Understanding Your Users in the Age of AI
🔑 Why Users Still Come First
Artificial Intelligence, automation, and other emerging technologies are reshaping products — from automating repetitive workflows to generating entire user experiences. But no matter how powerful the technology, products succeed only if users adopt them.
In the PathPatron Compass, the People Pillar starts with Users because:
- They feel the product pain most directly.
- Their adoption (or rejection) defines real impact.
- They are the ultimate test of whether technology reduces pain — or simply creates new frustrations.
Think of it as moving from a pain-ful state → to a pain-free state:
- Pain-ful: Slow onboarding, irrelevant recommendations, clunky automation, opaque AI decisions.
- Pain-free: Smooth flows, personalized experiences, transparent explanations, reliable automation.
💡 PM takeaway: Technology must reduce real user pain — not just add novelty.
📱 How Technology Is Changing User Expectations
Users no longer think in terms of features. They expect technology to adapt to them seamlessly:
- Personalization by default — Whether powered by AI or smart automation, users assume products anticipate their needs.
- Fluid interactions — From chat interfaces to automated workflows, smoothness is the baseline.
- Transparency & trust — Opaque automation or unexplained AI decisions quickly erode confidence.
This makes user research in the tech era more complex: PMs must validate not only what users want, but also how comfortable they are with technology doing the work.
And critically — users never exist in isolation. Their pain or delight triggers reactions across the ecosystem:
- If users churn, buyers cut funding.
- If adoption stalls, deciders deprioritize initiatives.
- If satisfaction drops, influencers raise alarms.
- If workflows break, transformers absorb the fallout.
🌍 Case Examples
1. LinkedIn (2023): AI-powered writing suggestions
LinkedIn rolled out AI assistance to help users draft headlines and profiles. Adoption was strong among job seekers who valued speed, but users quickly flagged when generated text felt too “generic.” PMs had to refine prompts and UX to preserve authenticity. LinkedIn, Jun 2025
💡 PM takeaway: Users want help, not homogenization. Preserve their voice while reducing effort.
2. Duolingo Max (2023): AI for personalized practice
Duolingo introduced GPT-4 powered conversation simulations and “Explain My Answer” features. Users loved the added interactivity, but early pilots showed they valued teacher reinforcement alongside AI, not AI alone. Duolingo Blog, Mar 2023
💡 PM takeaway: Even if AI scales personalization, users still want human reassurance.
3. Klarna (2024): AI customer support
Klarna launched an AI-powered assistant that handled 2.3 million customer chats in its first month. Users praised the speed, but satisfaction metrics revealed gaps when complex queries arose — requiring escalation paths to human support. Klarna Press Release, Feb 2024
💡 PM takeaway: AI must integrate smoothly with human fallbacks. User trust collapses when escalation fails.
🧩 Scenario: How User Pain Ripples Across Stakeholders
Imagine you launch an automated onboarding assistant:
- Users love the speed — but find explanations shallow.
- Buyers question the ROI when churn persists.
- Deciders worry about compliance (“Are we over-collecting user data?”).
- Influencers (CS leads) push for more training investment instead.
- Transformers (maintainers) complain the system breaks under edge cases.
👉 The PM’s dilemma: user delight is fragile, and if it slips, every other stakeholder reacts.
💡 PM takeaway: Solving user pain is never just about users. It sets off a chain reaction across the Compass.
🔗 How Users Tie to Transformers
Transformers often bear the brunt of user pain. If onboarding is broken:
- Creators need to redesign flows.
- Implementers must re-wire integrations.
- Testers scramble to validate edge cases.
- Maintainers inherit long-term monitoring burdens.
💡 PM takeaway: Reducing user pain doesn’t just improve UX — it also protects transformers from burnout.
👩💼 How the PM leverages AI for users
Leveraging technology for users is a two-way street:
1. Building for the User
- Keep user pain front and center during AI/automation adoption.
- Translate tech opportunities into clear, relatable value for users.
- Balance speed + personalization with trust + transparency.
2. Using Tech as a PM
You can use AI and automation to stay closer to your users:
- Summarize user feedback at scale → Cluster thousands of survey comments or reviews.
- Generate user journey hypotheses → Feed behavioral data into AI to propose maps.
- Simulate personas → Prompt AI to role-play as different user types.
- Identify trust risks → Use AI to flag where automation may feel confusing or biased.
💡 PM takeaway: Technology helps you reduce your own pain-ful state (data overload) into a pain-free state (clear signals and priorities).
👉 Next step: Try our Micro Learning: Using AI for User Research (free) — a practical exercise where you’ll run your first AI-powered clustering of user feedback.
🚀 Next Step
📥 Download the Stakeholder Mapping Canvas (free) to capture:
- Your users’ biggest pains.
- How AI might solve them.
- What trust barriers you need to address.
And then sharpen your skills with the Micro Learning: Using AI for User Research.
Because in AI-driven products, users don’t just consume value — they define it.