Why Trust Drives AI Adoption [Newsletter #80]

​Hello, AI enthusiasts from around the world.

Welcome to this week's newsletter for the AI and the Future of Work podcast.

In the short and rapid early stage of AI adoption, we’ve seen more organizations embrace AI across their operations. At the same time, fear of job loss and hesitation around learning AI still persist.

There’s a key factor in shifting this dynamic. Surprisingly, it often isn’t employees who resist change most. Instead, the way leaders frame AI sets the tone.

Leaders who build trust through transparency and empathy create the conditions for successful AI adoption.

Today’s conversation highlights the key traits these leaders must have.

Let’s dive into this week’s highlights! 🚀

🎙️ New podcast episode with Kelly Jones, Chief People Officer at Cisco 

As AI becomes more present in our work and daily lives, the narrative that AI will take our jobs is starting to lose strength.

AI can make work more meaningful and more human. If fear still lingers, it’s not because the technology falls short.

According to Cisco’s Chief People Officer, Kelly Jones, it comes down to how leaders show up.

Building healthy teams has been central to Kelly’s work during her 18 years at Cisco, where she has helped shape global teams and strengthen the company’s reputation as a best place to work.

Today, she leads the evolution of Cisco’s culture in the age of AI, shaping strategies that impact more than 86,000 employees worldwide.

For Kelly, openness toward AI doesn’t begin with employees. It starts with leaders and with how they frame AI inside the organization. The logic is simple. When leaders promote fear, that fear spreads. When they promote clarity and trust, teams follow.

This responsibility weighs even heavier for those in leadership roles.

Kelly sat down with PeopleReign CEO Dan Turchin to share a reminder many leaders need to hear: In moments of uncertainty, employees look up, not out. In her experience, AI adoption accelerates when leaders invite employees into the design and deployment process.

Transparency lowers fear. Inclusion builds confidence. And together, they create excitement for what comes next. A future where AI doesn’t replace human capability—it strengthens it.

In this conversation, we cover this and much more:

• Why trust has become the most valuable workplace currency, shaping decisions around AI, culture, and leadership.

• What “super leadership” looks like, and the four traits Cisco’s CPO believes define successful managers in an AI-augmented workplace.

• How Cisco evaluates AI use cases through disruption, scale, and their impact on the employee experience.

• Why the real value of AI sits in automating administrative work, giving people more time to focus on  meaningful work, creativity, and connection.

• The systems Cisco is putting in place to support responsible AI adoption, including governance, upskilling, and clear ethical guidelines.

🎧 This week's episode of AI and the Future of Work, featuring Kelly Jones, Chief People Officer at Cisco.

Listen to the full episode to learn how leadership and trust shape successful AI adoption across organizations.

📖 AI Fun Fact

On October 20, 2025, large parts of the internet slowed or stopped altogether.

ChatGPT went quiet. Smart mattresses stopped working. Video games like Fortnite blinked out. Platforms like Snapchat and even banking apps were affected.

Across the web, services tied to Amazon Web Services stalled. Online shopping paused. Ring doorbell cameras failed. What looked like isolated glitches quickly revealed something bigger.

An AWS outage rippled across the internet and exposed how much of our digital world depends on a single layer of infrastructure.

The cause was a DNS resolution issue.

DNS, or the Domain Name System, translates URLs like “Amazon.com” into IP addresses. You can think of it as a phonebook that lets everything connect online.

But when those phone numbers are outdated or wrong, and you’re AWS, everything breaks fast. That’s a DNS resolution issue.

AWS has suffered major outages before. This one stood out because of its timing.

Just months earlier, Amazon’s cloud unit cut hundreds of jobs, possibly more. At the time, CEO Andy Jassy warned that the adoption of generative AI would lead to layoffs.

That context matters. Not because AI caused the outage, but because it shapes how people interpret moments like this.

If Amazon is relying on AI to pick up the slack after those AWS layoffs, this outage may serve as a stark example of how attempts to rely too heavily on AI systems can backfire, as Noor Al-Sibai writes in Futurism.

In the same article, Al-Sibai quotes Corey Quinn, a cloud computing expert and author of the Last Week in AWS newsletter, who said:

“You can hire a bunch of very smart people who will explain how DNS works at a deep technical level but the one thing you can’t hire for is the person who remembers that when DNS starts getting wonky, check that seemingly unrelated system in the corner, because it has historically played a contributing role to some outages of yesteryear.”

PeopleReign CEO Dan Turchin expects more dissonance as customers and displaced workers look to assign blame to AI that has seemingly replaced jobs. The counter-narrative is that AI is better at detecting and resolving outages than humans with limited recall.

As is often the case, the answer is more complicated.

A combination of human domain experts paired with machines trained on trusted historical data would have likely led to a faster resolution of the DNS issue.

Expect smaller teams of experts working alongside AI-driven predictions and recommendations to become the new work paradigm.

And as tech-driven apps and services continue to proliferate, expect the demand for new human domain experts to more than offset reduced team sizes. If you’re in a role that is easily automated, now is the time to reskill and upskill.

You have a unique opportunity to become a domain expert and, in the process, turn toil into more meaningful, higher-paying work.

Worth A Listen

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Until Next Time: Stay Curious 🤔

👋 That's a Wrap for This Week!

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