Workflow

A workflow is a defined sequence of steps that accomplishes a specific business task. In the context of AI, workflows combine human actions with AI processing to complete work more efficiently than either could alone.

What makes a workflow

Every workflow has:

• A trigger: What starts the process (a customer email arrives, a weekly report is due, a new lead enters the CRM)
• Steps: The actions performed in sequence (read the email, categorise it, draft a response, send it)
• Handoffs: Points where work moves from one person, system, or AI to another
• An output: The end result (the customer received a response, the report was published, the lead was qualified)

Before AI: manual workflows

Consider a typical content creation workflow before AI:

1. Writer researches the topic (2 hours)
2. Writer creates an outline (30 minutes)
3. Writer drafts the article (3 hours)
4. Editor reviews and provides feedback (1 hour)
5. Writer revises (1 hour)
6. Marketing formats for publication (30 minutes)
7. Marketing creates social media versions (45 minutes)

Total: approximately 9 hours per article.

After AI: augmented workflows

The same workflow with AI assistance:

1. AI researches and summarises key sources; writer reviews (30 minutes)
2. Writer creates outline with AI suggestions (15 minutes)
3. AI generates first draft from outline; writer refines (1 hour)
4. AI flags potential issues; editor reviews with AI context (30 minutes)
5. Writer makes final adjustments (30 minutes)
6. AI formats for publication (5 minutes)
7. AI generates social media versions; marketing reviews (15 minutes)

Total: approximately 3 hours per article. Same quality, 67% less time.

The workflow audit

Before adding AI to your workflows, conduct a workflow audit:

1. List your repeating tasks: Everything you do weekly or more frequently
2. Categorise each task: Is it language-based? Data-based? Creative? Administrative?
3. Score AI suitability: Rate each task on how well AI could assist (high/medium/low)
4. Estimate time savings: How much time would AI realistically save?
5. Prioritise: Start with high-suitability, high-time-savings tasks

Common AI workflow patterns

• Draft and refine: AI creates first versions of emails, reports, or content; humans review and polish
• Analyse and summarise: AI processes large volumes of text (meeting transcripts, research papers, feedback) and produces structured summaries
• Extract and organise: AI reads unstructured documents and populates structured databases or spreadsheets
• Monitor and alert: AI continuously monitors data sources and flags items that need human attention
• Transform and repurpose: AI converts content from one format to another (article to slides, email to tweet, notes to report)

Building effective AI workflows

Key principles:

• Start with the human process: Understand the current workflow before adding AI. If the human process is broken, AI will amplify the problems.
• Keep humans in the loop: AI generates drafts, suggestions, and analyses. Humans make final decisions, especially for external-facing output.
• Define quality standards: What does "good enough" AI output look like? When does human revision improve it versus waste time?
• Measure everything: Track time per task before and after AI. This data justifies continued investment and identifies where to optimise next.
• Iterate: Your first AI workflow will not be optimal. Refine prompts, adjust handoff points, and add or remove AI steps based on results.

Workflow tools

• Simple workflows: AI chat interfaces (ChatGPT, Claude) — manual but immediate
• Automated workflows: Make, Zapier, n8n — visual builders with AI API integration
• Custom workflows: Python scripts, internal tools — maximum flexibility
• Agent workflows: Claude Code, custom agent frameworks — autonomous multi-step execution