Artificial intelligence is no longer a futuristic buzzword reserved for Silicon Roundabout start-ups or niche academic conferences. Today, technologies like ChatGPT shape the way Britons shop, learn, work, bank, vote, and interact with one another. Among its most profound—yet least understood—capabilities is its potential to assist with user-profiling: the process of analysing data to understand people’s preferences, behaviours, motivations, and likely actions.
As a member of the UK academic policy community, I have observed first-hand how rapidly this space is evolving. A combination of advanced AI models, vast datasets, and increasingly seamless integration across platforms means that user-profiling is moving far beyond simple marketing segments. It now touches public services, national security, online safety, education, healthcare, and even democratic trust. ChatGPT, in particular, has accelerated this shift by making complex data analysis accessible to organisations of every size—from Britain’s largest retailers to the smallest voluntary groups.
Yet, despite its power, the public discourse on AI-assisted profiling often oscillates between extremes: breathless enthusiasm about efficiency, or apocalyptic fears of dystopian surveillance. The truth lies somewhere in between. If used responsibly, ChatGPT can democratise insights, reduce inequality, strengthen services, and empower individuals. If used poorly, it could erode privacy, reinforce bias, and undermine public confidence in institutions and technology alike.
This article explores what ChatGPT-assisted user profiling really means, where it is already being used across the UK, the promises it holds, the risks it carries, and—most importantly—the principles Britain should adopt to govern its future.
To begin with, we must clear up a misconception. ChatGPT is not, by default, a data-scraping machine rummaging through personal details. It does not “hunt” for private information across the internet. Instead, organisations provide ChatGPT with inputs—data they already own or have lawful access to—and ChatGPT helps them interpret patterns.
For example:
A supermarket might provide anonymised customer feedback to identify emerging shopping trends.
A local council might analyse residents’ comments to understand what influences satisfaction with public services.
A health charity could summarise patient support conversations to detect common challenges facing newly diagnosed individuals.
A media organisation might use ChatGPT to understand the different ways audiences respond to specific stories.
In all these examples, ChatGPT acts as a sophisticated analysis tool. It learns nothing permanently about individual users and stores no private details. Instead, it identifies patterns, categorises information, and presents insights in a natural and understandable format.
Think of ChatGPT as a highly skilled analyst who can read a million lines of feedback in seconds—but has no memory of who said what once the job is done.
In the UK, personalisation is no longer a commercial luxury. It is becoming central to how organisations operate, allocate resources, prevent harm, and meet rising public expectations.
British citizens increasingly expect the convenience of private digital services from public institutions. When applied responsibly, user profiling can help councils, NHS trusts, and government departments understand what matters to different groups.
For example:
A transport authority might learn that younger commuters prioritise digital updates, while older residents value reliability and clear signage.
An NHS clinic might discover that appointment cancellations correlate more strongly with logistics than with patient motivation.
A job centre could identify which interventions are most effective for people experiencing long-term unemployment.
By translating sprawling datasets into actionable insights, AI can help overstretched public bodies serve people more effectively—with greater fairness and fewer assumptions.
From the high street to the fintech sector, British companies are under pressure to keep pace with changing consumer behaviour. ChatGPT helps them understand:
why customers abandon online baskets,
what drives loyalty,
how different audiences interpret messaging,
and which products meet emerging needs.
Well-targeted offerings reduce waste, lower costs, and allow smaller businesses to compete with tech giants that have long dominated algorithmic decision-making.
User profiling can also help identify:
harmful content,
grooming attempts,
extreme behaviour patterns,
misinformation networks,
and other risks.
ChatGPT can summarise flagged content, detect anomalies at scale, and support moderators without exposing them to traumatic material. Used wisely, AI can help platforms comply with the UK’s Online Safety Act while reducing the psychological burden on human reviewers.
From fraud prevention to public health monitoring, user profiling supports national preparedness. The ability to rapidly spot unusual trends—such as spikes in scam patterns or shifts in community sentiment—can offer early warning signals.
Of course, such uses require strict oversight, proportionate governance, and clear limits. But in moments of crisis, insight can be as vital as infrastructure.
ChatGPT is not the first tool that organisations have used for analysis. But it brings three transformative advantages: speed, accessibility, and context.
Traditional analysts are limited by time. ChatGPT can process millions of words in minutes, allowing organisations to:
spot emerging patterns before they become problems,
react in real time to public sentiment,
personalise experiences with unprecedented speed.
For time-sensitive sectors—such as retail, public safety, or customer services—this speed is invaluable.
One of ChatGPT’s most radical impacts is its democratisation of complexity. You do not need a PhD in data science to ask meaningful questions. Anyone in an organisation—from frontline staff to senior leaders—can obtain insights with natural language prompts.
This accessibility means:
more voices contribute to decisions,
fewer insights are trapped within specialist silos,
and more organisations (especially SMEs and charities) gain access to high-quality analysis.
