“AI-ify” Your Products – And “The AI Golden Rule”

“AI-ify” Your Products – And “The AI Golden Rule”

You’re a CPO, and the board’s pushing hard to “AI-ify” your product by next quarter, googly-eyed by competitors “AI-powered” buzz. You roll out an AI recommendation engine, expecting a win, but users hate it—irrelevant suggestions, no control, and a 20% engagement drop in a week. Why? Chasing AI hype over user needs, a mistake that sinks 80% of AI projects (McKinsey, Gartner). Instead of racing to keep up, you can be a smarter leader, building AI that users trust and love. This blueprint shows you how, starting with a principle that delivers ROI without the fallout.

A Practical Guide for Product Leaders

With 32% of consumers switching brands after one poor experience (PwC, 2022), human-centered AI is critical. This 5-part series introduces a playbook built on a core principle that ensures your AI delivers ROI by prioritizing users.

The AI Golden Rule: “AI Must Empower Human Agency”

The cornerstone of human-centered AI is simple but powerful: AI must empower human agency. This is a practical filter for every feature, preventing costly missteps and building trust. Grounded in Self-Determination Theory, it translates into three actionable pillars. First, autonomy ensures users steer AI with opt-outs and clear choices, like GitHub Copilot’s optional code suggestions. Second, competence comes from transparent explanations that build confidence, as seen in Duolingo’s adaptive feedback. Third, relatedness fosters collaboration and community, such as Slack’s AI nudges for team workflows. Together, these pillars turn AI from a gimmick into a feature users can’t live without.

Why Human-Centered AI Wins

Chasing AI hype dooms projects. Features labeled “AI-powered” often miss real problems and undermine user control. Take Salesforce Einstein’s early models, which predicted lead scores without explanations, frustrating reps and hurting autonomy. The fix—transparent reasoning, like “This lead ranks #1 due to recent engagement,” and user overrides—boosted adoption by 25%. In contrast, Spotify Discover Weekly empowers users to skip, save, or share playlists with clear logic, such as “Based on your recent listens,” driving 80% user engagement. Ignoring human agency leads to eroded trust, as with Alexa’s misheard commands creating unease, silent churn, where poor recommendations caused 19% of Netflix users to cut usage (Statista, 2022), and wasted resources, like IBM’s Watson Health burning $4B on misaligned features.

From Principle to Practice: Your AI Playbook

Where AI Goes Wrong—and How to Fix It

AI missteps are costly but avoidable when guided by The AI Golden Rule, which prevents three critical pitfalls. First, overreach happens when AI makes decisions without user consent, stripping away autonomy and breeding resentment. Instead of empowering CX, such systems feel controlling, prompting users to distrust or abandon them. The solution lies in prioritizing user control with clear opt-in mechanisms and customizable settings. Second, silent disengagement creeps in when AI delivers irrelevant or opaque outputs, undermining users’ sense of competence. Without transparency or context, users lose confidence, quietly reducing engagement. Addressing this requires AI to provide clear, relevant suggestions grounded in user data and explained in plain terms. Third, resource waste occurs when AI is built for hype rather than solving real user problems, draining budgets and missing ROI. Aligning AI with specific, user-defined needs ensures resources are invested wisely. By applying the AI Golden Rule’s focus on autonomy, competence, and relatedness, these pitfalls transform into opportunities for trust and loyalty.

The Solution: CX Curve + ORBITS Model

The CX Curve maps how emotions, from frustration to trust to delight, shape adoption. The ORBITS model provides a step-by-step guide to apply The AI Golden Rule:

Obstacle: Pinpoint user friction points without overstepping their autonomy. Use AI to detect inefficiencies in workflows, but ensure suggestions are optional and respect user preferences, preserving their control.

Research: Design AI to enhance decision-making confidence. Model suggestions based on anonymized user data, providing transparent reasoning to make outputs feel trustworthy and relevant.

Benchmark: Align AI outputs with users’ specific goals. Configure systems to adapt to individual priorities through customizable settings, ensuring relevance over generic solutions.

Invest: Support user onboarding with personalized nudges. Use AI to guide users through initial interactions with tailored prompts that adapt to their progress, fostering confidence without being prescriptive.

Transform: Build lasting habits by celebrating user milestones. Implement AI-driven rewards for small achievements to encourage engagement and create a sense of accomplishment.

Share: Amplify user advocacy by enabling seamless sharing of AI-generated outputs. Design features that allow users to share results effortlessly, strengthening community and connection.

Trust-Focused Metrics: Success is measured through specific metrics:

Feature Adoption Rate: Tracks the percentage of users enabling AI suggestions, targeting over 60%.

User Retention: Measures the percentage of users returning after 30 days, aiming for over 75%.

User Sentiment Trend (UST): Monitors real-time shifts in user sentiment via micro-surveys or behavioral signals, such as emoji reactions or feature usage patterns, with a goal of a consistent positive trend over 2 weeks.

At every ORBITS step, the AI Golden Rule ensures AI respects user control, boosting ROI and loyalty.

Your Turn...

What’s your biggest challenge in building human-centered AI—proving ROI, balancing automation, or ethical data use? 

This article draws on principles from my book, “The CX Curve-Rewiring Corporate DNA for Relentless Customer Focus”. You can find it on Amazon