CTO-Level AI Decisions
5 min read
Cto
Cto
Your board wants clarity. Give them a decision framework, not a buzzword deck.
CTO-Level AI Decisions
TL;DR
- Build vs. buy vs. AI is now a three-way choice. Each has different trade-offs.
- AI changes the math: some things that used to require a vendor or internal build can now be "AI-assisted" for much less.
- Your job: make the framework explicit so the org can make consistent decisions without you in the room.
The board asks: "What's our AI strategy?" The VP of Eng asks: "Do we build this or use a vendor?" The product team asks: "Can AI do this for us?" You need a framework. Not a deck full of buzzwords. A way to consistently evaluate options and make calls.
The Three-Way Choice
Build
- Full control, tailored to your needs. High cost, slow. Good when: competitive differentiation, heavy customization, regulatory constraints.
- AI angle: Building is faster now. Internal teams can prototype with AI. The bar for "we should build" is lower for some things.
Buy
- Fast, supported, proven. Less control, ongoing cost, potential lock-in. Good when: non-differentiating, standard problem, speed matters.
- AI angle: Many vendors are adding AI. Evaluate whether their AI features matter for your use case — or if you're paying for AI theater.
AI-Assist
- Use AI (GPT, Claude, internal models) to augment humans. No full product, no vendor. Good when: workflow acceleration, content generation, low-risk tasks.
- AI angle: This is the new option. "We'll use AI to draft specs" is different from "we'll buy a spec tool" or "we'll build one."
When to Choose Which
| Situation | Lean Toward |
|---|---|
| Core product, key differentiator | Build (possibly AI-augmented) |
| Standard infra (auth, billing, etc.) | Buy |
| Internal productivity (docs, code gen, triage) | AI-Assist |
| Compliance-heavy, sensitive data | Build or Buy (carefully); avoid public AI |
| Experimentation, unclear ROI | AI-Assist first; graduate to Build/Buy if it sticks |
CTO-Specific AI Decisions
1. Tool standardization
- Do you standardize on Cursor, Copilot, something else? Or allow choice?
- Standardization simplifies support and security. Choice enables experimentation. Pick one and explain why.
2. Data and IP governance
- What goes into AI tools? What doesn't? Public models vs. on-prem vs. air-gapped?
- One policy. Communicate it. Enforce it.
3. Build vs. buy for AI capabilities
- Do you fine-tune your own model? Use OpenAI/Anthropic? Wait?
- Most companies should use APIs for now. Building your own only makes sense at scale or with unique data.
4. ROI and headcount
- "AI will let us do more with less" — true only if you adjust scope or accept risk. Make the trade-off explicit to the board.
- Don't promise headcount reduction without a plan. You'll get the reduction without the plan.
Manual process. Repetitive tasks. Limited scale.
Click "With AI" to see the difference →
Quick Check
What remains human when AI automates more of this role?
Do This Next
- Document your build/buy/AI framework — One page. Share with direct reports. Use it in the next three decisions.
- Audit one vendor — Is their "AI" feature real or marketing? If you're paying for it, know what you get.
- Prepare a one-slide AI summary for the board — Tools we use, governance we have, risks we're watching. Rehearse it.