Artificial Intelligence

The Autonomy Ladder

Give AI only as much authority as the job needs

Start at the lowest useful level. Move upward only when evidence, permissions, review, and recovery make the additional autonomy safe.

1. FIND

   Retrieve approved context

   Search records, documents, and knowledge while respecting workspace permissions.

2. EXTRACT

   Structure information

   Read unstructured files or messages and return validated fields, classes, and summaries.

3. DRAFT

   Prepare work for review

   Write a response, report, brief, or recommendation that a person can inspect and change.

4. RECOMMEND

   Suggest the next action

   Compare rules and evidence, explain the reasoning, and let an authorized person decide.

5. ACT

   Complete a bounded task

   Use approved tools inside explicit limits with logs, stop conditions, and a recovery path.

Strong AI Jobs

High context, repeatable judgment, reviewable output

AI fits best when the task consumes attention but the output can be checked against evidence and business rules.

• Research follows a repeatable structure

• Documents contain important but inconsistent fields

• Knowledge is useful but difficult to locate

• A person repeatedly drafts the same kind of response

• Incoming requests need classification before routing

• Recommendations can cite the information behind them

What Artificial Intelligence Can Help Do

Example	What it helps accomplish
Prospect research	Investigate a company, evaluate fit, and prepare a useful sales brief.
Document extraction	Read PDFs and files and return the important fields as structured data.
Document classification	Route agreements, invoices, applications, and messages by content.
Summarization	Turn long records, conversations, reports, or files into concise context.
Knowledge search	Help employees find answers across approved internal information.
Customer guidance	Answer questions and direct customers toward the right service or next step.
Message drafting	Prepare contextual email, follow-up, support, and internal communication.
Meeting preparation	Compile account history, open questions, risks, and recommended talking points.
Triage	Evaluate incoming requests and recommend priority, category, or ownership.
Data quality review	Detect incomplete, inconsistent, duplicated, or suspicious records.
Recommendation support	Compare available information and suggest relevant options or actions.
Workflow decisions	Interpret unstructured input before a controlled automation continues.

What We Do Not Automate Blindly

• Irreversible decisions without an authorized human checkpoint.
• Actions that cannot explain which records or evidence informed them.
• Access across data boundaries the user could not cross directly.
• Open-ended agents without budgets, allowed tools, stop conditions, and logs.
• High-stakes outputs with no practical validation or recovery path.

From Model To System

The work around the model creates trust

• 01

  Ground it

  Connect approved records, knowledge, and current workflow context.

• 02

  Constrain it

  Define schemas, permissions, tools, confidence thresholds, and escalation rules.

• 03

  Measure it

  Review accuracy, corrections, cost, latency, business outcome, and failure patterns.

Explore An AI Opportunity->