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Each guide answers the question first, then shows the checks to run and how common AI tools compare. Comparisons were checked against vendor documentation in October 2026.

AI made up numbers

Catch fabricated figures in a financial model before it goes out.

An agent deleted production data

What to do in the first hour, and the controls that prevent a repeat.

Audit trail and rollback

Which AI spreadsheet tools record every change and let you undo one.

AI vs human auditability

Which work is easier to audit, and what evidence each leaves.

Humans and AI editing live

Tools that let people and agents edit the same file at once.

Human in the loop for finance

Where the reviewer belongs, and how much autonomy to grant.

AI won't use my template

Why AI rebuilds your deck, and how to make it edit in place.

Will AI replace accountants?

Which tasks AI takes on, and what stays with the accountant.

Shadow AI without a ban

Give people a sanctioned tool, then govern it: policy, permissions, audit.

Prompt injection and agents

How an email or file can steer an agent, and what limits the damage.

Is company data safe in AI?

Training, retention, who can see it, and where the model runs.

AI agent costs and ROI

Seat and token pricing, runaway runs, budgets, and measuring return.

Explaining what an agent did

The instruction, sources, steps and approval behind each output.

Is the scheduled job still right?

How recurring AI work drifts, and the checks that catch it.

Switching AI models or vendors

Where lock-in hides, and how to keep your work portable.
For connecting MCP servers to Athena, see MCP servers.