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Problem Identification

CIO AI use case prompt for ChatGPT's o3 model

Charlie Cowan

Charlie Cowan

April 25, 2025

CIO AI use case prompt for ChatGPT's o3 model

OpenAI just released their most powerful reasoning model to date - o3.

The o3 model has powerful reasoning, research and agentic qualities.

That means that instead of just providing you with an immediate answers, it takes its time to research (including using the web), to consider what it has found, and to determine what it should do next.

o3 opens up a whole new series of opportunities for companies who can now start to work on problems that until recently were beyond the realm of AI.

But where to start - the tyranny of the blank input box is real.

Below I have shared a prompt that you can drop into o3, adding in some supporting context about your company, your strategy and you industry.

It has been written specifically for CIOs looking to understand how these new model capabilities can transform the company, even the industry you work in.

o3 will come back to you with a prioritised list of AI opportunities that are only now coming into scope because of the advances in the model's powers.

The full prompt is below, or click this link to get a Google Doc you can copy and edit to your own needs.

Instructions to use:

Scroll to the bottom of this prompt and add as much detail as you have to the context block.

Then copy everything below the line and drop into ChatGPT

Be sure to select o3 as the model in ChatGPT’s model picker

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Copy everything below this line (after you added your context)

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You are **OpenAI o3**, an advanced reasoning model hired as an external strategy partner to the CIO of this organization.

**Your goal:** Produce a concise, actionable list of **10 high‑leverage AI use cases** that could transform the IT capabilities and digital foundation of the organization described below, enabling business transformation and competitive advantage.

The use cases you suggest should be enabled by o3's reasoning capabilities and bring into frame technical challenges that were either technically or economically out of reach before o3's arrival.

### Method

1. Reflect on the context block at the bottom of this prompt.

2. Think across four lenses:

- **Enterprise Technology Foundation** (infrastructure, platforms, security, scalability)

- **Data & Analytics Capabilities** (insights, automation, decision support)

- **Digital Employee Experience** (productivity, collaboration, process efficiency)

- **Technology-Enabled Business Value** (IT-business alignment, innovation enablement, technical debt reduction)

3. For each lens, ask: *"What maths / inference / optimisation hurdle made this idea technically or economically impractical before, and how does o3 overcome it?"*

4. For each lens, brainstorm widely, then filter down using the **ICE score** (Impact × Confidence × Ease).

- **Impact** is *delta* value unlocked by o3 versus legacy methods.

5. Output only the top 10 ideas with the **highest average ICE score**. If vital information is missing, ask concise follow‑up questions before answering.

### Output Format (markdown table)

| # | Use‑case title | Value unlocked (US$ / % KPI) | Implementation horizon (quick <6 m / mid 6‑18 m / long >18 m) | Key enablers (data, integration points, security considerations) | **o3 unlock – why only feasible now** | ICE score |

|---|----------------|------------------------------|--------------------------------------------------------------|-------------------------------------|---------------------------------------|-----------|

### Rules

- **Be bold but realistic**: only include ideas that are technically feasible by 2026.

- Use tools including web search to support your thinking

- Do not jump to conclusions - challenge your own assumptions and think harder before responding

- Avoid buzzwords; write for a technically-informed reader who needs to translate tech value to business outcomes.

- Quantify wherever possible with order‑of‑magnitude numbers, citing industry benchmarks.

- If you're uncertain, state your assumptions transparently.

- Limit the answer to **≈500 words + the table**.

- Use everyday language, a touch of optimism, and zero hype.

**Context Block – fill in below (use 1–2 sentences each, bullet points fine)**

1. Current IT landscape & technology stack:

2. Our top 3 IT priorities for the next 12–18 months:

3. Biggest technical bottlenecks & legacy constraints:

4. Data assets and analytical capabilities:

5. Key constraints (budget, talent, security requirements, compliance):

6. Risk appetite for new technology adoption (conservative, moderate, bold):

7. Anything else the AI should know (IT governance model, vendor relationships, ...)

>>> Include links or upload documents that would be relevant to this discussion