Is AI a product or a Service?

 


        I watched a recent video by Marques Brownlee, a YouTuber, who made a great point about what is the use case for AI. He quoted a Wired Podcast by saying that WDC, Apple's developer conference, proved that "AI is a feature not a product" and while I partially agree I think it's important to understand that fundamentally AI at this point is almost exclusively stemming from the emergence of software. Software as an industry tends to follow the Software-as-a-Service model (SaaS). It should follow, then, that AI would naturally also become a service or feature for the end consumer.

    However, what I really want to point out is that AI, at least in the Large Language Model Space, is struggling to find good business use cases. It's not that they do not exist or that the technology is not amazing but consider that it is more of a novelty at this point and is not quite ready for large scale implementation for businesses. For example, McDonald's just recently revealed that they are ending the use of AI taking drive-thru orders while still recognizing that it has a place int the future. It does beg the question though of whether or not AI might still be useful to large corporations, especially given that Human labor in many areas is still decent enough and importantly cheap enough that the use case for AI remains almost untenable. 

    AI is not cheap and is a great tool in quarterly reports to generate hype around a company, but fundamentally as a product it does not stand out. And as a service it seems much more useful, but as of yet is still mostly novelty. This is not to discount that it will continue to progress and get better, but when it gets better will it be its own product with an ecosystem, or will it be a service that you integrate with other products? That is not quite clear yet.

    Despite the promising applications, several barriers impede the widespread adoption of AI in business. Cost is a significant factor. Developing and deploying AI solutions requires substantial investment in both technology and talent. Additionally, many businesses are hesitant to fully automate processes that are currently handled by human workers, partly due to the unpredictability and potential failure of AI systems, as evidenced by McDonald’s experience with AI in drive-thrus.

    Another critical barrier is the lack of understanding and expertise in AI among business leaders. This knowledge gap can lead to unrealistic expectations and disappointing results when AI projects do not deliver immediate or clear-cut benefits. Moreover, concerns about data privacy and security also play a role in slowing down AI adoption, as businesses must ensure that their AI systems comply with regulations and protect sensitive information.

    Looking ahead, the future of AI in business will likely hinge on its ability to evolve from a novelty to a necessity. As AI technology advances, it will become more reliable, affordable, and integrated into everyday business tools. This evolution will depend on continuous improvements in AI algorithms, increased availability of high-quality data, and advancements in computing power.

    Further, the development of AI ethics and governance frameworks will be crucial in building trust and ensuring responsible AI deployment. Companies will need to adopt transparent practices, mitigate biases in AI systems, and address the ethical implications of AI use to gain the confidence of consumers and regulators alike.

    While AI is currently more of a feature than a standalone product, its role as a service is gaining traction. The journey from novelty to necessity will involve overcoming significant barriers, but the potential benefits make this a worthwhile endeavor for businesses willing to invest in and adapt to this transformative technology.

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