INBOX INSIGHTS, June 11, 2025: When AI-First Goes Wrong Part 3, Speakability and Text to Speech AI - Trust Insights Marketing Analytics Consulting

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INBOX INSIGHTS: When AI-First Goes Wrong Part 3, Speakability and Text to Speech AI (2025-06-11)

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When AI-First Goes Spectacularly Wrong – Part 3

If you missed Part 2 on why smart companies keep making the same AI mistakes, you can find it here. This week: the hidden costs of the “replacement approach” to AI.

Most leaders focus on what they’ll save by eliminating human roles, but they never calculate what they’ll lose.

So let’s do that calculation. Here’s your SWOT analysis of what actually happens when organizations choose replacement over partnership.

Strengths Lost: The Internal Expertise Drain

Institutional Knowledge Disappears:

Those contractors Duolingo eliminated didn’t just create content—they knew what worked. They understood which lessons confused beginners, which cultural references landed, and which teaching approaches actually helped retention.

This isn’t information you can feed into an AI model. It’s pattern recognition developed over thousands of interactions with real learners. When you eliminate the people, you lose the insights that took years to develop.

Tacit Knowledge Evaporates:

The most valuable knowledge in any organization is tacit—the stuff people know but can’t easily explain. How to spot quality issues before they become problems. Which customers need extra attention. When to break the rules to get better outcomes.

AI can replicate explicit processes, but tacit knowledge lives in people’s heads and transfers through relationships. Eliminate the people, and it’s gone forever.

Innovation Capacity Shrinks:

Here’s the organizational behavior insight that leaders miss: the people doing day-to-day work are often your best source of improvement ideas. They see problems first and understand why current processes fail.

When you eliminate those roles, you don’t just lose current capabilities—you lose your ability to spot opportunities for future improvements.

Weaknesses Created: New Organizational Vulnerabilities

Quality Control Gaps:

Duolingo’s remaining human reviewers are now overwhelmed trying to catch errors across dozens of language programs. The workload that was distributed among many experts is now concentrated among fewer people.

This creates bottlenecks, burnout, and gaps. Quality doesn’t just maintain—it degrades as remaining staff struggle to cover expanded responsibilities.

Knowledge Transfer Breakdown:

When experienced people leave (voluntarily or involuntarily), their knowledge leaves with them. But the organizational behavior pattern is worse: remaining employees stop sharing knowledge freely when they think their job security depends on being irreplaceable.

This creates knowledge hoarding, reduces collaboration, and makes the organization more fragile.

Learning Organization Dysfunction:

Organizations learn through people. When you eliminate the people who understand both current operations and potential improvements, you break the learning loop that drives continuous improvement.

Opportunities Missed: The External Competitive Costs

Market Responsiveness Declines:

Human experts can adapt quickly to cultural shifts, trending topics, or emerging learner needs. They can create timely, relevant content that connects with current events or social movements.

AI can scale existing patterns but struggles with real-time cultural responsiveness. You miss opportunities to stay relevant and connected to your audience.

Innovation Potential Shrinks:

The most successful product innovations come from deep domain expertise combined with user empathy. People who understand both the subject matter and the audience can spot opportunities that data alone can’t reveal.

Eliminate the domain experts, and you lose your capacity for breakthrough innovation.

Competitive Differentiation Erodes:

What made Duolingo special wasn’t just language lessons—it was culturally aware, creating sound content created by experts who understood learning science.

As they move toward AI-generated content, they lose the differentiation that human expertise provided. They become more like their competitors, not better than them.

Threats Increased: New Competitive Vulnerabilities

Competitor Advantage Creation:

While Duolingo eliminates language experts, competitors who maintain human expertise can offer superior cultural authenticity and sophistication.

The talent Duolingo eliminated doesn’t disappear—it goes to competitors, taking institutional knowledge with it.

Brand Vulnerability Amplification:

The social media backlash revealed something crucial: customers value human expertise. When users comment “mama may I have real people running the company,” they’re expressing preference for human-created content.

Brands that eliminate visible human expertise become vulnerable to competitors who emphasize their human element.

Crisis Response Capacity Diminished:

The masked employee video and social media blackout revealed another hidden cost: when crisis hits, you need people who deeply understand your brand, audience, and values.

