In the space between your screen and a purchase lies an invisible persuader. In 2025, that persuader is increasingly powered by conversational artificial intelligence — tools like ChatGPT. As a British economist observing market and behavioural shifts, I believe we are at a pivotal moment in the evolution of advertising and consumer decision making. This article explores how ChatGPT (and similar models) can — and will — reshape how goods and services are marketed, how consumers process adverts, and how the balance of power may shift among firms, platforms, and buyers.
This is not a piece of technophilic hype, nor a dystopian warning. Instead, it is a grounded exploration for general UK readers, asking: how will ChatGPT influence the adverts we see, the decisions we make, and the transparency and ethics of persuasion? The stakes are high: both for businesses seeking competitive edge, and for citizens navigating an increasingly invisible digital marketplace.
Historically, adverts have been visual or textual push messages — banners, pop-ups, sponsored posts, search engine ads. These are broadcast or ambient. What ChatGPT brings is interactivity: the ability for an ad to act like a conversation. Instead of static text, imagine your browser or app offering:
“Hi, looking for running shoes? Tell me how you plan to use them — I can help pick.”
That shifts the ad from interruption to engagement, akin to a helpful assistant. Because ChatGPT can parse your preferences and feedback in real time, the resulting message is more tailored, more persuasive, and more adaptive than before.
Several advances converge to make this moment possible:
Large language model (LLM) maturity: These models now generate fluent, context-aware responses.
Ubiquity of chat interfaces: Many platforms incorporate “chat plugin” features, making conversational agents accessible.
Data on users: Firms already hold deep data about preferences, search history, purchase legacies — enabling richer context for conversation.
APIs and integration: Advertising platforms are beginning to integrate LLM APIs, enabling dynamic ad generation on demand.
Yet constraints remain: latency, costs, fairness and bias, regulatory boundaries (e.g. data privacy laws), and detection or “ad blindness” strategies by users.
Conversational AI can affect consumer decision making in several distinct ways. Some are extensions of existing advertising logic; others are novel pathways.
Personalisation is not new: digital ads for years leveraged demographic, behavioural, and contextual targeting. ChatGPT, however, allows conversational personalisation. Instead of merely adjusting which ad a user sees, it can adapt tone, focus, arguments, and even persuasive logic based on immediate signals.
For instance:
If a user expresses sustainability concerns, the AI can highlight eco-friendly features.
If the user is budget sensitive, it can emphasise discounts or value propositions.
If the user is uncertain, it can pose clarifying questions (“What matters more: battery life or weight?”) to surface latent preferences.
This reduces the cognitive “distance” between user wants and product framing.
Chatbots can engage in nudges or framing within the conversation itself. For example:
“Most customers buying this supplement also considered the premium brand. I find you are halfway between those — would you like to see the benefit comparison?”
Such conversational anchors — “most customers did X” — are well documented in behavioural economics as influence tools. The conversational medium makes them more subtle and interwoven with perceived advice.
One pain point in digital ads is user friction: doubts, uncertainties, objections (e.g. “Is this safe? Is the quality good?”). ChatGPT can serve as a dynamic objection handler, responding to user questions in context and pacing the persuasion. This is akin to a salesperson guiding a hesitant consumer through concerns, but automated.
Because ChatGPT can adjust narratives, metaphors, and examples on the fly, it can weave mini-stories tailored to you. For example, a wine ad might ask:
“Do you prefer bold reds or delicate whites? I’ll tell you a short story of a friend’s dinner choice last week that matches your taste.”
These micro-stories can create emotional resonance and cognitive salience, making the product more memorable.
One virtue of software is measurement and iteration. ChatGPT-driven ads can A/B test dialogues, measure drop-off points, refine persuasive steps, and loop back to better versions. Over time, the "conversation paths" that lead to conversions become optimized. The AI learns which turning points matter most to users, and which conversational styles backfire.
These shifts carry profound implications for how ad firms, platforms, agencies, and brands operate.
