VivoLearn

AI In Business: Directing Intelligence · Domain Playbooks

What should AI do in each business function — and what should it not?

14 domains, 85 processes, 491 stages — each stage scored with a four-verdict instrument, with the reasoning and the blockers on the record. Pick a domain to explore its playbook.

Automate
An agent does it; humans spot-check.
Draft
AI produces; a named human owns the result.
Assist
AI at the edges of a human task.
Avoid
Not yet — and the blocker is named.

The landscape

Every process from the fourteen playbooks, placed by how much of it AI can own and the sophistication it takes to get there. Note the empty bottom row: no core business process is a one-prompt job.

Front officeBack officeStrategy & operationsTechnology
AGENT-TEAM FACTORYhigh payoff, worth the orchestrationHARD ORCHESTRATION,THIN PAYOFFempty by good judgmentEMPTY BY FINDINGno core business process is a one-prompt job25%40%55%70%85%PromptSkillWorkflowAgentAgent teamshare of process stages AI can own (verdict-weighted) →AI sophistication the process needs →
Dot size = cadence:ContinuousPer eventPeriodicHover a dot for details; click to highlight its domain, click again to open the playbook.

The playbooks

Customer Support & Success

6 processes · 32 stages

AI should own the middle of every ticket (classify, retrieve, draft) while humans own the two ends — the policy that constrains it and the exceptions that escape it.

Data & Analytics

6 processes · 33 stages

AI is a superb query-writer and a dangerous analyst — automate the mechanical translation layers aggressively, and keep humans owning every step where a subtle error produces a confident, wrong number that executives will repeat.

Executive & Administration

6 processes · 34 stages

AI can produce almost everything this layer produces, and can own almost none of it — the leverage is in reclaiming synthesis hours to spend on judgment and relationships.

Finance & Accounting

6 processes · 34 stages

AI eats the reconciliation and drafting middle of the pipeline fast, while attestation, judgment calls on estimates, and anything auditors will re-perform stay Draft-at-best.

HR & People

6 processes · 33 stages

automate the paperwork around people decisions; never let the model make, or appear to make, the decision.

Information Systems & IT

6 processes · 36 stages

automate the reading and the drafting aggressively, keep humans on the writes to production and identity — and remember that AI agents are now themselves IT assets that need accounts, permissions, and offboarding like any employee.

Legal & Compliance

6 processes · 35 stages

AI compresses legal reading by an order of magnitude and legal drafting by half, but privilege, sanctions risk, and the duty of candor keep a licensed human's name on everything that leaves the building.

Marketing & Content

6 processes · 36 stages

AI has collapsed the cost of producing marketing assets to near zero, so the scarce skills are now positioning judgment, taste, and knowing which of a thousand cheap variants to ship.

Operations & Supply Chain

6 processes · 35 stages

AI excels at watching, reconciling, and drafting across operations' enormous document and data flows, but every verdict must respect a hard constraint — the cost of an error here is physical, and physical errors don't have an undo button.

Product & Strategy

6 processes · 32 stages

AI has collapsed the cost of the synthesis and drafting layers, which means the product manager's job is shifting from producing documents to owning the calls those documents encode — and the fastest way to fail is to let fluent AI drafts substitute for talking to actual customers.

Sales

6 processes · 36 stages

AI gives every rep a research team and a chief of staff, and the sellers who win are the ones who spend the reclaimed hours in front of customers instead of generating more automated noise.

Software Development

7 processes · 40 stages

code is the most verifiable artifact in business (it compiles, tests pass or fail, CI is binary), so AI can be pushed harder here than in any other domain — *provided* the verification layer (tests + CI) is strong, because that layer is what converts "AI wrote it" from a risk into a non-event. Where verification thins out — ambiguous requirements, architecture bets, production deploys — humans stay in the loop, and that's exactly where you'll feel it in weeks 9-14.

Strategy

6 processes · 38 stages

Deep-research agents have made the analysis layer nearly free, which moves the scarce skill upstream to framing the question and downstream to challenging the synthesis; the bet itself — the choice, the conviction, the accountability — remains stubbornly, correctly human.

Technology & Product Evaluation

6 processes · 37 stages

AI dramatically accelerates the *processing* of evaluation material (summarizing, scoring, cross-referencing, drafting test plans), but the *evidence-generating* steps — talking to users, running your own tests, checking references — must stay independent, because an AI summarizing a vendor's marketing inherits the vendor's framing.