AI can’t navigate nuanced reputation management or cultural sensitivity during a crisis. The people who could have managed this crisis effectively were the ones being eliminated.

Market Disruption Susceptibility:

Organizations with strong human expertise can pivot quickly when markets shift. They can identify new opportunities, adapt offerings, and respond to disruption.

Organizations that have eliminated human judgment and creativity become more rigid and less adaptable to change.

The Organizational Behavior Pattern

Here’s what’s really happening: leaders see AI capabilities and assume human capabilities become redundant. But they’re not calculating the systemic effects on organizational learning, adaptation, and resilience.

The SWOT reveals a dangerous pattern: short-term cost savings create long-term competitive vulnerabilities that are much more expensive to address than the original human expertise would have been.

The Strategic Question

The question isn’t whether AI can handle specific tasks that humans currently do. It’s whether eliminating human expertise makes your organization stronger or weaker in the long term.

For most organizations, the SWOT analysis reveals that replacement approaches trade short-term savings for long-term competitive disadvantage.

The companies that thrive with AI won’t be the ones that eliminate human expertise most aggressively. They’ll be the ones that figure out how to amplify human capabilities while maintaining the organizational strengths that expertise provides.

Next week in Part 4: How to implement AI in ways that preserve organizational strengths while building new capabilities.

What expertise is your organization at risk of losing?

Reply to this email to tell me, or come join the conversation in our free Slack Group, Analytics for Marketers.

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In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss the Apple AI paper and critical lessons for effective prompting.

You’ll learn what reasoning models are and why they sometimes struggle with complex tasks, especially when dealing with contradictory information. You’ll discover crucial insights about AI’s “stateless” nature, which means every prompt starts fresh and can lead to models getting confused. You’ll gain practical strategies for effective prompting, like starting new chats for different tasks and removing irrelevant information to improve AI output. You’ll understand why treating AI like a focused, smart intern will help you get the best results from your generative AI tools. Tune in to learn how to master your AI interactions!

Watch/listen to this episode of In-Ear Insights here »

Last time on So What? The Marketing Analytics and Insights Livestream, we walked through building an AI sales copilot. Catch the episode replay here!

This week on So What?, we’ll be remixing content using foundation generative AI tools. Are you following our YouTube channel? If not, click/tap here to follow us!

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In this week’s Data Diaries, let’s go behind the scenes on one part of our AI-Ready Marketing Strategy Kit: the audiobook version. We generated it with the text to speech system Eleven Labs, but if you’ve read the kit, you know that it’s not conductive to being read aloud.

The secret here is something called speakability, a close cousin of singability. When music composers write lyrics for singers, not only do they have to think about meaning, they have to think about how easy a song is to sing.

For example, vowel placement is a big part of singing. songs that are easy to sing have vowel placements that can be made big or drawn out. Another example are tough consonants that don’t sound great when sung because they’re complex diphthongs, like the word diphthong.

Speakability is the same thing in many respects. As a human or a machine reading something aloud, text has to flow. It has to be free of interruptions and weird structures – like en dash excerpts in the middle of sentences – that can throw off both a human and a machine.

And for text like the AI Kit, one of the worst things you can give to text to speech software systems are lists. Lists tend to REALLY mess up a text to speech system. You often end up with an audio recording that sounds like “bullet point” and other marks being read aloud.

If you’ve downloaded the AI Kit, you know it’s rife with lists, checklists, bullets, checkboxes… everything that will screw up a text to speech system. So what did we do? We put the entire thing through a speakability prompt using Google Gemini 2.5.

We prompted it to essentially rewrite the guide as a spoken script, smoothing out all the known bumps that trip up text to speech systems.

Okay, but where did that come from? We commissioned a Deep Research report on the things that most commonly trip up text to speech systems and using that as part of the prompt, then had Gemini summarize the things to look for in text. The net result is a large prompt (too large to share here) that transforms ANY text into speaking scripts for humans and machines.

The net result is something that the Eleven Labs software had a much easier time reading aloud, which means a much smoother listening experience for you.

The key takeaway is this: use generative AI tools to reformat text for the purposes you want. You did the hard work of creating your content – now let generative AI transform it for use in nearly any system or format.

Be sure to catch our livestream on Thursday at 1 PM at TrustInsights.ai/youtube for more content transformation ideas.

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