checklist to move from successful pilots to scalable, monetizable AI products that deliver measurable business outcomes.

    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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    10 min
  • When Models Break: An Executive Playbook for AI Incident Response

    When Models Break: An Executive Playbook for AI Incident Response
    Apr 27 2026
    In this episode Mirko presents a concise, executive-focused playbook for responding when production AI systems fail, behave unpredictably, or cause downstream harm. Framed as a business continuity and governance problem rather than a pure engineering incident, the monologue walks through detection, rapid triage, escalation, containment, rollback, external communications, regulatory documentation, and post-incident learning. Listeners get clear decision points for C-suite leaders: how to prioritize incidents by business impact, structure cross-functional incident teams, allocate authority for containment versus investigation, and measure success through pragmatic KPIs. The episode emphasizes trade-offs—speed versus forensic fidelity, transparency versus legal exposure—and gives concrete governance levers to embed response playbooks into contracts, SLAs, and executive dashboards. Practical, repeatable steps help leaders turn reactive firefighting into institutional resilience that protects value, trust, and compliance.

    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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    10 min
  • Features as Products: An Executive Playbook for Strategic Feature Platforms

    Features as Products: An Executive Playbook for Strategic Feature Platforms
    Apr 26 2026
    Enterprises investing in machine learning often overlook a single leverage point that separates pilots from production: features. This episode reframes features as products—discoverable, versioned, governed, and measured assets that executives must manage as part of their data strategy. Mirko delivers a focused monologue that explains how leaders decide which features to productize, how to fund shared feature platforms, and how to link feature SLAs to business outcomes. Listeners will get a pragmatic playbook covering organizational ownership models, engineering patterns (feature stores, lineage, and serving), prioritization frameworks tied to ROI, and pragmatic governance that balances agility with control. The episode is designed for C-level leaders and senior data professionals who need concrete guidance to reduce duplicate work, improve model reliability, accelerate time-to-value, and turn feature stewardship into a strategic capability.

    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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    10 min
  • Human-in-the-Loop at Enterprise Scale: Building Decision Pipelines Executives Can Trust

    Human-in-the-Loop at Enterprise Scale: Building Decision Pipelines Executives Can Trust
    Apr 23 2026
    Many organizations treat AI as a drop-in automation rather than a decision partner. This episode gives C-level leaders a practical, strategic playbook for designing human-in-the-loop (HITL) pipelines that balance speed, accuracy, auditability, and risk. I walk through how to pick the right handoff points between models and people, structure escalation and review workflows, measure combined human+model performance, and align incentives and governance so HITL systems produce reliable business outcomes. You’ll hear concrete examples for finance, operations, and customer experience where HITL moved projects from brittle pilots to repeatable production value. The focus is on executive decision-making: investment trade-offs, organizational ownership, KPIs that matter, and how to operationalize responsibility and explainability. By the end, leaders will have a clear checklist to evaluate current initiatives, reduce failure modes, and scale human+AI decisioning with measurable ROI. Subscribe for more executive playbooks from DataScience.Show.

    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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    11 min
  • Shadow AI: An Executive Playbook to Discover, Manage, and Harness Unofficial AI Use

    Shadow AI: An Executive Playbook to Discover, Manage, and Harness Unofficial AI Use
    Apr 22 2026
    Many enterprises face a parallel AI economy: employees using external models, browser plugins, automation scripts, and SaaS features outside IT’s visibility. This episode gives C-level leaders a practical, strategic monologue on treating 'Shadow AI' as both a risk and an opportunity. You’ll get a repeatable framework to discover unsanctioned AI, assess business impact and compliance exposure, design lightweight governance that preserves velocity, and create safe channels to productize high-value grassroots solutions. The episode translates technical controls into board-level decision criteria—cost, liability, data exposure, and measurable ROI—and explains how to align incentives, create an internal marketplace for validated tools, and operationalize auditing and incident response. Realistic, executive-focused guidance walks leaders through fast wins and durable practices so Shadow AI becomes a managed source of innovation, not a hidden threat.

    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 min