If conversational ads replace (or supplement heavily) static creatives, agencies must evolve. Traditional roles (copywriting, static design) will be complemented (or supplanted) by conversation designers, AI prompt engineers, and behavioural psychologists who craft dialogue flows.
Brands that cling to legacy ad formats risk losing effectiveness. The pressure to embed conversational layers will rise.
Big platforms (Google, Meta, Amazon) that control ad infrastructure may integrate ChatGPT layers into their systems. They can embed “conversational overlays” over search, recommendation, social feed, or shopping interfaces. Those who sit at the interface between user and ad — platforms — may gain even more control of persuasive narratives and metrics.
Smaller brands or publishers may then depend on platform permission to use conversational extensions, raising concerns about gatekeeping, fees, or algorithmic favouritism.
Conversational AI is data hungry: to talk well, it needs context. This intensifies the tradeoff between personalization and privacy. Firms will jockey for more signals (preferences, history, device data) to power more convincing dialogues.
Regulators (e.g. the UK Information Commissioner’s Office, EU’s GDPR) may step in, restricting what can be done in conversational targeting. Firms with better compliance, or with first-party data advantages, may gain relative strength.
Advertising may increasingly be viewed as not just "message plus placement" but "conversation design plus timing plus interface." That means a new vertical: conversation as a service (CaaS). Some specialist firms will build, host, manage chat ad layers for brands, optimizing dialogue modules, user branching, tone calibration, fallback error handling, and analytics.
Conversation ads change the shape of attribution. If a user interacts via dialogue across sessions, attributing the “touchpoint” becomes more complex. Unlike a click or impression, conversations have states, branching paths, and multi-session continuity. Firms will need new tracking, modelling, and reporting systems to capture conversational influence. Biases and overfitting remain risks.
What does this mean for you — the buyer, the citizen in the UK — navigating this new advertising landscape?
You may well see adverts or chat interfaces that feel genuinely helpful. A motor insurance firm might chat: “Would you like me to compare quotes based on your actual driving habits?” These helpful overtures, though, carry persuasive weight. The boundary between help and push is thinner in conversational form.
Thus, while utility may improve (less irrelevant adverts), the intensity of persuasion rises. You might be nudged in directions you did not consciously plan, without overt awareness.
Part of purchasing friction (searching, comparing, reading reviews) serves a deliberative function: to protect you from impulse. Conversational AI reduces friction, doing work on your behalf. That is convenient — but also risks eroding your agency. If a persuasive conversation path leads you efficiently to the “designer brand,” you might not pause to reflect on quality, cost, or alternatives you would otherwise have considered.
If the AI conversational ad tailors only what you usually respond to, you risk narrower exposure. The ad system’s incentives push toward reinforcing prior preferences, not challenging them. This can create echo chambers in consumption — less exploration, fewer surprises.
One challenge is that users may not always be aware that they are in a “paid conversational ad” rather than a neutral assistant. If not disclosed clearly, these “chat ads” could mislead. Trust will depend on how transparently platforms label and enforce boundaries between brand-sponsored AI chat and neutral services.
Furthermore, if the underlying model hallucinates or misstates facts, that adds risk. Consumers may be misled by persuasive but false claims. The possibility of bias or manipulative framing becomes more salient in conversational form.
Consumers may develop resistance: muting or opting out of conversational ads, installing blockers, or demanding “no chat” modes. We may see settings like “allow only static ads, no chat overlay,” or browser policies to disable upstream chat interfaces.
Just as ad-blocking rose against static ads, there is room for “chat ad blocking” or regulatory backlash — especially if conversational persuasion is deemed too opaque or manipulative.
Let’s sketch some realistic scenarios to illustrate how ChatGPT might be used (or misused) in advertising to UK consumers.
Imagine you're browsing an online bookstore. A chat window pops up:
“Hi — are you looking for historical fiction or non-fiction today? I noticed you read some Winston Churchill biographies. I can recommend two new titles you’d enjoy, and apply a 10 % discount.”
