# AI strategy that starts with a better question.

> Decide is veridive’s AI strategy and discovery service. In an Executive Build Day or a Discovery Sprint of about two weeks, the team maps real workflows, measures today’s baseline, reviews data, access and risk, and delivers a scoped roadmap with a clear go/no-go decision on what to build first.

veridive helps leadership teams find where AI can make a useful difference, and where it would be a distraction. We map real workflows, measure today’s baseline and help you choose what is worth building first.

## What is AI strategy and discovery?

AI strategy and discovery is the work of choosing which workflows AI should change first, and proving the choice before anyone builds. veridive maps how the work actually happens, measures a baseline, checks that the data is reachable and the risks are acceptable, and ends with a scoped roadmap and a clear go/no-go.

## When should you talk to us?

- You have more AI ideas than owners, and no shared way to rank them.
- A pilot impressed in a demo but never became part of the daily work.
- Leadership keeps asking “build, buy or wait?” and nobody has the evidence to answer.
- You can’t say how long the work takes today, so you can’t prove that AI helped.
- You want to know which of your processes are ready for AI before you commit a budget.

## What do you get?

- **Opportunity map.** Candidate workflows scored for value and feasibility, with an owner named for each one.
- **Baseline measurements.** Volume, time per case, error rate and cost for the top workflows, recorded before anything is built.
- **Readiness review.** Where the data lives, who may access it, and the privacy, security and operational risks that need a decision.
- **Pilot plan with acceptance criteria.** What a first pilot would change, how it will be evaluated, and what “good enough” means for your team.
- **Roadmap and go/no-go.** A sequenced plan and a clear recommendation for each candidate: build, buy, wait or stop.

## How does a Discovery Sprint run?

1. **Frame** (Day 1). Agree the business goals, the candidate workflows and who owns each one.
2. **Walk the work** (Week 1). Sit with the people who do the work, map each step and collect real examples.
3. **Measure and test** (Weeks 1–2). Record the baseline, check data access and try the riskiest assumption on approved data.
4. **Recommend** (End of week 2). Present the scored map, the pilot plan and a go/no-go decision, in writing.

## How can you start?

- **Executive Build Day** · 1 day. One day with your leadership team. We build a working prototype on one of your real workflows, together, and leave you with three prioritized opportunities.
- **Discovery Sprint** · ≈2 weeks. A focused assessment of one or two workflows: baseline, data and access review, risks, and a pilot plan with acceptance criteria. Scope is confirmed after a first conversation.

## What changes?

- **A short list you can defend.** Leadership agrees on the few workflows worth changing, and on the reasons.
- **A baseline to measure against.** Every later claim about AI is compared with how the work runs today.
- **Owners, not orphans.** Each candidate has a named owner who will still be there after launch.
- **A decision, not a deck.** You leave with a go/no-go and a scoped next step, not a library of slides.

## Questions about AI strategy

### What is an AI Discovery Sprint?

A Discovery Sprint is a fixed-scope assessment of one or two workflows that takes about two weeks. veridive walks the real work with the people who do it, measures the baseline, reviews data access and risk, and delivers a pilot plan with acceptance criteria. Scope and price are fixed before it starts, after a first conversation.

### How is an Executive Build Day different from a Discovery Sprint?

An Executive Build Day is one day with your leadership team; a Discovery Sprint is about two weeks with the team that owns a workflow. The Build Day produces a working prototype on a real workflow and three prioritized opportunities. The Sprint goes deeper on one or two workflows and ends with a baseline, a risk review and a pilot plan.

### Do we need clean data before we start?

No. Discovery is where you find out whether the data is good enough, and reachable, for the workflows you care about. We look at where the information lives, who may access it and how current it is. If the data is not ready, the first project is often a data project, and the roadmap says so.

## Related

- Where it works: [Commerce intelligence](https://veridive.com/solutions/commerce-intelligence/) · [ERP & enterprise workflows](https://veridive.com/solutions/erp-enterprise-workflows/) · [Customer operations](https://veridive.com/solutions/customer-operations/)
- Field notes: [Choose the workflow before the model](https://veridive.com/insights/choose-the-workflow-before-the-model/) · [Questions leadership teams ask before their first AI project](https://veridive.com/insights/questions-before-your-first-ai-project/) · [The cost of a token vs. the cost of a mistake](https://veridive.com/insights/cost-of-a-token-vs-cost-of-a-mistake/)
- See also: [How we work](https://veridive.com/approach/) · [Ways in](https://veridive.com/services/#ways-in) · [Returns intelligence (illustrative engagement)](https://veridive.com/work/returns-intelligence/) · [Start a project](https://veridive.com/contact/)

## Not sure where AI fits yet?

Start with one conversation. Describe a workflow and we will reply within one business day with a recommended first step. [Start a project](https://veridive.com/contact/) or write to [hello@veridive.com](mailto:hello@veridive.com).