Tags

AI Adoption

AI Adoption

0 lessons
6 AI Engineering questions

ai-adoption

AI Engineering

6 questions
AI Engineering

Choose which team workflows to hand to AI

Judge six workflows at a fictional home-services company by volume, error cost, checking effort, data, and the people affected, set an automation level and a human checkpoint for each, and choose the first pilot.

ai-engineering
ai-adoption
leadership
decision-making

3

Easy
AI Engineering

Turn an executive's AI mandate into a scoped pilot

Answer a COO who wants AI on every customer email and support costs down by a third: find the goal behind the request, check both targets against the team's figures and rules, and commit to a pilot you can measure.

ai-engineering
ai-adoption
stakeholder-management
communication

3

Easy
AI Engineering

Measure an AI pilot's quality, cost, and return

Judge a six-week AI order-entry pilot against a team that did not use the tool, count its full cost and quality per order channel, and recommend whether to expand, fix, or stop it with a budget cap and a review date.

ai-engineering
ai-adoption
estimation
llm-evaluation

3

Medium
AI Engineering

Decide whether to build or buy an AI tool

Choose between the AI feature in your finance suite, a specialist vendor, and an in-house build: apply hard gates first, read a pilot on your own invoices, compare three-year cost on one basis, and recommend one option with contract conditions and an exit plan.

ai-engineering
decision-making
data-privacy
ai-adoption

2

Medium
AI Engineering

Judge whether coding assistants helped your team

Use three quarters of team delivery data to separate what coding assistants changed from a holiday freeze and a migration, check whether code review became the bottleneck, and recommend which seats to renew and whether and how to try agent mode.

ai-engineering
coding-assistants
engineering-manager
ai-adoption

3

Medium
AI Engineering
Premium

Plan an AI rollout across a support team

Plan a staged rollout of AI drafting, knowledge suggestions, and auto-tagging across a fictional retailer's 64-agent support team before peak season. Set the automation level per queue, size each stage against training, QA, cost, and calendar limits, write gates before results, and lead the people side honestly.

ai-engineering
ai-adoption
leadership
stakeholder-management
responsible-ai

0

Hard