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AI Strategy

AI strategy is not a board-slide category. It is the set of technical and organizational choices that decide whether AI work improves margin, reduces risk, or increases throughput.

This hub focuses on the operating questions: what to fund, what to stop funding, how to measure progress, and how to keep architecture decisions connected to business outcomes.

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Decision Criteria

Strong AI strategy answers four questions before implementation starts:

  1. Which workflow changes if the system works?
  2. Which owner is accountable for quality after launch?
  3. Which cost or risk metric proves the investment is working?
  4. Which fallback keeps the business running when the model path degrades?

If those answers are missing, the work is still experimentation. That can be fine, but it should be funded and measured as experimentation.

Practical Reading Paths

For budget decisions:

For organization design:

For technical execution:

Failure Modes

  • Funding AI initiatives because competitors announced something similar.
  • Treating vendor selection as strategy while ignoring data readiness and workflow ownership.
  • Reporting activity metrics instead of margin, risk, speed, quality, or throughput.
  • Letting every team build isolated AI tooling without shared evaluation and governance.

References

40 entries tagged “AI Strategy”

    Compliance Fails at the Vendor Handoff · 4 min You answer for an AI system you can only partly witness. Build a compliance interface to each vendor, with owners, deadlines, and drills. compliance governance ai Agent Scale Has a Company-Size Gap · 4 min Large firms report scaling AI agents; smaller ones sit flat. A small company needs one workflow with an owner, gate, boundary, spend cap, and off switch. ai strategy operations A Backup Model You Never Exercise Is Not a Backup · 4 min Vendor count is inventory; measured failover time is resilience. Shadow replay, a bounded canary, and a recovery clock with defined start and stop. ai reliability strategy The Statistic Nobody Can Reconstruct · 4 min I tried to reconstruct '95% of AI pilots fail.' It isn't in the report it cites. Card the numbers that steer your decisions: licensed, expired, or retired. metrics ai executive Don't Book the Cut Before the Work Disappears · 4 min Expected AI headcount cuts outran reported ones last year. Let forecasts drive scenarios; book a saving only once the work has observably gone. leadership teams ai The Software You Didn't Buy Still Needs an Owner · 4 min Teams skip software purchases and build with agents. Each build is rational; the fleet is the risk. Agents compress upkeep but can't own it. strategy ai cost The EU Gave You a Reprieve, Not a Pardon · 5 min The Digital Omnibus deferred the AI Act's high-risk duties, not its live ones. Build a deferral ledger: one row per system and obligation. governance compliance ai Geopolitical Model Risk Is an Engineering Constraint · 4 min Export controls, gated releases, and open-to-closed reversals make model availability an architecture-review line item. ai architecture strategy The Diffusion Gap: Why Pilots Don't Become Capability · 4 min Most AI pilots pass the trial and then die. Closing the gap takes ownership, cadence, and incentives. Write exit criteria as operating changes. ai operations leadership Unsupervised · 7 min Producing the work can be handed to a machine. Answering for it cannot. What an organization values when machines do most of the making, what people are for, and four things to try this week. opinion ai strategy Power Belongs on the AI Roadmap · 3 min Grid power and GPU quota arrive on lead times of months to years. Put region, capacity type, owner, and fallback next to every committed AI ramp. ai architecture strategy Your Vendor's Balance Sheet Is Your Risk · 4 min AI vendor risk you can price: compare the API price to a self-hosted floor, lock deprecation notice and export rights at signing, fund a warm fallback. strategy ai cost The Benchmark You Didn't Build · 4 min Use public LLM benchmarks as a shortlist filter, then decide on an owned eval: programmatic assertions, a versioned LLM judge, and paired per-case diffs. ai reliability metrics Sovereignty-by-Design for AI: How to Win Regulated Enterprise Deals · 4 min AI data sovereignty an auditor can test: BYOK, in-region decryption, and which copies key revocation kills versus which need signed delete receipts. ai privacy governance The AI Strategy Stack: What Boards Mistake for Moats · 4 min Models and prompt scaffolding are not AI moats. The defensible layer is a correction loop on your own work, tracked by escalation rate, and it depreciates. strategy ai executive From Model Demos to Profit Engines: The CTO Playbook for AI Unit Economics · 3 min AI unit economics: route requests by value and risk, price in failure and rework, and measure margin per workflow instead of per model call. ai cost strategy The New Talent Stack: Product, Platform, and Applied AI Must Work as One System · 2 min AI organizations create leverage when product, platform, and applied AI are designed as one operating system instead of three kingdoms. teams ai platform-engineering The Post-Prototype AI Org: