How to Be an AI Consultant

Companies know AI matters but do not know where to start. An AI consultant finds the tasks where AI saves real time or money, sets up the tools, trains the team, and makes sure it keeps working.

Clients do not buy AI. They buy hours back, fewer errors, and more revenue.

• Hands-on skill with tools like ChatGPT, Claude, Gemini, and automation platforms
• Process thinking: mapping how work really gets done
• Clear communication with non-technical people
• Basic data privacy and security knowledge
• Enough technical depth to know what is realistic

• An industry you know, such as real estate, law firms, or clinics
• A function, such as sales, support, or finance
• A company size, such as businesses with 10 to 100 staff

“AI for accounting firms” is easier to sell than “AI consulting.”

• Automate parts of your own work and document the results
• Do two or three projects at a discount in exchange for a case study
• Share before-and-after examples with real, permitted numbers

AI audit

Review workflows and deliver a prioritised plan

Implementation

Set up tools, prompts, and automations for one workflow

Training

Workshops so teams use AI well and safely

Retainer

Ongoing support, updates, and new use cases

• Price fixed projects by value delivered, not hours
• Start with a paid audit so clients can try you with low risk
• Raise prices as your case studies grow

• Start with your network and former employers
• Post useful AI tips for your niche on LinkedIn
• Run a free workshop for a local business group
• Partner with agencies and IT firms that lack AI skills

Act as my discovery coach. I am meeting a [industry] company with [size] staff. Give me 12 questions to find their most time-consuming tasks, their tools, their data rules, and how they would measure success.

• Start with one workflow and win quickly
• Measure the baseline before you change anything
• Write simple guides for each new process
• Train the people who will use it daily
• Check in after 30 days

Time saved

Hours per week multiplied by hourly cost

Quality

Fewer errors or faster response times

Revenue

More leads handled or deals closed

• Use a written contract with scope, deliverables, and payment terms
• Sign NDAs and follow clients’ data rules
• Use business plans of AI tools with proper data protections
• Never paste client secrets into tools that are not approved

• Set aside time every week to test new tools
• Follow official release notes, not just social media
• Update your clients when better options appear

• Selling AI hype instead of measurable results
• Building complex systems nobody maintains
• Promising accuracy AI cannot guarantee
• Ignoring change management and training