Episodes

  • Decision Contracts: Turning Predictions into Accountable Business Actions

    Decision Contracts: Turning Predictions into Accountable Business Actions
    Feb 8 2026
    Models that emit scores rarely include the binding rules leaders need: who acts, when, at what threshold, and who pays for mistakes. In this 20‑minute executive monologue Mirko introduces ‘Decision Contracts’—compact, board‑readable agreements that translate predictions into executable, funded business decisions. The episode defines the contract’s essential fields (decision trigger and action matrix, costs of false positives/negatives, human‑in‑loop gates, rollback and fallback plans, monitoring SLIs, feedback cadence, funding and escalation clauses), illustrates two anonymized vignettes where absent decision rules caused revenue or compliance harm, and gives a repeatable rubric to draft and pilot Decision Contracts in 30–90 days. Listeners get board‑friendly KPIs, a prioritized checklist to brief legal/procurement/business owners, and a link to download the Decision Contract template to place into procurement and governance cycles. Practical, non‑technical, and immediately actionable for executives who must make predictions produce measurable value. CTA: download the Decision Contract template at datascience.show/decision-contracts. 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.
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    10 mins
  • Incentives That Stick: Designing Executive and Team Incentives to Deliver Measurable AI Outcomes

    Incentives That Stick: Designing Executive and Team Incentives to Deliver Measurable AI Outcomes
    Feb 7 2026
    Too many AI programs fail not for lack of models but because incentives push the wrong behavior: teams optimize vanity metrics, vendors chase one‑time uplift, and business owners avoid ownership of outcomes. In this 20‑minute executive monologue Mirko lays out a compact, pragmatic playbook for designing incentives and performance systems that tie funding, career signals, and product KPIs to measurable business outcomes. The episode explains three incentive levers (funding cadence, metrics architecture, and career/accountability design), gives concrete examples of misaligned incentives and how they produced measurable harm, and presents a repeatable rubric to choose metrics that resist gaming (multi-horizon measures, cohort-based LTV, cost‑to‑serve). Listeners receive a prioritized 30–90 day checklist to audit current incentives, sample KPI translations for finance/product/data, and negotiation language to align procurement and legal. Practical, non‑technical, and immediately actionable for leaders who must turn pilots into sustained 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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    11 mins
  • SLOs for AI: An Executive Playbook to Define, Monitor, and Enforce Model & Data Service-Level Objectives

    SLOs for AI: An Executive Playbook to Define, Monitor, and Enforce Model & Data Service-Level Objectives
    Feb 6 2026
    Executives often demand reliability from AI but lack a shared language to measure it. In this 20-minute monologue Mirko opens with a concise vignette where unseen model latency and stale features caused revenue slippage, then delivers a compact, decision-first playbook for Service-Level Objectives (SLOs) tailored to models and data. Listeners learn how to define business-aligned SLOs (accuracy bands, latency windows, freshness, fairness thresholds), set error budgets, choose a minimal monitoring signal set that executives can read, and map SLO breaches to concrete decision gates and funding actions. Practical artifacts include a board-ready SLO template, example alert thresholds, and a prioritized 30–90 day pilot plan to embed SLOs into governance. The episode keeps trade-offs explicit and non-technical so leaders can commission measurable reliability commitments. CTA: download the Executive SLO Template and 30–90 Day Playbook at datascience.show/slo. 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 mins
  • Price of Intelligence: An Executive Playbook for Governing Algorithmic Pricing

    Price of Intelligence: An Executive Playbook for Governing Algorithmic Pricing
    Feb 5 2026
    Dynamic pricing can unlock margin and responsiveness, but when algorithmic prices misalign with customer expectations or regulation, revenue wins can turn into churn, complaints, and legal risk. In this 20‑minute executive monologue Mirko presents a concise playbook for governing algorithmic pricing: translate pricing goals into board-ready SLOs (price stability, realized uplift, churn elasticity), detect economic and fairness drift, set tolerance bands and automated rollback gates, and convert technical signals into commercial decision rules. The episode opens with a short anonymized vignette where a miscalibrated model produced frequent outlier prices and measurable churn, then walks listeners through a prioritized 30–90 day audit and remediation checklist, contract and procurement clauses to insist on with vendors, and practical metrics to report to the board. Listeners leave with immediate actions and a downloadable one-page Algorithmic Pricing Governance Checklist to brief legal, product, and finance teams.

