Your AI fails because
users can't use it.
87% of AI implementations fail to meet adoption targets. Your teams don't use it because it was built for data scientists, not daily users. We bridge that gap through proven UX methodology.
You're not alone in this adoption crisis
Every enterprise faces the same problem: tech built for tech's sake doesn't serve people.
Manufacturing: Interface Confusion
Your predictive maintenance AI buried critical alerts in 200 daily notifications. The UX overwhelms operators who now ignore everything, including emergencies.
→ 67% more downtimeSaaS: Experience Breakdown
Your AI chatbot has great NLP but poor handoff UX. Users get stuck between bot and human support, creating worse experiences than before AI.
→ 31% increased churnEngineering: Workflow Disruption
Your code AI generates valid syntax, but the interface doesn't match developer workflows. They spend more time fighting the UX than coding.
→ 40% velocity lossOperations: Alert Fatigue
Your monitoring AI is highly accurate but the UI treats all alerts equally. Teams can't distinguish critical from routine, missing what matters.
→ $4.7M annual lossWhy AI adoption really fails
It's not the AI. It's the human experience of using it.
Engineers Design for Engineers
Your AI was built by people who think in algorithms, not by people who understand user psychology and workflow reality.
Features Over Experience
Your AI has every capability except the one that matters: being usable by actual humans in actual work contexts.
Trust Through Design
Users don't trust what they can't understand. Poor UX makes even accurate AI feel unreliable and risky.
Nielsen Norman Group methods meet AI reality
Research-backed UX principles applied to your AI adoption challenges. 15 years making enterprise systems actually usable— translated into the Astrolab Framework™ for human-AI workflows, trust architecture, and measurable adoption.
Make your AI investment work for humans
Three engagement models based on proven UX methodology
Is poor UX killing our AI ROI?
Outcome: Verify the adoption problem and quantify the upside of fixing it.
Mechanism: 2-week UX diagnostic—journey mapping across AI touchpoints, trust-break analysis, and a ranked list of blockers by cost/impact.
Can we fix UX without rebuilding?
Outcome: Improve adoption quickly without replacing core AI.
Mechanism: 8-week optimization—critical interface redesigns, workflow integration, user testing, iterative improvements.
Do we need complete UX transformation?
Outcome: Re-architect human-AI workflows for durable adoption.
Mechanism: 12-week program—full UX strategy, design system, implementation roadmap, adoption metrics.
What 80% adoption actually looks like
Alert interface redesign drives 93% adoption
UX Problem: 200 daily alerts in a flat list overwhelmed operators who couldn't identify critical issues
UX Solution: Hierarchical alert design matching operator mental models, visual priority system, contextual actions
Dashboard UX fix saves $3.2M ARR
UX Problem: AI insights required navigating 6 different screens; users couldn't find value
UX Solution: Contextual AI suggestions within existing workflows, single-screen insights, progressive disclosure
Maintenance UX redesign cuts costs 40%
UX Problem: Predictive maintenance interface designed for data scientists, not maintenance technicians
UX Solution: Mobile-first design for floor use, visual severity indicators, one-tap work order creation
Hiring UX fix drives 84% manager adoption
UX Problem: AI recruiting tool required managers to learn a new interface instead of enhancing the familiar ATS
UX Solution: AI embedded as an enhancement layer within the existing ATS interface, preserving familiar patterns
*Representative outcomes from anonymized engagements
Leaders who fixed their AI UX
"We spent millions on AI that no one used. Astrolab showed us it wasn't the AI—it was the user experience. The fix transformed everything."
"Our AI was technically perfect but the UX was killing us. Astrolab's human-centered approach turned our worst feature into our biggest differentiator."
"Finally, someone who understands that AI adoption is a UX problem. They didn't touch our AI—just made it usable. Usage went from 2% to 84%."
UX expertise meets AI reality
The Astrolab Framework™ combines 15 years of enterprise UX design with deep understanding of why AI adoptions fail. We fix the human experience, not the algorithm.
After designing user experiences that drove adoption across 50+ enterprise integrations, I watched company after company fail at AI—not because the technology was wrong, but because no one designed for the humans who had to use it. Astrolab exists because great AI with poor UX is just expensive complexity.
Ready to fix your AI adoption?
Let's discuss if proven UX methodology can unlock your AI investment.
Schedule UX Assessment