You reply you like Churchill and also modern history. The chat then draws on your prior purchases, suggests cross-genre picks, averts objections (e.g. “Do you already own this?”), and finalises a purchase — all within the chat flow.
That upsell via dialogue is more frictionless than navigating static pages and links.
You visit a car insurance site. Rather than a long form, the site says: “Let’s chat — I’ll guide you step by step.” Through the chat you enter driving history, expected mileage, optional extras. But along the way:
It floats insurance “bundles” tailored to your needs
It says “Customers like you also added breakdown cover”
It asks nuanced clarifiers (“Is your car mainly for urban or rural driving?”)
It optimises the flow to reduce abandonment
Compared to form-based quotes, conversational quoting may reduce drop-off, increase conversion, and channel you toward profitable add-ons.
Suppose you interact with a hotel website chat:
“Are you travelling for business or leisure? Are you interested in a spa, gym, or local excursions? Based on that, I’ll show you room types, package blends, and limited-time deals.”
This chat advice might steer you toward package options that yield higher margins — but presented as helpful guidance.
A news website or streaming service could use ChatGPT to offer customised bundles:
“I see you read politics and science. Would you prefer a ‘Science & Policy’ bundle or the ‘Full Access’ plan? I can run through a side-by-side cost benefit in a minute, based on your reading habits.”
By tailoring messaging and steering suggestions conversationally, subscription uptake can rise.
Local businesses — e.g. plumber, florist, clinic — might embed chat in their sites:
“Need a plumber for a leak? Tell me when and where. I’ll compare two quotes and help schedule.”
This reduces the barrier for contacting, quoting, and booking — turning “interest” into action faster.
As an economist, I must examine not just what’s possible, but who gains, who loses, and what norms or regulations may be needed.
On one hand, conversational ads can improve matching — better aligning offers with consumer preferences, reducing wasteful ad impressions, and lowering marketing costs. That is an efficiency gain.
On the other hand, when persuasion becomes that seamless, the risk of manipulation increases. The line between helpful recommendation and coercive nudge becomes blurred. Stronger regulation may be needed to protect vulnerable consumers, particularly in sectors like finance, health, or gambling.
Platforms controlling the conversational AI layer may accrue disproportionate influence. A few “chat ad intermediaries” could emerge, creating bottlenecks. This intensifies concern over market power, gatekeeping, and platform fees.
Brands with rich first-party data (like Amazon, Tesco, major banks) will have advantages in tailoring conversational persuasion. Smaller firms might be locked out or forced into dependency.
Economic welfare analyses must ask: does the consumer gain more surplus (because they find better matches) or does the advertiser capture more surplus (by persuading the user more effectively)? It likely depends on market structure, transparency, and regulation. Without safeguards, surplus capture could dominate.
Regulators may need to establish guidelines such as:
Required labels: “This is a brand-sponsored conversational ad.”
Limits on persuasive tactics: e.g. banning anchoring or scarcity claims that mislead.
Audits of AI persuasion flows — checking for bias, undue influence, or disallowed claims.
Rights of opt-out: users should be able to avoid conversational formats if desired.
Privacy rule enforcement around data use in real time.
In the UK and EU, existing consumer protection, advertisement standards, and data laws will need adaption. The Advertising Standards Authority (ASA) will likely intervene to assess whether conversational ads comply with fairness, truthfulness, and clarity.
Conversational models risk perpetuating bias: recommending certain products more heavily to certain demographics, or subtly framing offers differentially. Ensuring fairness — that comparable consumers see comparable persuasive opportunities — is a design challenge. Transparency, auditing, and accountability mechanisms become essential.
No technology transforms reality instantly or smoothly. Many obstacles and uncertainties lie ahead.
ChatGPT sometimes hallucinates or fabricates. That creates risk: if a conversational ad misstates specs, misquotes price, or misleads, regulatory or reputational fallout may occur. Ensuring guardrails, fallback rules, and human oversight is critical.
