B2B services company, family-run
We selected AI initiatives with the leadership team
Management at a family-run B2B services company wanted to turn competing AI ideas into a shared roadmap with clear responsibilities.
| Industry | B2B Services |
|---|---|
| Services | AI Workshops, AI Transformation |
Each department brought a different AI priority
Sales, operations and administration had their own ideas for AI use. Some wanted to prepare proposals, others to speed up internal inquiries or generate reports automatically. In leadership discussions, the conversation quickly shifted from problems to tools. The effects on effort, margin and collaboration remained unclear.
Management wanted to make a decision without commissioning extensive studies first. The leadership team needed to show which workflows consumed time and who could take responsibility for a change. Some ideas looked attractive but required knowledge or data that nobody yet maintained reliably.
The workshop needed initiatives with accountable owners
Our task was to prepare and moderate a compact decision workshop. Participants needed to leave with a prioritized selection and concrete next steps. We agreed to assess expected business impact, access to required data and feasibility within the business team. Uncertain assumptions would remain visible and receive an assignment to test them.
The roadmap linked impact to available resources
Process examples replaced general ideas
Each department brought a recurring task. We described its trigger, work steps, handovers and the consequences of delays.
The assessment made assumptions visible
The leadership team compared business impact, data availability, effort and responsibility. Where assessments lacked a sufficient basis, we recorded the missing evidence.
Selected initiatives received named owners
Managers took business responsibility for the initial initiatives. They named contacts from daily operations and the next verifiable work step.
Deferred ideas retained their prerequisites
The remaining proposals received a reason for deferral. Data maintenance, access or missing capacity were recorded as prerequisites for reassessment.
Leaders resolved disputed assessments using real cases
Before the workshop, we asked participants for sanitized work examples. During the session, we reviewed them with management and department heads. A proposal request showed, for example, that the time-consuming research happened before writing. This shifted the discussion from text generation to access to approved project knowledge.
Participants initially assessed candidates from their own perspectives. We then discussed differences together. Operations could explain why an apparently simple workflow contained many exceptions. Management clarified which workload reductions would lead to different resource planning.
We limited parallel work to initiatives for which leaders also allocated business-team capacity. A technically appealing idea remained deferred because its data foundation was unclear. For selected initiatives, owners defined an acceptance condition and decided which assumption to test first.
At the end, each owner presented their next step. This showed, while everyone was still in the room, whether a decision was concrete enough. Open dependencies were assigned directly to a contact and added to the existing leadership meeting agenda.
Leadership could launch the selected initiatives
The leadership team left the workshop with a shared selection and named owners. The initiatives had a business purpose and a verifiable starting point. Deferred ideas remained documented with their reasoning. In regular meetings, management could ask about progress and open assumptions without reopening the selection each time.
An AI roadmap requires decisions about capacity
Bring a real case into the discussion
Concrete documents reveal which work an agent could take over and which prerequisite is missing.
Assessments can show uncertainty
An open assumption with an assignment to test it helps implementation more than an assessment softened into consensus.
Ownership includes available participation
A selected initiative needs experts who provide examples, review results and take responsibility for later changes.
A first conversation takes 30 minutes.
We clarify which decisions your leadership team needs to make for an actionable AI roadmap.