How was AI used in the delivery of this project? Toggle on each stage where AI was used, then select the specific ways it contributed.
Where Claude helped — select all that apply
Research the client company ahead of the meeting
Generate smart discovery questions tailored to their sector
Summarise recent news, leadership moves, or growth signals
Draft a pre-meeting briefing note from public information
Where Claude helped — select all that apply
Draft the proposal structure and narrative from meeting notes
Write a compelling opening that reflects the client's specific challenge
Sharpen the language — remove jargon, increase clarity and impact
Stress-test the proposal by anticipating client objections
Where Claude helped — select all that apply
Turn rough call notes into a structured mandate document
Extract key criteria and flag gaps with [TO CONFIRM]
Build an ideal candidate profile from the brief
Draft clarifying questions to send back to the client
Where Claude helped — select all that apply
Identify target organisations and feeder companies
Suggest search geography based on the talent pool
Draft a project timeline and key milestones
Create a structured research brief for the team
Where Claude helped — select all that apply
Build a market overview for the mandate sector
Identify and research target organisations
Draft individual candidate research summaries
Compile compensation benchmark data
Where Claude helped — select all that apply
Build Boolean search strings for LinkedIn and other platforms
Analyse org structures and identify function leaders
Compare candidates against the mandate brief
Draft a structured longlist with brief summaries
Where Claude helped — select all that apply
Draft personalised outreach messages for each target
Write email and LinkedIn InMail templates
Adapt tone and content for different seniority levels
Follow-up messaging for non-responses
Where Claude helped — select all that apply
Prepare interview guides and qualifying questions
Summarise conversation notes into candidate assessments
Flag red flags or gaps in candidate profiles
Draft candidate update emails
Where Claude helped — select all that apply
Draft candidate profiles from conversation notes and CVs
Ensure consistent structure and tone across all profiles
Summarise key strengths and areas to probe in interview
Proofread and refine final profiles
Where Claude helped — select all that apply
Summarise market themes emerging from candidate conversations
Draft the market intelligence section of the report
Identify patterns across candidate motivations and concerns
Structure findings into clear, client-ready insights
Where Claude helped — select all that apply
Structure and draft the full shortlist report
Write an executive summary of the market and process
Ensure consistent tone and formatting throughout
Final proofread before client submission
Where Claude helped — select all that apply
Prepare a presentation narrative and talking points
Anticipate client questions and draft responses
Summarise key candidate differentiators for quick reference
Draft follow-up notes and agreed actions post-presentation
Where Claude helped — select all that apply
Review and structure the final dataset for delivery
Draft a handover document explaining how to use the data
Suggest next steps for pipelining or ongoing intelligence