Trillions of dollars in business are an alluring prospect in the AI products/platforms space, which will attract billions in investment. Throwing money is not going to fetch results. Just as it happened in the early stages of telecommunications, which was a huge learning for everyone including and especially the companies and governments – because everybody got it wrong – the AI market too will force interested parties to think carefully before plunging. Clinging to entrenched notions could be a path to disaster.
The fascination with ‘AI’ is so overwhelming with many ‘commentators’ predicting the eclipse of many roles and functions that it doesn’t seemed to have dawned on most people that AI is a business to be built, which means finding ways to counter competition. Not just companies but even countries are competing with one another, reminiscent of the fight for space that spanned the Cold War. Bill Gates warned a few days ago that China is winning the AI race outside the West.
It is not a simple competition. This competition, very similar to the Cold War, spans many businesses such as chips, copper, cobalt, rare earth, electronics, software, and so on. It is in grasping the nuances of counter-products that the potential for edge will begin to appear. Of course, you still have to find ways to incorporate that ‘edge’ in a coherent strategy.
Products and products
There are many AI ‘products’ that are vying with one another to attract customers, some of them falling under the GenAI category and for the sake of convenience, the rest. (We are not evaluating GenAI in this article). Among the rest, we can distinguish between products that are embedded within an existing software, such as SAP, for example and other products that facilitate something or the other. And platforms, which could be a blend of products and services, offered on a software as a service basis from either designated data centres or cloud.
Clearly, just as we would study competition under different ‘categories’ of FMCG products or steel or whatever, we must embrace the same approach for understanding competition within the ‘AI world of products’. This competition will displace many existing products, not just people, because the new version or new generation of AI products will presumably do things better than earlier ones.
Reversion to DSS?
For instance, it is an important question to ask whether AI-embedded ERP will displace any ‘analytic AI’ because AI-embedded ERP will carry out ‘analytics’ on the data captured by the software. DSS stands for decision support system, which used to be a critical feature in any software and invariably an influential factor in the decision to buy. As I have written earlier, the importance of DSS lies in the fact that the analytics stayed within the system.
Many software products companies such as SAP claim to have incorporated AI begging the question as to whether a separate analytics software is necessary at all. Will the embedding of AI within ERP will spell the death of ERP analytics? This is certainly an interesting space to watch.
Not just tech alone
There are many estimates of the size of the AI products and services market and each runs into trillions of dollars, but we are not getting into the merits of these estimates. Since the process of economic reforms, many estimates were made of many factors with many proving to be considerably inaccurate. In this case too, many estimates will fall by the wayside, as has happened in many a product.
One caveat. The experience of LTE and Wimax as well as GSM and CDMA are stellar examples demonstrating that superior technology does not necessarily emerge the winner. CDMA and Wimax were the superior technologies but the market was captured by GSM and LTE, because services could be launched earlier with these two than the other two.
Asking ‘Who will win the AI race for market domination?’, Xavier Ferràs Associate Dean of the Executive MBA at Esade, a business school (October 2023), notes that “The competition is fierce, with giants Amazon, Microsoft, Apple, Google, Facebook, NVIDIA and Oracle leading the way. But who will be the VHS victor, and who’s resigned to Betamax history? It’s difficult to assess which company is emerging as producing the dominant design without the benefit of hindsight; Nokia phone fans may testify”. (The reference to VHS is extremely educative for students of management.)
Products, Platforms, Service
AI is not an unified market just as are most markets, which is a cautionary warning against a sweeping generic approach to building a business in AI. Products Vs Platforms is one dimension and within products there will be others depending on what the product is designed for. The competitive edge has to be separately found in every single case; there is no one all-encompassing solution. Platforms will initiate a debate over open and closed architectures and products will involve questions of modularisation. Whether products will be sold as products or as services through the SaaS mode is yet another open question, including whether on the cloud or with dedicated data centres.
Products can be focused but must facilitate easy integration with other software products in customers’ systems to produce intended results. Platforms have to appeal to a broad range of customers without losing the technological sharpness, balancing scale and technology, as the chips business has taught us.
The enormous challenge to repeat the success of TSMC (in the chips business) is an education by itself – an education in designing a technology platform and an education in attracting customers. Not very sharply defined as to exclude a majority, not too loosely defined as to be unattractive from a technology perspective. Those who crack this will emerge winners.
Since we are in the speculation phase, I will wager that anyone who thoroughly grasps the chips market to fine tune AI products/services with the accompanying aspects of architectures, standardization. The business model will eventually be a process of discovery. The business model per se is not the most pressing question; it is the specific balancing between technology and technique, technology and users that should occupy attention and focus.
There is more to this and I will return to this in my next writing.
