Generative AI is just a wake-up call for what has always been inevitable. Including incalculable profit.

AI and machine learning (AI/ML) will unleash history’s greatest profit engine as expensive human-managed processes are replaced with cheaper and more efficient digital processes. What we’ve seen so far – including generative AI (like ChatGPT) – is just the beginning of how AI/ML will transform and reinvent business – which is why companies will invest whatever it takes in intelligent systems.

Inevitable results

Let’s start with some results. AI and Machine Learning (AI/ML) will:

  • Change business processes and entire business models forever.
  • There is no doubt that thousands if not millions of jobs will be replaced.
  • accelerate corruption.
  • Make our homes and offices more efficient.
  • Replace teachers and medics, including surgeons.
  • Steal and create more money than is imaginable today.
  • Eliminate car salesmen, accountants, recruiters and lawyers.
  • Transforming – and reinventing – production, manufacturing, supply chain management and entertainment.
  • Enable offensive and defensive warfare.
  • Strengthen social, political and economic surveillance.
  • change transportation.
  • enable genetic research.
  • Increase misinformation and disinformation.
  • Increase agricultural production at a lower cost.
  • Reduce – and worsen – climate change.
  • manage water distribution.
  • Increase in wealth and income inequality.
  • Enable technology oligarchies.
  • Challenge competitive advantage and so many other business strategies, models and processes.

Of course, there are more results, but this list sums it up. Keep in mind that many of the applications today are in tightly constrained areas – such as B. accept/decline loans – that definitely save money and increase accuracy with simple, easy-to-train regression models. But tomorrow’s applications will augment with much more adaptive and powerful algorithmic approaches and interfaces (like chatbots) that make the algorithms accessible to everyone. Whole new industries will emerge as older ones die. Disruptive “progress” sure.

Unimaginable profit

Let’s pause here for a moment to honor them raison d’être of all businesses: Profit. AI will change, replace and automate entire industries. Those who make money from online digital retail, production, manufacturing and distribution will make heaps of money on the profit margins that digital efficiencies deliver.

AI/ML will unleash the greatest profit machine in history as expensive human-managed processes are replaced with more efficient ones. While we used to believe that the so-called knowledge industries are relatively devoid of what AI has to offer, we now know that the true goals of AI/ML Are the knowledge industries (in addition to the more industrial and corporate industries).

show horses

Sometimes show horses are fabulous. Generative AI is a fabulous show horse. I love it for that reason alone, but am still amazed at its capabilities. But show horses can also be wake-up calls. ChatGPT-3 is an interface to the ever-expanding ocean of data to be answered, solved, created and viewed. It creates descriptions, explanations, predictions and recipes – all by accessing a growing amount of data. That – along with embedded connectivity and inferencing – does the trick. But don’t think of generative AI as the “answer” or where AI was always supposed to go. It’s just a step toward increasing power and influence.

where vs how

We are heading towards the results listed above. Generative AI will enable some of these outcomes. But there is more under the covers that AI/ML will enable to enable “how” all of this is done.

  • Some of the technologies that AI will both create and use include:
  • Data integration in real time
  • API generation and integration
  • Network configurability and reconfigurability
  • Adaptive cyber security and cyber warfare
  • Operational technology management, including cloud optimization and management
  • Integrated sensors
  • data as a service; operation as a service; Strategy as a Service
  • Prescriptive Analytics as a Service
  • Automated application development
  • maintenance and repair

Again, there are other examples, but these should get to the heart of the matter.

Food for thought or time to act?

While many would disagree with the picture I have drawn here, many would agree. Managers have a decision to make. You can assume that “inevitable” may be true, but you still have plenty of time before the world changes as dramatically as I’ve described here. That’s what most leaders do: they put big decisions on future leadership. They claim there is plenty of time to think, analyze and observe; that there is no need to panic. In that case, they would be wrong. It’s like climate change, isn’t it? Some believe we have decades to address it, while others believe the time to act has already passed.

Executives should assume that the impact of AI/ML will not increase gradually, but at a pace that will directly impact their business model and processes over the next 2-3 years. Which operational and strategic processes are influenced by the entire range of AI/ML methods, tools, techniques and platforms? That’s the question leaders should be asking – now. (You could also spend some time looking at climate change.)

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