We are witnessing the emergence of agentic and ubiquitous AI systems that will reshape the digital world. We will see vastly more machine content than human content: nothing will be comprehensible without a machine interpreting it for us. By machines, for machines is the new paradigm.
While considering the potential risks and implications of OpenAI releasing an AI voice that appears designed to draw people in, I found an interesting r/artificialinteligence Reddit thread of people sharing their preference for talking with AI over other humans.
A recent paper entitled The Platonic Representation Hypothesis supports the idea that widespread use of singular algorithms might actually be simplifying hte world. Large-scale AI models, such as GPT-4, are all starting to learn the same representations of human digitized reality.
Considering Big Tech's longer-term potential, peril, and possibility with AI.
This week, the investor narrative about Big Tech was all about AI. Microsoft’s earnings beat estimates, fueled by AI growth in its cloud business. Alphabet benefited from AI growth in its cloud, advertising, and productivity suite businesses, although not as much as investors had hoped. Amazon said its cloud business had a significant year due to generative AI and is exploring new generative AI tools in its retail business. Meta’s story was mostly about revenue growth and cost-cutting unrelated to AI, but investors still talked up potential to integrate AI in its advertising business. True to form, Apple said it was “incredibly excited” about things it won’t talk about yet, but investors read through the lines when Tim Cook said “there’s a huge opportunity for Apple with Gen AI.”
We’ve been in the AI space for more than a decade and built our first AI stock index in 2015, so we understand the excitement. But, this quarter’s results only reflect the very early stages in the long journey with AI. So, we’d like to take time this week to think about the longer-term prospects for Big Tech by considering three things:
Potential. What’s the upside potential for the current business?
Peril. What’s the downside peril for the current business?
Possibility. What new opportunities might AI open?
Note: This is not investment advice in any way, shape, or form. If you want investment advice, talk to an investment advisor. We do not hold direct investments in these stocks, although we may own them in index-based securities.
Potential. Strong potential for growth in Google Cloud supporting AI development, Google Workspace upsells to include generative AI features, and improvements in Search and YouTube to benefit advertisers. Alphabet’s investment in its chip technology for data centers and phones gives it a lead against other Big Tech companies that are just starting to develop chips. Its ability to reduce the cost of running generative AI by using phone-based chips is only matched by Apple.
Peril. Significant risk to Search revenue and profits as the company adds generative AI results to the traditional search experience. This is perhaps the most unknown risk of all Big Tech companies, given how little we know about what the company plans to do and the scale of the peril. Good to remember that Alphabet created the technology behind LLMs so they’ve had a long time to plan for this perilous transition.
Possibility. Conversational search and dynamic design could allow Google to capture more traffic and commerce by serving more consumer needs. For instance, if you go to Google to search for a product or service, might Google engage in a conversation to learn more about your needs and then provide that product or service directly? Google is the first stop for most people’s journey on the internet—might they capture more of your journey simply by chatting?
Potential. AWS is the largest cloud business and, so far, it seems to be showing early success in delivering AI services. We’re fans of the company’s early use of generative AI to summarize user reviews, and can see a long list of opportunities to integrate generative AI into the shopping experience. The company’s new AI chips will help maintain cost control and predictability as it scales its data centers.
Peril. Generative AI content could make Amazon listings a mess (we’ve already read about reviews being written by ChatGPT). While AWS is showing good gains today, it’s possible that companies would shift to either Microsoft or Google for cloud AI that benefits from tying into those companies’ productivity suites.
Possibility. Remember the little “refill” buttons Amazon used to sell to make it easier to reorder things like laundry detergent by pressing a button next to your laundry machine? Now imagine that you can create an AI agent that has the authority to shop for you. Not just re-ordering products, but shopping based on an objective like: buy me all the supplies I need for my kids’ birthday party or buy me a complete outfit for my Swiftie daughter.
Potential. Great AI experiences will require data privacy and security at a reasonable cost. Apple is well positioned to deliver this given its leading position in user privacy & security and well-developed AI-oriented chips in iPhones and Macs. Incorporating new AI experiences across its software platform (including for developers) could drive a new hardware upgrade cycle and growth of services to support additional storage requirements.
Peril. Risk of losing market share to other platforms that offer better AI experiences.
Possibility. The new Vision Pro provides a glimpse into what might be possible by combining spatial computing with a conversational interface. Might Apple be able to replace the keyboard and mouse with voice and gestures? Apple also has a similar possibility as Google to use chat to capture more of a user’s experience. In fact, Apple might even use chat to capture the user before sending them through to Google.
Potential. Increase advertising effectiveness through generated personalization. Create new consumer experiences with avatar characters (a la Character.ai) across its social properties. Strong lead in the open-source community, which could give its Llama model strong tailwinds.
Peril. Creating personalized ads and communications is risky today. Generative AI creates a huge misinformation challenge for Meta—likely in elections around the world in 2024. Generative AI is expensive to run and Meta risks that usage is highly popular while advertising revenue can’t keep pace.
Possibility. Zuck continues to believe consumers will want a future in an AI-driven metaverse. We haven’t found his vision compelling—but maybe we just can’t see it yet.
Potential. Well-positioned across its entire portfolio: cloud, analytics, and productivity. The company is experiencing strong interest in upgrading to add AI features by a long list of companies. If these evaluations result in deployments, the company could experience strong revenue growth.
Peril. If Copilot isn't good enough, significant downside risk of customers slowing or stopping deployments. We see a lot of hidden complexity in workplace automation that will take time and effort to untangle. If this slows adoption growth, Microsoft could suffer the biggest downside from disillusionment. If Copilot is successful, however, and people use Copilot as much as Microsoft hopes, delivering the service could become quite expensive. If it delivers enough value, the company could simply charge more. But if it doesn’t deliver enough value, all bets are off.
Possibility. For companies with closed Microsoft ecosystems, AI agents could be powerful. AI agents are really exciting, but they are also terrifying without well-defined agency. The company’s big advantage here is the security control to provide AI agents with adequate guardrails to complete tasks and accomplish objectives without going rogue.
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