    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 mins
  • Causal Decisioning: How Leaders Prove AI Drives Value

    Causal Decisioning: How Leaders Prove AI Drives Value
    Feb 4 2026
    Many leaders celebrate accurate models but can’t prove they change outcomes. In this 20‑minute episode Mirko opens with a vivid executive vignette: a personalization pilot that tripled engagement yet didn’t move revenue, and uses that story to frame a compact, non‑technical playbook—what he calls causal decisioning—for proving AI actually drives value. He defines causal decisioning and the term “uplift” (the measured change caused by an intervention) in plain English, explains which minimal experiment designs leaders should demand, and includes a short two‑minute worked example showing a simple uplift calculation and how to read a sample dashboard. Practical rollout patterns, governance and consent checkpoints, and a prioritized 30–90 day checklist are provided. Listeners leave with board‑ready KPI translations and a link to download a Causal Decisioning Toolkit (experiment brief, dashboard template, legal checklist) so they can commission evidence and tie funding to measurable ROI.

    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 mins
  • Synthetic Signals: An Executive Playbook for Using Synthetic Data to Unlock Enterprise AI

    Synthetic Signals: An Executive Playbook for Using Synthetic Data to Unlock Enterprise AI
    Feb 3 2026
    Enterprises routinely hit practical limits: unavailable or sensitive data, rare-event gaps, and slow procurement that stalls valuable AI projects. In this focused 20‑minute episode Mirko gives senior leaders a pragmatic, decision-first playbook for using synthetic data as a strategic lever—not a silver bullet. Listeners get a short anonymized micro‑case showing measurable business impact, a plain‑language decision rubric (when to substitute, augment, or avoid synthetic data), board‑friendly ROI metrics (time‑to‑data, labeling cost delta, model performance vs baseline), and the concrete governance and contract artifacts executives must insist on. The episode closes with a prioritized 30–90 day checklist, negotiation language for procurement, and a 60–90s practitioner clip with hard lessons from a real pilot. Deliverables: a downloadable five‑item Executive Playbook and template vendor clauses to take to legal and procurement.

    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
  • AI in the Deal Room: An Executive Playbook for M&A Due Diligence and Post‑Merger Integration

    AI in the Deal Room: An Executive Playbook for M&A Due Diligence and Post‑Merger Integration
    Feb 2 2026
    Mergers and acquisitions routinely misprice or miss downstream costs of embedded AI: tangled data lineage, undocumented models, unenforceable IP claims, or regulatory exposures can turn strategic acquisitions into recurring liabilities. In this 20‑minute executive monologue Mirko delivers a decision‑first playbook for buyers and integration sponsors. He walks through focused AI due diligence (what to ask in 30–90 minutes of executive interviews), a lightweight technical checklist for validating model and data health without deep engineering work, legal and IP red flags to surface, and a prioritized post‑close integration plan that preserves optionality and reduces run-rate. Listeners get board‑ready metrics to translate technical findings into price adjustments and escrow triggers, negotiation levers to allocate remediation costs, and a 30–90 day integration roadmap to onboard models, align SLAs, and retire redundant pipelines. Practical, non‑technical, and immediately actionable for deal teams and executives. 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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    14 mins
  • Sunset Clause: An Executive Playbook for Retiring AI and Managing Model Debt

    Sunset Clause: An Executive Playbook for Retiring AI and Managing Model Debt
    Feb 1 2026
    AI lifecycles end as surely as they begin—yet most organizations lack an executive process to retire, replace, or repurpose models and datasets safely. In this focused monologue Mirko provides a decision‑first playbook that helps leaders identify retirement signals (drift, rising run-rate, opportunity cost, regulatory or contractual change), apply a pragmatic rubric balancing business value, risk, and technical debt, and run a prioritized decommissioning program. The episode covers stakeholder communication (internal owners, customers, regulators), legal and audit obligations for data retention and provenance, migration patterns (dual-run validation, phased rollback, staged sunset), and how to budget transitional costs so teams can stop subsidizing legacy systems. Listeners get a 30–90 day checklist to inventory candidates, cost ongoing run-rate vs replacement, define rollback and observability requirements, and embed retirement gates into governance. Practical, non‑technical, and action-oriented, this episode helps executives remove hidden liabilities and preserve strategic optionality.

    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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    12 mins