We hear it all the time: ChatGPT is changing search. But what does that actually mean in practice? For me, it’s not just a headline — it’s my reality. And when you zoom out, I believe it’s the beginning of a new distribution network that could reshape discovery and commerce as we know it.
We’ve all been there: ten open tabs, each claiming to have the “top 10 best” products. Every list looks the same, padded with affiliate links, designed to optimise clicks more than serve the reader.
That was fine at first, but over the years digital discovery has become noisy, transactional, and frankly exhausting.
What makes this experience especially draining is decision fatigue. Traditional search doesn’t just surface information; it forces the user to evaluate, compare, and reconcile conflicting claims across multiple sources.
The real burden isn’t the lack of information — it’s the burden of synthesis. Users are expected to read between the lines, discount bias, weigh trade-offs, and arrive at a decision on their own. AI-driven discovery shifts that work away from the user, turning scattered inputs into a coherent, contextualised answer.
Lately I’ve been skipping that grind. Instead of opening a browser, I just start a conversation with ChatGPT.
If I’m looking for running shoes, cycling gear, or even a sleep mask, I don’t ask a vague “What’s the best?” I give ChatGPT clear instructions: don’t trust affiliate-heavy sites, compare materials and durability, show me the trade-offs between budget and premium options.
What I get back feels different: a tailored, unbiased recommendation that cuts through the noise. It’s like moving from reading ads to having a candid conversation with a trusted advisor.
What builds trust in this model isn’t just better answers — it’s context. Instead of isolated facts, the response reflects my constraints, preferences, and priorities, which dramatically shortens the path from consideration to decision.
Over time, the interaction feels less like querying a tool and more like working with a discovery partner. Each follow-up refines the recommendation, creating a two-way learning loop where the system adapts to how I think, not just what I ask.
This shift is about more than answers — it’s about how discovery happens.
Instead of search → click → scan → doubt, my journey looks like ask → refine → decide.
Trust emerges because conversational discovery delivers context, not just facts. By framing options within constraints, trade-offs, and intent, AI reduces uncertainty and speeds up decision-making without requiring the user to cross-check multiple sources.
In this model, AI functions less like a results page and more like a discovery partner. Each follow-up question sharpens understanding, creating a two-way interaction where recommendations improve through dialogue rather than repetition.
What feels personal today is already being scaled. OpenAI has added shopping features to ChatGPT, providing recommendations, images, prices, and review snippets directly in the chat (TechCrunch, April 2025). They’ve also said neutrality is a design choice: results aren’t influenced by ads or affiliate deals, in order to preserve trust.
And payments are coming. Reports suggest OpenAI is working on in-chat checkout with Shopify, which would allow people to move seamlessly from curiosity to comparison to purchase, all inside the same interface (Reuters, July 2025).
Conversational discovery still starts with intent. You ask, the AI responds. The next shift is discovery without a query.
AI is moving from a pull model to a push model. It uses prior context to surface relevant options proactively, based on preferences and past conversations rather than keywords.
For example, if a user regularly discusses running, the AI may surface new shoe releases or comparisons aligned with those interests, without any search action.
Discovery becomes continuous and context-driven. The search bar becomes secondary, and relevance comes from understanding rather than query volume.
If you step back, the implications are massive.
The last era of digital distribution was built on attention and clicks — Google’s search dominance, Facebook’s social graph. The next moat will be built on context and memory, which is exactly where AI platforms like ChatGPT excel.
Here’s the question I keep coming back to:
For users like me, the future already looks different. I don’t just search — I ask. And when I ask, I expect clarity, context, and trust.
For brands, the challenge is existential. The ones who adapt early — by focusing on transparency, product quality, and conversational discoverability — will be the ones who thrive when prompts become the new gateway to discovery.
This isn’t just a tweak to search engines. It’s the foundation of a new distribution era. We’re moving from a world optimised for algorithms and clicks to one optimised for conversations and trust.
And the shift isn’t abstract — it’s already happening in my daily life. The real question is: how ready are we for the search of tomorrow?
Trust comes from synthesis, not volume. AI reduces decision fatigue by combining context, constraints, and trade-offs into a single response. Instead of forcing users to evaluate multiple biased sources, it provides a reasoned answer aligned to intent, which increases confidence and speeds decisions.
Neutrality removes incentives tied to ads, affiliate rankings, or paid placement. Recommendations are based on relevance, quality signals, and user-stated preferences rather than commercial influence. This shifts visibility away from who pays the most and toward who best fits the context of the request.
Conversational discovery will not fully replace keyword search, but it will reduce its dominance. Keyword search remains useful for broad exploration and navigational queries. For comparison, evaluation, and decision-making, conversational interfaces are becoming the primary entry point.
The difference is context and control. Helpful suggestions are grounded in prior intent, timing, and relevance, while spam ignores user signals and prioritises volume. Effective push discovery requires transparency, opt-in behavior, and clear boundaries to maintain trust.
Craig Parker is a Product Manager at RealityMine, where he leads the development of mobile app and web measurement solutions. With over a decade of experience spanning project delivery, UX optimisation, and data-driven SaaS products, Craig specialises in turning behavioural insights into strategic value. He’s especially interested in how emerging technologies like AI are reshaping user journeys across the app ecosystem.
