As I take stock of it, the development of AI has been an ongoing progression.
The watershed moment, in my mind was the development of Excel. It replaced the need to add and subtract on paper ledgers, making data processing and storage far more efficient. Affordable memory, probably not part of progression, but equally important, replaced the need to store personal memories in the brain. In the last 15 years there has been the arrival of grammar checkers in word processing. And there is the common phenomenon of autosuggestion in messaging apps.
What AI does is supplement your ability to think and operate. That’s not a bad thing.
The choices that face you now are to think less and allow AI to do the work (copy and paste is a mediocre route), or to think better and deeper with the support of AI.
How does this work?
In my case, I used to search Google for baseline frameworks of knowledge, sometimes visiting thirty or forty pages to get an overview. After a day or a morning, I would have the framework and add my own insights. Nowadays, I can find the baseline in a minute or two using an LLM (large language model) AI, then begin to cross reference on grey areas and add my insights. That’s a remarkable efficiency gain. AI is here to stay.
The next iterations come in three phases. Firstly (currently), AI will develop in the context of search. Secondly, AI will become an individualized tool. Thirdly, enterprise AI will begin to market to individual AI.
SEO ethics is currently shifting to small data. To understand small data, consider algorithmic use of data on accounts such as Netflix or Kindle. These sites track your accounts to deliver personalized recommendations on movies and books. However, you will notice flaws. For instance, a horror movie fan may prefer supernatural horror movies to slasher flicks but still get recommendations for slasher flicks. Incorporation of AI will better identify nuanced choices according to observable behaviour on the user’s accessible online / electronic accounts.
Today, the early emerging thread is personalized AI. You are able to personalize and ‘own’ an AI that observes your behaviour and collects data on yourself. You train the AI on your own preferences and needs and it delivers content to you. For instance, if you go to a vehicle showroom, the AI geolocates your position, registers the type of car and then begins to deliver information on vehicle finance according to your financial means and personal behaviour. If you look at a business vehicle, it can theoretically deliver business advice and fleet finance information.
The third step is enterprise AI to individual AI. In this phase the enterprise AI communicates with your personal AI. The enterprise AI will be able to identify the questions you are likely to have and make recommendations on products based on enterprise product availability. In other words, without the laborious process of searching for scattered information, your own AI will deliver a) the content and b) the useful marketing you need. Your role is to say yes or no.
There is a hinge in this, which is development of personalized Ais. Given the prize of users, subscriptions and marketing budgets, I doubt it will take long.
This fundamentally changes the role of marketers to persons who can identify and analyse significant user behaviour, then develop the enterprise AI. It’s a brave new world ahead.
*Pierre Mare has contributed to development of several of Namibia’s most successful brands. He believes that analytic management techniques beat unreasoned inspiration any day. He is a fearless adventurer who once made Christmas dinner for a Moslem, a Catholic and a Jew. Reach him at pierre.june21@gmail.com if you need help.
