gen-ai

Why I’ve Stopped Playing the Field: The Case for a Google-Only AI Strategy

I have spent the last two years neck-deep in the world of Artificial Intelligence. I haven’t just been “dabbling” or asking chatbots to write limericks about cheese; I’ve been formally studying the architecture, experimenting with the logic, and trying to find a path through what has become a chaotic digital circus. After twenty-four months of watching a thousand different startups promise to “revolutionize” my morning coffee, I’ve reached a conclusion that will likely upset the tech-evangelists.

I’ve decided to stop playing the field. I have formally narrowed my AI skills and my entire workflow to Google-developed tools.

Now, some might call that a lack of imagination. I call it a refusal to spend my life managing a bag of mismatched spanners. While the rest of the world is busy chasing every “model of the week” like a puppy chasing a van, I’ve chosen to settle down with the one player that actually has the bank balance and the infrastructure to still be standing when the dust settles.

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By David Tong, ago

Beyond the AI Hype: Entering the Trough of Disillusionment

Let’s bypass the standard executive summaries and talk frankly about what is actually happening with AI in our departments.

If you sit in enough steering committee meetings the past 12-18 months, you notice a distinct shift in the room when the topic of any “AI”-related topics come up. The initial novelty has completely worn off. We find ourselves thoroughly entrenched in Gartner’s Trough of Disillusionment. From a management perspective, this is exactly where we need to be. The early days of generative AI were dominated by parlor tricks. Seeing a chatbot write a poem or draft a polite email, or generating 7-fingered models for social content were interesting, but general-purpose tools do remarkably little to improve a department’s operating margins, let alone an enterprise’s.

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By David Tong, ago