Most enterprise AI strategies take 12-18 months to produce their first production deployment. DGT has compressed this to 90 days — not by cutting corners, but by eliminating the organizational friction that slows most AI programs. Here is the playbook.
Weeks 1-2: Use Case Selection and Scoping
The most common mistake is starting with the most ambitious use case. Start with the use case that has the clearest data, the most willing business owner, and the most measurable outcome. This is usually not the CEO's favorite idea — it is the operations leader's pain point.
- Identify 5-8 candidate use cases through stakeholder interviews
- Score each on data readiness, business impact, and organizational willingness
- Select the one with the highest combined score — not the highest impact alone
- Define success metrics that are measurable within 90 days
Weeks 3-4: Data Readiness Sprint
Spend two weeks getting the data right. This is not a data engineering project — it is a focused sprint to connect, clean, and validate the specific data your use case needs. Use DGT's DataBridge accelerator to connect source systems and establish data quality baselines.
Weeks 5-8: Build, Test, Integrate
Four weeks of iterative development. Build the model, test it against real data, and integrate it into the business process where it will create value. This is where most programs stall — not because the model does not work, but because the integration with existing systems (SAP, Salesforce, ServiceNow) is harder than expected.
DGT's platform expertise is the differentiator here. We do not just build models — we integrate them into the enterprise platforms your team already uses.
Weeks 9-12: Deploy, Adopt, Measure
The final four weeks are about adoption, not technology. Train the users. Build the monitoring dashboards. Establish the feedback loops. And measure the outcomes against the success metrics you defined in Week 1.
If you hit your 90-day metrics, you have proof of concept for the organization — and the credibility to scale. If you miss them, you have learned exactly where the gaps are, and you can address them before investing further.
The goal of the first 90 days is not perfection. It is proof — proof that your organization can execute on AI, and a clear roadmap for what comes next.