AI feature adoptionBy Lindsey J
Why nobody is using your new AI feature
AI feature adoption is the real bottleneck: why shipping AI features outpaces real use and value, plus a five-question AI feature adoption check for any product team.
5 min read
AI product strategy
AI product strategy
The fastest teams decide with evidence, not opinions. We instrument products with tools like Pendo and run AI-assisted experimentation, turning real user behavior into a continuous loop of what to build, test, and sharpen next.
Teams we have worked with
Why do product teams need evidence before adding AI?
AI makes features cheap to ship, so the hard part moves to choosing which ones deserve to exist. Teams that decide by opinion ship AI features nobody uses. Teams that measure real behavior can see which features earn their place, and cut the rest before they cost more.
What do we set up?
#01
Product analytics
instrumentation with tools like Pendo, tied to a metric your business already reports.
#02
Dashboards and funnels
KPI reporting your team actually reads.
#03
Feedback loops
NPS, surveys and structured feedback from the people using the product.
#04
Experiments
AI-assisted experimentation and optimization cycles, so each change is tested against real use.
How does AI help decide the roadmap?
We use AI where it is strong: sorting feedback at volume, finding patterns across usage data and drafting options to test. People still decide. Every prioritization call ties back to a number, so the roadmap can be argued with evidence.
What if we already shipped an AI feature nobody uses?
That is a common starting point. Our AI feature adoption work finds why a capable feature goes unused and redesigns the experience around it, measured on trial, first-use success and repeat use.
The engagement
What do you get?
Who is this for?
Product leaders at software companies who are adding AI to the product and need evidence, not opinions, to decide what to build, test and cut next.
- AI integration into product workflows and strategy
- Product analytics setup and instrumentation (Pendo)
- KPI dashboards, funnels, and reporting
- NPS, surveys, and structured feedback loops
- AI-assisted roadmap prioritization and feature validation
- AI-assisted experimentation and optimization cycles
Solutions
Related services
Brand strategy for people and machines
Your brand now has to resonate with people and register with machines. We build the operational skills and AI workflows that carry your brand consistently through every touchpoint, from your product and site to social and AI answer engines.
AI-accelerated UX and UI design
Pixels are commoditized. Brand-fluent, accessible systems aren't. Your team can ship the next screen. Keeping your fiftieth screen on-brand, on-pattern and on-business-logic is a different problem: design system governance, the discipline most internal teams haven't built yet. We've been designing since 2014, and we pair that experience with AI for what AI does well: parallel exploration, deep research and system-wide consistency. You get AI speed plus the discipline AI can't generate on its own.
Website design and development, built for AI search
We design and build websites on a modern content management system, written and structured so search engines and AI assistants can read, trust and cite them. Every site is built to be run after launch, by your team or by agentic web management.
Agent-ready design systems
Agents now build from your design system, and they bring none of your team's context. We engineer and audit systems with machine-readable metadata and explicit anti-patterns, using Figma MCP, Cursor, and Claude, so agents stay on-brand and on-system while your team ships faster.
Further reading
Field Notes
AI product strategyBy Lindsey J
When every product has AI, what actually makes yours different?
6 min read
Got questions?
Frequently asked questions
What is AI product strategy?
It is deciding what to build with AI based on evidence: product analytics, user feedback and AI-assisted experiments, connected to a metric your business already reports.
Which analytics tools do you use?
We set up product analytics with tools like Pendo, plus KPI dashboards, funnels, NPS and surveys.
How is this different from AI feature adoption?
AI product strategy decides what to build. AI feature adoption fixes a feature that already shipped and is not being used.
Make your product agent-ready
We design the products, websites and design systems your customers use and their AI agents act on.