Why Many Companies still aren’t Ready for AI Adoption
episode
Voices of Search // A Search Engine Optimization (SEO) & Content Marketing Podcast
59 min
2 speakers
5 chapters
transcribed 1 month ago
Transcript
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Transcript generated automatically by AI and may contain errors.
What is the main topic discussed in this episode?
The Voices of Search Podcast is a proud member of the I Hear Everything Podcast Network. Looking to launch or scale your podcast? I Hear Everything delivers podcast production, growth, and monetization solutions that transform your words into profit. Ready to give your brand a voice? Then visit IHear Everything.com. Welcome to the Voices of Search Podcast in IHear Everything presentation. Production. In this podcast, we'll share the news, knowledge, and strategies you need to navigate the ever-changing world of SEO. Ready to expedite your company's organic growth efforts? Sit back, relax, and get ready for your daily dose of search engine optimization wisdom. Here's today's host of the Voices of Search podcast, Tyson Stockton.
According to recent TWI research, 67% of organizations now spend more than a quarter of their engineering time simply maintaining data pipelines. And that may explain why so many companies are struggling with AI adoption. Because while nearly everyone is experimenting with generative AI tools, most organizations still don't have the infrastructure, governance, or data foundations required to scale AI successfully. So the real challenge isn't access to AI anymore. It's operational readiness. My name is Tyson, and joining me today is Fern Halper, founder of the AI Foundations group and VP and Senior Research Director for Advanced Analytics at TWI. Today we're talking about why many companies still aren't ready for AI adoption, what fundamental systems and organizations are missing, and why original thought may become even more valuable in an AI saturated market.
Vern, welcome to the podcast.
Thanks, Tyson. Happy to be here.
And I I was excited to have this conversation because I I wanted to hear kind of uh Your perspective being so in depth, doing so much research on it and also kind of not just being within the SEO industry. So it's like, I like that you're bringing kind of a a fresh perspective for us SEOs.
Yeah, I'm definitely not in the SEO industry, although I I can make some comments about that.
And maybe to set the stage, like, um, tell the audience and the listeners a little bit about kind of like your background and the research that you do.
Yeah, sure. So I started my career at Bell Labs and later worked at ATT and Lucent. And I think that was during a period where organizations were just starting to think about data. As a strategic asset, and they wouldn't have called it that, you know, then. But and at Bell Labs, I was part of something that would now be called a center of excellence. And we were focused on finding new ways to solve business problems through data and analytics. So we used early machine learning techniques for things like customer churn prediction. We helped to pioneer concepts like continuous auditing, and we explored. how data can be used to drive insights. And we did a lot of analysis for various parts of ATT. And it was a really exciting time.
I mean, I'm I'm talking over twenty years ago. And it was an exciting time. There were new algorithms hitting the market and it was just fun. And I think that um What I what I've seen over the course of my career is that In terms of AI It's not just that the technology has evolved. But so has the scope of the challenge.
Why are many companies still not ready for AI adoption?
You know, when we were at a when I was at Bell Labs, we talked about can we build a model, you know, and now we're asking, can we transform an organization? You know, so today AI can generate content. It can reason, it can take action through agents, but what's interesting is that many of the challenges are are similar. You still need what you were talking about before: trusted data governance, skilled people, clear business objectives. You know, so my perspective has evolved from viewing AI primarily as an analytical capability to seeing it as an enterprise. helping with ent enterprise transformation. You know, but to do that you need the right foundations in place.
And it's I feel like it's so critical, especially for like SEOs, because and I've been saying it quite a bit on the podcast where
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Chapters
5 chapters
1
What is the main topic discussed in this episode?
0:00–3:27
2
Why are many companies still not ready for AI adoption?
3:27–12:00
3
What foundational systems are required to move AI from experimentation to production?
12:00–24:44
4
How do data quality, governance, and skill gaps hinder AI scalability?
24:44–36:02
5
What practical steps can organizations take to assess AI readiness gaps?
36:02–59:24