For the last year, a lot of companies rushed to add AI features.
A chatbot here. A summary tool there. Maybe a little automation layered on top.
But that phase is getting old fast.
What’s trending now is something deeper: AI-native products — products where AI is not an add-on, but part of the core workflow itself. You can see that shift in the market already: OpenAI’s Frontier is focused on helping enterprises build and manage AI agents that do real work across business systems, and major software vendors like Oracle are redesigning enterprise apps around agentic workflows rather than isolated AI features.
That matters because users do not really care whether a product “has AI.”
They care whether it:
saves time
reduces manual effort
fits into existing workflows
feels reliable enough to trust
That is the difference between an AI demo and an AI-native product.
And honestly, that’s where I think the next serious winners will come from, who intelligently will be getting partnered with AI-native development services.
Question: Do you think most companies are building real AI-native products yet or still just shipping AI-flavored features?
Koharune Airi
Nuriekawaiiの創設者
Most companies haven't answered a basic question yet: who is accountable when an AI agent takes an action? Until that's resolved, they'll keep defaulting to safe, surface-level AI features instead of truly rethinking workflows. The bottleneck isn't the technology; it's the accountability layer nobody wants to own.
Most companies are still in the “AI-flavored features” stage rather than building truly AI-native products. Adding chatbots or automation layers is easier and quicker than redesigning products around AI from the ground up. AI-native products require rethinking workflows, data architecture, and user experience with AI at the core not just as an add-on. That said, we’re starting to see a shift as companies realize that real competitive advantage comes from deeply integrated AI capabilities, not surface-level features. The transition is happening, but it’s still early for most organizations.
The frontend side of this doesn't get enough attention. Building UI for AI-native products is a different problem than CRUD. You're dealing with response times you can't predict, outputs that arrive mid-stream, and failures that don't look the same twice. A loading spinner and a try/catch don't cut it.
Most teams are still reaching for the same patterns they'd use for a form submission. It works until users start feeling the difference and they do feel it.
React Suspense + streaming in the Next.js App Router is the first thing I've reached for that actually matches how AI responses behave. You stop thinking about how long to wait and start describing what to show while waiting. The stream decides when things appear. Small shift in how you write the component, noticeable shift in how it feels to use. The teams getting this right aren't the ones with the nicest chat UI. They're the ones who questioned where their component boundaries sit before they wrote a single line.
I think most companies are still in the “AI-flavored features” phase, not truly AI-native yet.
Adding a chatbot or a quick automation is fast and looks good in demos, but building AI into the core workflow is much harder. It requires redesigning processes, handling reliability, and actually trusting AI to do meaningful work not just assist.
That said, the shift is definitely happening. The companies that are winning are the ones focusing less on “adding AI” and more on solving real problems like saving time and reducing manual effort.
Right now it feels like:
70–80% = AI as an add-on 20–30% = moving toward AI-native
But over the next few years, that balance will flip. The real winners will be those who treat AI as infrastructure, not a feature.
Most are still shipping “AI add-ons.” The real shift happens when the whole workflow disappears into one action — that’s when users actually feel the value.
Most companies are still in the AI flavored features phase it's easier to layer ai on top than to rethink the entire workflow AI-native products require deeper changes data flow, decision-making logic, and user experience all built around AI from the ground up. That shift takes time, which is why only a few players are getting it right so far.
Spot on. The 'AI as a feature' phase is definitely hitting a ceiling. I’ve been following the same shift in the QA world recently. Most legacy tools are just adding a GPT-wrapper to 'generate a test case,' which is just a feature.
But the real winners are those moving toward AI-native orchestration—where the system doesn't just write a script but autonomously manages the execution layer and heals itself. I was just reading a deep dive on how ai in software testing https://testomat.io/blog/ai-in-software-testing/ is moving toward this 'agentic' workflow where the product IS the automation engine, not just a UI with a chatbot.
It's exactly as Archit said above: the mental model shift from 'AI as a feature' to 'AI as architecture' is the real unlock for ROI.
I think the key distinction isn’t just “AI-native vs AI features” — it’s workflow-native vs feature-native.
Most products today still treat AI as a step in the UI. AI-native products treat it as part of the execution layer of the system.
That’s a fundamentally different architecture:
We’re still early — most companies are shipping features, not redesigning workflows.
Most companies are still adding AI features rather than building truly AI-native products where AI is the core workflow, not an add-on.
Honestly, it’s a bit of both. In my point of View AI definitely makes me faster and more productive & it helps with boilerplate, debugging, and even learning new concepts quickly. But at the same time, it can create a subtle anxiety, like questioning whether I’m truly improving my skills or just relying too much on assistance. I think the key is using AI as a tool to enhance understanding, not replace it that way, it builds confidence instead of dependency.
This is exactly the shift I'm seeing with my automation clients. The ones getting real ROI aren't bolting a chatbot onto an existing workflow — they're redesigning the workflow entirely around what AI makes possible. For example, instead of adding AI to manually review invoices, we built a system where the invoice processing pipeline is AI-native from intake to reconciliation. The mental model shift from "AI as feature" to "AI as architecture" is the unlock. The challenge is that most orgs still have teams structured around the old workflow, so the reorg is harder than the tech.
I think most companies are still shipping AI-flavored features, not true AI-native products.
We’re in a transition phase—some are moving toward workflow-level integration, but very few have fully rethought their product around AI.
The main blockers aren’t just tech, but also mindset and legacy systems.
The real shift will happen when companies start building for outcomes, not features.
Totally agree! The biggest shift is toward AI-native products—solutions designed around AI from the start, not just apps with “AI features” tacked on. These products change how we work and solve problems, rather than just adding small enhancements. That’s where the real impact lies.
100% agree — most companies are still in the "sprinkle AI on top" phase. The real shift happens when the product literally cannot exist without AI at its core. I'm seeing this firsthand building automation systems: the clients who get the most value aren't adding chatbots to existing workflows — they're rethinking the entire process around what AI agents can do. For example, instead of "add AI to our invoice matching," it becomes "build an agent that handles the entire accounts payable pipeline end-to-end." The product IS the agent. That's the AI-native difference. I think the biggest opportunity right now is in vertical AI-native products for specific industries like manufacturing, textiles, and agriculture — industries where the workflows are manual enough that AI-native solutions feel like magic.
Great insight, I completely agree that the shift toward AI-native products is becoming more obvious. Simply adding AI features feels superficial if it doesn’t truly integrate into the core workflow. What stands out to me is how users are no longer impressed by the presence of AI itself, but by how seamlessly it improves efficiency and reduces friction. The real value comes when AI becomes invisible just a natural part of getting things done. Curious to see how many companies can actually make that transition, since it requires rethinking products from the ground up, not just layering AI on top.