AI Isn't New. It's Just Better Marketing.
I've been watching the recent messaging from Nextdoor CEO Nirav Tolia about how AI will revolutionize the way we interact with neighbors and local businesses. While AI is certainly advancing rapidly, the idea itself isn't exactly new.
Nirav joined Yahoo as employee #84 and spent years helping shape the early internet. From web directories to e-commerce and eventually becoming one of the company's public faces, he has an impressive background. The spokesperson role certainly explains why he's comfortable in front of a camera.
But if he'd spent more time in the operational trenches, he might realize many of us have been working alongside AI for decades.
My career started in primary automotive collections—a far cry from Silicon Valley glamour. I worked predictive dialers, managed collection queues, answered inbound calls, negotiated payment arrangements, and made lending decisions. It was hard work, but I'm grateful for the experience because it exposed me to AI long before it became today's buzzword.
Some examples:
• Phone IVR Systems – "Press 1 for English. Oprima el dos para español." These systems intelligently routed calls, reduced congestion, improved service levels, and matched customers with the right department. Primitive by today's standards, but still AI-driven automation.
• Grammarly (2009) – When I transitioned into Learning & Development, I began relying heavily on Grammarly to help create participant workbooks, facilitator guides, instructional materials, one-page FAQs, job aids, and other learning documentation. It became an invaluable AI writing assistant that not only catches spelling and grammar mistakes but also predicts the author's intent, improves readability, and suggests clearer ways to communicate ideas. Even today, I use Grammarly alongside ChatGPT and other AI tools to ensure my message is conveyed as effectively as possible.
• Siri (2010) – Before becoming part of iOS, Siri launched as a standalone app capable of voice commands, sending texts, answering questions, and controlling device functions through natural language.
• Automotive Credit Decisioning Matrices – During my automotive finance career, I purchased loans and leases from franchise dealerships. A human didn’t do the first review—it was performed by an automated decision engine evaluating the four Cs of credit: Character, Capacity, Capital, and Collateral. Straightforward approvals and declines happened automatically, while analysts focused on the more complex borderline applications. Business rules could be adjusted as risk appetite changed.
AI has been quietly improving efficiency for decades. Today's generative AI is more powerful and accessible, but it didn't suddenly appear overnight.
Before declaring AI "revolutionary," let's take a moment to acknowledge the thousands of engineers, call center employees, underwriters, operations leaders, and technologists who have been working with AI since the 1990s and long before it became the latest corporate buzzword.