Users may tire of persistent chat overtures. If every site prompts you to chat, the novelty may wear off. Some users will prefer brute-force browsing. Balancing helpful conversations and intrusion is tricky.
Brands and platforms must coordinate on technical standards: interoperable APIs, conversation markup languages, analytics formats. Without standardisation, fragmentation or vendor lock-in may limit adoption.
If consumers feel manipulated or deceived, backlash can ensue. People may disable chat features, demand regulation, or boycott. Trust is fragile — overstepping persuasive boundaries may provoke rejection.
Lawmakers move slowly. Conversational persuasion may outpace regulation, creating an interim period of “wild west” experimentation. Some actors may exploit loopholes, risking erosion of public trust.
Even the smartest chat persuasion is constrained by the underlying value of product and user preferences. If your product is inferior or misaligned, no clever dialogue will accomplish sustained success. Overreliance on persuasion may distract firms from product quality, pricing, or fulfillment fundamentals.
To navigate the coming transformation, I offer some strategic guidance to different parties.
Start experimenting now: Set up pilot conversational ad campaigns, preferably in controlled environments, to learn what works or fails.
Hire dialogue designers: Bring in experts (behavioural science, conversation UX) to craft flows, tone, fallback logic, and objection handling.
Run ethical audits: Monitor whether conversations drift into undue influence or misleading framing.
Build first-party data: Since third-party targeting may weaken, building direct customer relationships and data becomes more valuable.
Expose human fallback: In tricky cases, allow escalation to human agents to preserve trust.
Offer opt-outs: Give users an option: “No chat, show regular ads only.”
Provide transparent APIs: Allow brands controlled, fair access to chat ad layers without hidden biases.
Moderation and standards enforcement: Enforce advertising rules and disclosures within conversations.
Metrics and attribution tools: Develop measurement frameworks suited to chat flows, multi-step paths, and cross-session influence.
Protect user privacy: Enforce data minimisation, consent, and anonymisation in real-time messaging.
Clarify disclosure rules: Mandate that conversational ads be clearly labelled, and that users know when they’re in a promotional chat.
Create oversight bodies: Auditors may examine persuasive flows for fairness, bias, and misrepresentation.
Adapt consumer law: Update rules on misleading advertising to cover dialogues and interactive flows.
Support consumer literacy: Fund public campaigns to help users recognize conversational persuasion.
Enable opt-out rights: Guarantee users ability to disable conversational advertising if desired.
Be aware of persuasive chat: When interacting with chat agents, ask: is this a brand ad or a neutral assistant?
Pause and reflect: If the conversation feels too smooth, take a moment to compare alternatives independently.
Use opt-out tools: Preference settings or browser tools to disable chat ads may become available — use them.
Demand transparency: Complaints and feedback to regulators, firms, and media help set norms.
“The medium is the message,” Marshall McLuhan famously said. In this case, the conversational medium is the message. ChatGPT and similar models are building a new interface between consumers and advertisers — one that blends persuasion, service, and narrative. This evolution has the potential to uplift consumer experience through smarter matching, reduced waste, and more intelligent engagement. But it also carries risks of subtle manipulation, concentration of power, and opaque persuasion.
As a British economist, I see this as a turning point for digital markets. The actors who master the “conversation layer” will gain outsized advantage. Regulators must catch up. And consumers must remain vigilant about maintaining their autonomy.
For now, the best path is cautious experimentation, ethical guardrails, and public scrutiny. In a few years, you may well find yourself buying many goods, services, and subscriptions via conversation — not browsing links. The question is: Will that conversation serve you, or serve someone else’s persuasive aims?
In the end, the realignment of advertising and consumer decision making is not a distant science fiction — it is unfolding now. And its consequences will ripple through businesses, markets, and everyday buying life. May the conversation be transparent, fair, and in your control.