Unlike traditional analytics tools, ChatGPT understands nuance. It can:
interpret tone,
detect emotions,
compare across groups,
identify contradictions,
and summarise meaning rather than merely counting words.
For example, a thousand residents saying “the bus service is fine, but always late” is very different from a thousand residents saying “the bus service is always late, but otherwise fine.” Statistical sentiment tools might score these similarly. ChatGPT does not. It grasps intent, priority, and underlying themes.
Across Britain, early adopters span every sector. Some applications are widely known; others operate quietly in the background.
Major retailers use ChatGPT to analyse:
purchase journeys,
social media comments,
chatbot logs,
in-store feedback.
This helps them improve stock decisions, reduce returns, and tailor experiences to different communities—from London to Leeds.
Banks and fintech organisations use AI to:
detect unusual behaviour,
assess risk,
personalise financial advice (under regulatory guardrails),
support vulnerable customers.
Profiling helps spot patterns such as loan applicants misunderstanding terms or customers struggling with cost-of-living pressures.
British universities analyse:
student concerns,
learning behaviours,
support requests,
academic performance signals.
ChatGPT helps identify who may need early-intervention support, ensuring pastoral teams can focus attention where it matters most.
Health organisations leverage AI to:
understand patient experiences,
detect unmet needs,
synthesise staff feedback,
support complex case management.
Charities similarly use AI to tailor advice services or to improve volunteer support.
Journalists and editors increasingly rely on AI to understand:
what stories engage different audiences,
how headlines perform,
which topics generate confusion,
and how public sentiment shifts day-to-day.
This allows media outlets to produce clearer, more responsible reporting.
While the benefits are considerable, AI-assisted profiling raises legitimate concerns. These must be acknowledged—openly and honestly—before Britain can move toward responsible governance.
AI can reproduce or amplify existing societal inequities. If an organisation’s data reflects unequal service delivery, ChatGPT may inadvertently mirror those patterns in its analysis.
This is not a failure of the model alone; it is a failure of oversight.
Personalisation can become manipulation if not carefully bounded. Predictive insights could shape:
pricing,
political messaging,
or public service decisions.
While targeted support can be beneficial, excessively granular profiling risks reinforcing echo chambers or penalising certain groups.
Even when data is anonymised or ethically collected, public trust can be fragile. Britons value privacy deeply. There is a fine line between helpful tailoring and uncomfortable surveillance.
Clear communication about how data is used—and what boundaries exist—is essential.
If organisations rely too heavily on AI-generated insights, they may overlook:
human judgement,
context,
emotional understanding,
or lived experience.
AI should inform decisions, not replace them.
To harness benefits while minimising harms, Britain should adopt the following guiding principles.
Only use data that is necessary, proportionate, and relevant. More data does not always mean better outcomes.
People should understand:
what data organisations use,
why it is used,
how it benefits them,
and where limits exist.
Opacity breeds mistrust.
AI should support human expertise, not supersede it. Decisions affecting rights, access, or wellbeing must always involve human judgement.
Organisations must test for:
bias,
unintended consequences,
and group-level disparities.
Corrective strategies should be embedded from the outset.
Those who deploy AI—not the models themselves—are responsible for outcomes. Clear lines of governance and audit trails should be mandatory.
Britons must have a voice in shaping AI-driven systems. Public dialogue, community engagement, and informed consent are not optional extras.
Looking ahead, three major shifts are likely to shape Britain’s AI landscape.
AI insights will no longer sit in isolated systems. Retail, healthcare, education, and public services will increasingly share patterns (with proper safeguards) to understand societal needs holistically.
Imagine:
tailored NHS self-care guidance,
customised education pathways,
local government services that anticipate resident needs,
job-centre support aligned with personal motivations.
These are within reach—if implemented responsibly.
The UK will continue moving toward a more adaptive, principles-based regulatory model for AI. User profiling will be a priority area, combining:
privacy protections,
impact assessments,
sector-specific rules,
and cross-government coordination.
Britain has an opportunity to become a global leader in ethical AI governance.
ChatGPT is transforming user profiling across the UK with unprecedented speed. But its real power does not lie in automation alone—it lies in enabling better human decisions.
If we approach AI with clear principles, democratic values, and a commitment to fairness, Britain can harness this technology to:
strengthen public services,
empower individuals,
support businesses,
enhance safety,
and build a healthier digital society.
But if we neglect oversight—or treat AI as a technological inevitability rather than a choice—we risk undermining the very trust on which our social fabric depends.
User profiling is neither inherently good nor inherently bad. Like any powerful tool, its impact depends entirely on how we choose to wield it.
The future of AI in Britain will be shaped not only by engineers and policymakers, but by the expectations, values, and voices of every citizen who demands technology that works for society, not merely on society.
In this crucial moment, it is our responsibility—as academics, policymakers, business leaders, and everyday users—to steer ChatGPT-assisted profiling toward a transparent, fair, and human-centred future.
