“A robot may not injure a human being or, through inaction, allow a human being to come to harm.
A robot must obey orders given to it by human beings except where such orders would conflict with the First Law.
A robot must protect its own existence as long as such protection does not conflict with the First or Second Law.”
Isaac Asimov's Three Laws of the Robotics
In the now thriving world of AI and robotics, almost everybody knows about the so-called ‘Three laws’ defining how an AI – an artificial intelligence created by humans – should behave.
Now, you are probably asking yourself: Why is this important for B2B organizations and for e-commerce in general? Well, it is vital. And today, we will share with you why it is vital, while, at the same time, painting a more than probable future where AI will drive global commerce with predictive efficiency and with almost non-human interaction in its daily operations. Sounds far-fetched? You will see it is not…
Let us begin!
The three laws of predictive commerce
Returning to our famous Three Laws of Robotics, which today serve as a set of rules for the behavior of artificial intelligence. These laws were not written by scientists involved in the early developments of AI, robotics, or even programming, but by a writer and professor of biochemistry at Boston University School of Medicine: The legendary Isaac Asimov.
In fact, they work so well that in March 2007 the South Korean government issued a “Robot Ethics Charter” to force AI manufacturers to follow rules based on Asimov’s Three Laws because they provide “a safer way to develop future AIs.”
Hans Moravec (a prominent figure in the transhumanist movement) also proposed adapting the laws of robotics to “corporate intelligence” – the AI that he believes will run companies in the near future.
A belief that is not only shared by Moravec, because in early 2011 the United Kingdom published what is now considered the first national AI soft law. This agreement consisted largely of a revised set of five laws, the first three of which are actually updated versions of Asimov's laws.
The point is that Asimov's Three Laws hit a nerve. They address a major concern we humans have about AI: Can artificial intelligence do more harm than good?
And without delving into the deep waters of philosophical debate, the answer is simple: A real AI can do just as much harm or good as a human mind.
So the next time you think about whether your company is safe in the hands of predictive AI, you might also take a moment to think about whether your company is currently safe in the hands of your own C-level executives, your employees – or even your hands.
The fact is that the use of predictive AI is inevitable. And it will happen sooner than you think. The same conclusion you came to a few lines above is the same one that thousands of managers, CEOs and business owners are slowly but surely coming to: AI can safely – or at least as well as humans – take responsibility for things.
Let’s take a closer look at how exactly your B2B business can benefit from predictive AI.
Predictive AI applications for B2B
A predictive AI is an artificial intelligence solution that is capable of producing accurate predictions based on previous data processing. It is, in a way, similar to the thought process a human being does if we were capable of being completely rational – removed of prejudices and biases – and as such, it is pretty accurate when done properly.
Keep in mind that we are not saying that a predictive commerce AI will be able to act autonomously. That’s a bit farther down the road for us still. Currently, predictive commerce is more about offering the human supervisor a plethora of options based on accurate predictions, rather than an AI sailing alone our B2B ship across the global markets.
That being said, predictive commerce has a lot of potential applications. Some of these will most likely become trends during 2024 and some of them even allow for a certain degree of ‘autonomous behavior’ on the part of the AI.
Let's take a look at a few of them:
Personalized product recommendations offered to your clients based on the AI-driven solution prediction of their tastes and preferences – extracted from their previous browsing data, website navigation behavior, purchase history, or online behavior – is one of the most widespread applications of predictive commerce, usually based on some sort of AI-driven solution. In fact, this is the engine behind Amazon and Temu's success.
Product discovery is directly derived from the previous one, and yes, it is different. Why? product discovery is evolving into a more predictive approach in the sense that product discovery engines will be used with first-time website users. This means that contrary to product recommendations, the AI may not have any insights into that particular user’s behavior. However, based on the collective data of all previous clients, the AI will make what we humans call ‘an educated guess’.
Dynamic pricing is another key component of predictive commerce. The use of omnichannel price management functionalities will allow B2B organizations to establish consistency, agility, and transparency in dynamic price strategies. Obviously, because speed is of the essence for this to work properly, dynamic pricing will benefit a lot from a semi-autonomous or completely autonomous scenario for our AI.
Predictive analytics is the last big area for predictive commerce. And it is a huge area. Predictive analytics are fundamental for the future of global commerce itself. AI technologies can allow any B2B organization to improve inventory management, sorting, and search results for your customers or for your purveyors, seasonal discounts, and seasonal logistics – for wholesalers who have seasonal peaks like Christmas or Black Friday – and can even help predict when will be the perfect maturity point to break into a new market.
Mr. Roboto, Head of Business Development
Precisely the last area, predictive analytics, is what we believe will surely become the future of predictive commerce: using an AI companion to provide accurate assessment of business decisions based on data-driven predictions.
In fact, following Gartner's report on the growth of AI Ops – AI use for Operations – AIOps continues its growth and influence on the overall ITOM market, with a projected market size of about $2.1 billion in 2025 at a compound annual growth rate (CAGR) of around 19%, which shows massive growth.
Now, this means that, in the near future, companies could feed a specially trained AI - that understands the logic and ways of its business models – with a massive stream of data – data we are constantly generating being internet daily users – to decide when a market should be entered, when to lower prices, or even when to strike a deal with the competition.
And probably – as our friend Asimov realized a few decades before anyone – this AI will be as harmful or as beneficial as any current CEO. In fact, many major tech brands are already pushing to make this a reality. So much so that according to Statista, the market for predictive analytics software was valued at 5.29 billion U.S. dollars in 2020 and is forecasted to grow to 41.52 billion U.S. by the end of 2028.
A massive leap of faith – and money invested in this technology - shows that we might not yet be in a world where AI will run massive global corporations, but we are certainly close to the point at which we should start thinking about which ones will be our B2B organization's own Three Laws…?
