"AI has moved a little bit more slowly than a lot of people anticipated, but it's still a long-term threat for Apple. This is going to be very serious long-term." This stark assessment from Alex Kantrowitz, founder of Big Technology, on CNBC's Squawk Box, cut through the celebratory chatter surrounding Apple's robust holiday season. Kantrowitz, a seasoned observer of the tech industry, engaged with the CNBC anchors to dissect the contrasting AI strategies of two of the world's most influential technology companies: Apple and Alphabet (Google).
The immediate forecast for Apple appeared undeniably bright. Kantrowitz noted that the early sales data for the iPhone 17 was "definitely very promising." He relayed Tim Cook’s expectation that the current quarter would mark "Apple's best quarter in its history, more than $130 billion in revenue expected." This surge in hardware sales, particularly for the latest iPhone model, indicates a strong consumer response to Apple's core product, a welcome rebound after the perceived disappointment of the iPhone 16.
However, this apparent market strength serves to obscure a growing strategic chasm. While Apple continues to excel in its established hardware and services segments, its progress in artificial intelligence remains notably sluggish. Kantrowitz articulated this directly, stating that Apple is "still behind the eight-ball on AI." The anticipated readiness of advanced AI capabilities, once widely predicted for Apple, Google, and Amazon, has not materialized at the pace many expected, granting Apple a temporary reprieve from immediate competitive pressure in this domain.
The long-term implications for Apple are significant. Without a clear and compelling AI strategy integrated into its ecosystem, Apple risks falling behind competitors who are aggressively investing and innovating in this transformative field. The reliance on incremental hardware improvements, while currently successful, may not be sustainable as AI increasingly redefines user experiences and product utility across the tech landscape.
In stark contrast, Google has orchestrated a strategic resurgence on the AI front. Kantrowitz lauded Google's "great job on the AI front," attributing much of this success to a decisive organizational shift. Google has centralized its AI operations, moving approximately "250 or so engineers from Search, which is Google's most important product unit, into Google DeepMind." This bold move consolidated disparate product areas, or "fiefdoms" as Kantrowitz described them, under a unified AI "engine room," fostering a more cohesive and efficient development environment.
This centralization has not only accelerated Google’s AI development but also reinforced its formidable advertising business. Despite the emergence of powerful new players like OpenAI, Google’s core search business remains "unchallenged," largely due to its unparalleled ad-tech ecosystem. OpenAI, while boasting a massive user base for ChatGPT, currently lacks a comparable advertising product or robust ad network. This fundamental difference in business models means that while new AI services may capture user attention, they are not yet posing a direct financial threat to Google's primary revenue streams.
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Indeed, Kantrowitz suggested that the evolving AI landscape might be more "additive" than a winner-take-all scenario. He posited that generative AI applications would likely complement, rather than replace, traditional search, creating new use cases and expanding the overall market. This perspective allows for the coexistence of a "very big Google business and a very big OpenAI business," each carving out its own niche within the expanding AI economy.
Returning to Apple, the picture remains less clear. The talent drain from Apple's AI divisions, with engineers reportedly moving to companies like Meta, underscores a persistent challenge. Kantrowitz confessed, "I don't really know what they're working on there. I don't know if they know." This ambiguity surrounding Apple’s internal AI initiatives, coupled with its historical preference for secrecy, leaves the market speculating about its true readiness to compete in the generative AI era. While not spending capital on a floundering AI effort could be seen as prudent, it also signifies a lack of visible, aggressive investment and a tangible product roadmap in a domain that is rapidly becoming central to technological innovation.