Operating Models That Survive Year Two Canon post — · 2 min Year-two AI failure usually comes from org-design mismatch, not model-quality mismatch. The handoffs are where the system slows down. ai teams leadership Decision Latency as a P&L Variable: The Leadership Metric Nobody Owns Canon post — · 2 min Slow decisions are a hidden cost. How to measure decision latency, from issue to decision to action, and cut it with clear ownership of decision classes. leadership metrics strategy The AI Vendor Negotiation Playbook for CTOs · 3 min A pre-meeting checklist for AI vendor contract negotiations: know your workload, switching cost, eval evidence, and exit plan before the vendor does. ai strategy cost AI Roadmaps That Survive Contact With Reality Canon post — · 3 min AI roadmaps fail when they are sequenced around ambition instead of dependency, verification, and rollback cost. strategy ai leadership Technical Leadership in the AI Era: Throughput Over Trends · 3 min Technical leadership in 2026: anchor decisions in throughput, verification, and operability instead of chasing the latest agent framework. leadership ai teams Stop Building Internal AI Tools No One Uses · 4 min Internal AI tools die quietly when teams optimize for launch over workflow fit, output trust, and post-launch ownership. One tool failed, one stuck. productivity ai leadership Build the System the Model Cannot Break Canon post — · 12 min A manifesto for AI-native organizations: twelve tenets across strategy, architecture, economics, and people, and the one test that matters in year two. opinion ai strategy Measuring AI Progress Without Theater: A Board Scorecard · 2 min Most AI progress reporting confuses activity with value. Executive measurement should collapse around adoption, reliability, margin, and delivery speed. metrics ai executive AI Build vs. Buy in 2026: An Operational Cost Question · 3 min AI build vs. buy in 2026 turns on operational cost: who owns telemetry, fallbacks, and data residency. When to buy, when to build, and the hybrid default. strategy ai architecture AI Strategy Metrics: Margin, Risk, and Speed · 2 min Replace AI novelty metrics with three executive numbers: margin, risk, and speed. Give each a baseline, target, owner, cadence, and rollback path. ai metrics strategy AI Capital Allocation: What to Stop Funding First · 4 min Strong AI strategy starts with a kill list. If a project cannot defend margin, risk, or speed, it should not survive the next budget meeting. ai strategy cost AI Strategy for CTOs: It's Data Infrastructure · 2 min AI strategy for CTOs: the moat is the context pipeline, the eval loop, and the fallback path. Picking a model is the easiest problem in the room. strategy ai executive The Throughput Engineer: Why Headcount Is a Lagging Metric Canon post — · 7 min Headcount is a lagging metric. The best engineering organizations measure throughput: decision speed, defect containment, and constraint removal. leadership productivity operations AI Product Metrics: Measure Task Success, Not Usage · 3 min Engagement metrics tell you people clicked, not whether your AI feature helped. Measure task success, correctness, and trust signals instead. metrics ai strategy AI Trends for 2025: Why Engineering Discipline Wins · 4 min The AI hype cycle is over. 2025 belongs to teams that make AI work in production: repeatably, measurably, and without burning money. ai trends strategy AI in 2025 Will Reward the Boring Teams · 3 min The AI advantage in 2025 goes to teams that ship measurable workflows. Where to focus: evaluation, cost attribution, lightweight governance. ai strategy Why Enterprise AI Pilots Stall Between Demo and Production · 4 min Most enterprise AI pilots stall between demo and production. The blockers are organizational: ownership, security review, data access, governance. business ai strategy AI Product Strategy: Start With the Problem, Not the Model · 4 min Every 2023 roadmap has an AI feature, and most start from the model. A filter and five questions for picking AI features users will actually value. ai strategy startups What I Learned Building AI Features Into a Fintech Product · 5 min Shipping AI transaction categorization in a fintech product: two-day demo, six weeks to production. Eval sets, input normalization, fallbacks, rollout. ai strategy business AI Startups and the GPT Wrapper Problem · 3 min Most 2023 AI startups are GPT wrappers the platform can absorb. What makes one defensible, from a former startup founder. ai startups strategy How We Track and Prioritize Tech Debt at a Fintech Startup · 5 min A framework for cataloging technical debt, scoring it by impact and risk, and scheduling paydown without stalling feature delivery. technical-debt engineering leadership Technical Debt Triage: A Simple Prioritization Framework · 4 min Score tech debt by impact times change frequency to decide what to fix now, schedule, or accept. How it cut our 47-item list to six at a fintech startup. technical-debt engineering strategy The Business Case for Infrastructure: Pitch It in Money · 3 min Boards fund money, risk, and speed. How I pitched infrastructure investment at a fintech startup: business framing, rough ROI, and a skimmable proposal. infrastructure leadership business
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