AI adoption playbook: 16-week rollout plan
These are the rollout checklists from our playbook on getting a team to use a new AI workflow. Tick what is already done. The full playbook adds the readiness scorecard, a question bank for managers, the training plan and templates.
Weeks 1 to 4: foundation
Before the pilot starts
Weeks 5 to 8: pilot
Weeks 9 to 16: waves
Measuring adoption
If you are planning a rollout and want a second opinion on the plan, a discovery call with Kastling is a practical place to start. We build training and adoption into the project rather than adding them after go-live.
Read the guide
AI workflow automation: a practical guide for operations teamsAI workflow automation puts AI models inside a defined business process to read, classify and prepare work, while fixed rules, integrations and named people handle the steps that must be predictable. It suits repetitive, document-heavy or request-heavy work such as intake, routing, document checks and approvals. This guide is for operations leaders at companies of roughly 20 to 200 people, mainly in the US and Canada: start with one measurable workflow, keep consequential approvals with an accountable person, and expand only once the numbers show it works.Read In-house vs agency vs AI partner vs freelancer: how to staff an AI projectFor a first AI workflow, a specialist partner with named internal owners is usually the fastest route, and in-house hiring makes sense once steady work can keep a team busy. An AI project also needs a business owner and a process owner from inside your company, plus AI engineering, integration, data, cloud and change skills that you can hire, contract or bring in through a partner. Whichever route you take, your company should own the code, the accounts and the documentation.Read
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