Start with the risk, not the subscription
Before adopting a workplace assistant, decide what data it will receive and what it may change. The NIST AI Risk Management Framework organizes AI risk around the system’s context, measurement and management. Our practical interpretation: a meeting summary, a customer refund and a payroll change do not belong in the same approval bucket.
Begin with public or approved non-sensitive material and reversible outputs. Drafting an internal outline is easier to inspect and undo than sending a contract. Do not upload customer data, employee records, secrets or confidential plans merely because the interface has a file-upload button. Check your organization’s policy and the exact service terms. The Gemini pricing page is one concrete example of why free and paid data-use conditions deserve separate reading.
Keep the person responsible visible
Name an owner for each workflow: who supplies the inputs, who checks the result and who approves any action? A model can produce a proposed answer; the person accountable for sending it should still see the recipient, text and supporting evidence. For consequential decisions, use the appropriate professional review rather than treating the assistant as a substitute for expertise.
External material should remain untrusted. A webpage, email or document can include text designed to redirect an assistant. OWASP’s prompt-injection guidance describes that risk. Our recommendation is to keep tools narrowly scoped and to require explicit approval before publishing, sending, spending or modifying important records. “The document asked me to” is not authorization.
Measure the work after the draft
Track the whole process, not just time to first output. Include checking sources, correcting mistakes, formatting and handling failures. The evaluation guide supports using explicit criteria and representative cases. A draft that arrives quickly but requires a full rewrite may not save effort. We make no measured time-saving claim here.
For a small pilot, choose a bounded task and write a rubric. Record whether the result was usable, what needed correction and how much review was required. Stop or narrow the workflow if it repeatedly invents facts or crosses permission boundaries. Keep a manual fallback so the team can finish the job when the service is unavailable.
A pilot worth running
Exercise: Your team wants to summarize a confidential customer call in a new free app. What comes before uploading it?
Answer: Confirm consent where applicable, organizational approval, data-processing terms, access and retention controls. If those are unresolved, use a public or synthetic sample to design the workflow instead. This is a planning exercise, not an invitation to sign into a personal account.
The takeaway: the premium feature is not maximal autonomy. It is a useful output with clear evidence, controlled data and an accountable owner. Keep those boring parts, and the exciting parts have a chance to stick.