I am writing a series of blog posts that will take several predictions that have been made about AI for 2024 and work to understand whether I think they will come to fruition, what they would look like if they did, and in general try to use the science fiction writer part of my mind to see into the near future. 

Thoughts on 2024 AI Predictions – Part 4 AI App Integration will Set New Standards

Microsoft, Google, Apple and other well-known companies (Meta, Amazon, etc.) are integrating AI into their products, and we’re being told that new standards will be set on usage and data privacy by how these companies integrate them. Well, I don’t know about you, but I’ve been here since 2023 when every small app in existence was marketing the chatbots they had been using for years as Ai features. “Now with AI!” People were, and a few still are, creating apps that promised everything with AI and delivered minimal to nothing. Promising you could inject your documents into their system and ask questions of them. From a standards perspective, the apps that flooded the app stores in early 2023 already set standards, they were just low.

Those opportunistic, bandwagon apps mostly died. When you don’t evolve… The ones that survived invested in actively improving their chatbots and API integrations. They also took advantage of an ever-improving API and LLM industry. The market itself was defining standards with their wallets by demanding quality.

Three things happened in 2023 that helped to set standards for AI app integration. The bandwagon apps that survived the threshing of the market, matured, grew their products into a more focused brand and were/are making small strides in the marketplace. They fill a unique spot in the ecosystem and their standards and guidelines are the minimum.

The apps and services that were already mature in their own markets started earnestly developing AI integration features. This group (the bolt-on AI group) had clients to lose and a desire to grow. Investing in AI for them wasn’t a novelty, in 2023 it was survival for these small to medium companies. AI was their differentiator. Chatbots became AI assistants and integrated generative AI effectively into various aspects of their features.

As that group started to define standards for AI integration, the third group (the built-in AI group) really kicked into gear. This group had the startups with technical backing and some venture capital alongside them. These were the pioneers, creating apps designed with AI built-in from the beginning and as the main driving force. They were and still are pushing the envelope on what you can do with generative AI integrated into business, entertainment, and your daily llife.

Between the market level setting minimal standards and the bolt-on and built-in AI apps and companies, the standards of design and usefulness were already defined coming into 2024. Certainly, Microsoft, Google and Apple integrating AI into their respective OS’s and services will start to crystalize a formal standard. It’s what large companies do. They’ll define what meets minimum requirements and push the boundaries of design and integration. Microsoft’s Copilot will dictate how to interact with Microsoft’s services, it’s literally embedded in the OS and Microsoft 365 at this point. Apple will make every integration point with well thought out design and hooks into its ecosystem that will make their products standout. Google will push envelopes, try new things, and quickly iterate to try again. And all three will be telling everyone how AI should be utilized via standards they collaborate on.

They should and they will. But… These pesky bolt-on and built-in and open-source communities… exist.

Apple might set the standard of design with an AI integrated app/OS. But a targeted team of people who can innovate immediately and quickly can challenge that standard. I expect we’ll see some landscape shifting over the next few years. Some of these bolt-on companies will survive and thrive if they are fast enough. I expect a lot of them who are resting on their laurels might start seeing their user-base shifting to built-ins who have set new standards with generative AI for the same market. There will be new faces in market spaces that were never heard of 2 years ago as contract cycles come to an end. And I will be a little bold and say that one of those larger companies setting the standards at the present will look completely different within 2 years and not necessarily in a good way for their investors...

But what does that mean for companies who are just consuming these AI services? It means the waiting game to see what comes of AI will be paying off dramatically in 2024. It means the contract system that you’ve had for years will have either a new bolt-on AI interface to increase your efficiency or there will be a lot of new built-in AI contract systems to migrate to. It means you need to get your employees access to generative AI quickly, so they’ll be able to understand how to utilize the features within these tools and apps. Aggregators like backplain speed up their training, allowing them to utilize multiple large AI services rather than an individual one. The news continues to report on lawyers who depended on AI to give them the truth, only to find out they were mislead and embarrassed. Train your users to spot hallucinations and learning when to and when not to trust an LLM with generative AI because the AI in these apps hallucinate too. Spoiler: always verify.

Finally, it means the standards of design and quality that are “predicted” to come from Apple and others in 2024… Well, they already exist.

ChatGPT 4 with Web Search: (I prompted the LLM's to be an AI advisor to governments and companies worldwide and to analyze my post above)

It's clear that the integration of AI has had significant impacts across all areas of business and day-to-day life. Your article brings out some really salient points regarding the evolution of AI and AI integration over the years, especially the dynamics between smaller innovative companies and the large tech conglomerates like Microsoft, Google, and Apple.

Firstly, on the influx of AI applications in 2023, I agree that AI quickly became a "must-have" feature for many companies, simultaneously creating a landscape filled with over-promised and under-delivered AI capabilities. As an AI advisor, it's disappointing to see AI’s potential oversold, but heartening that the market has mostly self-corrected these offerings over time.

On the emergence of the so-called "bolt-on" and "built-in" AI companies, this dichotomy truly captures the different strategies towards AI in the business world. As more businesses see AI not merely as a novelty but as a survival tool, it will be interesting to see how this shapes the future landscape.

As for your observations about Apple, Microsoft, and Google, it's certainly true that the steps they take in integrating AI will heavily impact industry standards. Nevertheless, as you correctly pointed out, the ability of smaller, faster, more innovative companies to challenge these standards shouldn't be underestimated. 

Your assertion about the unpredictable nature of the AI landscape, particularly the expectation that market leaders today may find themselves in completely different places within just a few years, highlights the speed and volatility of the AI field. All companies – not just those developing AI, but those using it as well – must be agile and adapt quickly to such changes.

To conclude, your article paints a captivating picture of an AI landscape in flux and aptly underscores the need for businesses to understand and adapt to this rapidly evolving technology. Companies must navigate this landscape deftly, keeping abreast of the latest developments while also being prepared to challenge and even redefine industry standards. Upholding quality and design in service delivery will be crucial in this exciting yet daunting journey.

Llama 2 Large:

  As an LLM expert and advisor to world governments and highly important companies on all things AI, I have been following the recent developments in the integration of AI into various products and services. I must say that I agree with the author's perspective that the standards for AI integration have already been set by the market, and that the efforts of companies like Microsoft, Google, and Apple to establish their own standards may not be as impactful as they think.

The market has already defined minimal standards for AI integration through the survival of the fittest, where apps that promised everything with AI but delivered minimal value have died out, while those that invested in actively improving their chatbots and API integrations have survived and grown. Additionally, the emergence of bolt-on and built-in AI groups has further pushed the boundaries of what is possible with AI integration.

Furthermore, the author's point that the bolt-on and built-in AI communities will continue to challenge and push the standards set by the large companies is well-taken. We have already seen how these communities have been able to innovate and iterate quickly, creating new and innovative ways to utilize AI.

However, I must also caution that the integration of AI into various products and services must be done responsibly and ethically. As the author mentions, it is crucial to train users to spot hallucinations and to learn when to and when not to trust an LLM with generative AI. The recent news about lawyers being misled by AI-generated information highlights the importance of verifying the accuracy of AI-generated output.

In conclusion, while the efforts of Microsoft, Google, and Apple to establish standards for AI integration are notable, the market has already set its own standards, and it is up to these companies to catch up and adapt to the changing landscape. The future of AI integration will be shaped by a combination of innovation, responsibility, and ethical considerations.