When I started in healthcare market research, delivering faster usually meant adding people, adding cost or accepting compromises.
AI gives us an opportunity to revisit that equation.
But the biggest gains come from choosing the right tasks. Here are the five areas where I believe AI can make a truly valuable contribution, with experienced researchers directing the work.
1. Getting up to speed before the research begins
Every project starts with questions. What do we already know? What has changed? Where are the gaps?
AI can help organise existing research, summarise relevant publications and retrieve findings from previous projects we have permission to use.
That gives researchers a stronger starting point for designing primary research.
The important discipline is checking the original sources. A confident summary is only useful if the evidence behind it is accurate, current and relevant.
2. Making research materials better
A good discussion guide requires thought, experience and a clear understanding of the client's decisions.
AI can contribute by suggesting alternative questions, identifying repetition, flagging potentially leading wording and proposing probes.
I particularly like its potential as a second reader: someone to challenge what we have written before respondents see it.
Researchers still need to decide what to ask, whom to ask and which approach will answer the business question.
3. Reducing the burden of processing data
Transcription, initial coding and organising interview material can consume substantial time.
AI can accelerate these activities, leaving researchers more time to engage with what respondents actually mean.
In international research, draft translations can also help teams navigate material across languages.
However, healthcare terminology demands care. A misheard treatment name or a mistranslated expression can change the meaning. Checks against recordings and review by appropriately qualified language specialists remain essential.
4. Finding patterns we might have missed
AI can help compare interviews, explore differences between respondent groups and identify apparent contradictions.
Perhaps physicians describe a barrier that patients barely mention. Perhaps a theme appears repeatedly in one market but rarely elsewhere.
These observations can prompt better questions and deeper investigation.
They are starting points for analysis. Researchers must examine the supporting evidence, consider exceptions and distinguish an interesting pattern from a meaningful finding.
5. Turning findings into clearer communication
AI can help structure a presentation, draft an executive summary or adapt findings for different audiences.
That matters because even excellent research has limited value if its implications are difficult to understand.
The researcher's responsibility is to preserve nuance, check every number and quotation, and ensure recommendations follow from the evidence.
A polished presentation still needs sound thinking behind it.
For me, the opportunity across all five areas is straightforward: spend less time on repetitive work and more time understanding people and helping clients make decisions.
Being close to fieldwork provides valuable context. Systematic checking provides the additional assurance that familiarity alone cannot.