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“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

Back to our now famous ‘Three Laws’ of Robotics, the first thing we need to tell you is that these laws were not created by scientists involved in the early developments of AI, robotics, or even programming. They were created by a writer and professor of biochemistry at the Boston University School of Medicine: the legendary Isaac Asimov. And mind it, as a basic set of rules for AI behavior, they do work.

In fact, they work so well that in March 2007, the South Korean government created a "Robot Ethics Charter” to force AI manufacturers to comply with a set of rules, based on Asimov's Three Laws because they will provide ‘a safer way to develop future AIs’ Similarly, Hans Moravec (a prominent figure in the transhumanist movement) proposed that the Laws of Robotics should be adapted to "corporate intelligences" — the AI he believes will be running corporations in the near future.

A believe that is not Moravec’s alone… because in early 2011, the UK published what is now considered the first national-level AI soft-law, which consisted largely of a revised set of 5 laws, the first 3 of which are, indeed, updated versions of Asimov's Laws.

The point is that Asimov's Three Laws hit a nerve; they highlighted a massive concern we humans have about AI: Can an AI do more harm than good?

And without entering into the deep waters of philosophical debate, the most straightforward answer is, in fact, pretty simple: a real AI can do as much harm or good as a real human mind.

So, the next time you are pondering if your business will be safe in the hands of predictive AI, you could also take a moment to ponder if your business is currently safe in the hands of your own C-level managers, your staff… or even yourself.

Do you see it now? Predictive AI use will happen. Sooner than later. Because the same conclusion you arrive at a few lines above is the same one thousands of managers, CEOs, and business owners are slowly – but surely – arriving on their own: AI can be safely – or at least as much as humans – in charge of things.

With this notion cleared, let us delve deeper into what exactly predictive AI can do for your B2B business.


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 2024.

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…?

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