Why Value Propositions Matter
A value proposition is more than a slogan. It’s a promise that keeps a team focused on solving a specific user problem. Once a team understands exactly what problem it is solving, it can build the journey around that goal — prioritizing features that deliver the promised benefit and setting aside those that don’t.
This focused approach is how many successful products began. Dropbox launched as a service that simply stored files in the cloud. Instagram initially let users upload photos and add filters. Uber started by connecting riders with luxury cars in San Francisco. Each product focused on doing one thing exceptionally well before expanding to additional features.
This focus also makes it easier to market a product. Instead of forcing potential users to figure out why a tool might be useful, a clear value proposition communicates that upfront. When users can quickly see how a product fits into their workflow, adoption becomes much more likely.
The “What,” Not the “How”
Strong value propositions are always about what the product helps users achieve — not the technologies or methods behind it. Statements like “accelerate your research to make decisions more quickly,” “save time by skipping lines,” or “never miss a bill payment again” describe specific outcomes.
In contrast, vague claims such as “redesigned UI that’s easier to use,” “ten new features,” or “more powerful than ever” leave the burden on users to figure out why those things matter. The same problem arises when teams lead with technology: a product’s technical makeup is not, by itself, a reason for someone to use it.
Why “Powered by AI” Falls Short
In today’s market, many stakeholders and investors are urging teams to integrate generative AI. But when “powered by AI” becomes the most prominent part of a product’s pitch, users are left to make their own leap about why that matters.
Unlike a clear value proposition, “powered by AI” could mean almost anything — from drafting emails to generating images or summarizing data. Without explicit guidance, users must figure out how to fit these capabilities into their own workflows. This added cognitive load reduces the likelihood that they will give the product a serious try.
Research by Mesur Cicek, Dogan Gursoy, and Lu Lu further shows that simply labeling a product as AI‑driven can trigger anxiety or skepticism. Many users now know the downsides of large language models and worry about accuracy, privacy, or authenticity.
Grammarly’s approach illustrates how to overcome this barrier. Rather than selling itself as “an AI writing tool,” Grammarly promises something concrete: helping you find the words you need and get your point across while maintaining your voice. That message addresses common concerns about AI-generated content, such as sounding impersonal or being easily detected.
What Happens When Teams Lose Focus
AI is a broad, flexible technology, capable of performing many different tasks. Without a clear value proposition, product teams may try to showcase as many of these capabilities as possible. In practice, this often results in a generic chatbot or a grab‑bag of features that feel disconnected from any particular user goal.
The result is rarely satisfying. Users who are looking for a specific solution encounter an unfocused product. Teams that chase “AI for AI’s sake” often struggle to explain what their tool actually does.
In contrast, teams anchored by a clear value proposition can integrate AI only where it genuinely supports the user journey. They can leave out unnecessary features and refine those that matter most. This leads to products that are simpler to describe, easier to adopt, and more likely to retain users over time.
The Stakes for B2B Products
The temptation to treat AI as a selling point is strong in the B2B space as well. Business leaders may invest in AI features to appear cutting‑edge, even when the features do not address specific workflow needs. However, this approach rarely leads to long‑term success.
Teams that begin with a user-centered value proposition can choose the type of AI integration that actually solves a problem. A product that offers clear, tangible benefits — beyond just being AI‑enabled — is far more likely to maintain customer relationships after the initial excitement wears off.
A Better Path Forward
AI can play a powerful role in product design, but it is not a value proposition on its own. Teams should start by identifying the user problem they want to solve and then determine whether AI is the right tool to help.
By focusing on the what rather than the how, teams can design products that resonate with users, clearly communicate their benefits, and build lasting engagement — without relying on buzzwords like “powered by AI” to do the heavy lifting.
