Redefining Commerce: The Emergence of Machine Customers
It is not an overstatement to call 2023 the year of Generative AI. The technology market debates the limitless possibilities of Generative AI every day. According to the “Top 10 Strategic Technology Trends for 2024,” published by Gartner, Inc. in October 2023, this trend is expected to continue in 2024, and further democratization of Generative AI is anticipated. That 10-trends list also includes other AI-related technologies such as “AI Trust, Risk and Security Management” and “AI-Augmented Development.”
Along with those technologies, another interesting term was mentioned: “Machine Customers.” According to Gartner, machine customers are nonhuman economic actors who can autonomously negotiate and purchase goods and services in exchange for payment. Based on their forecast, by 2028, there will be 15 billion machine customers (more than the world’s population) and by 2030, they could be a source of trillions of dollars in revenue. Machine customers are positioned in the innovation trigger phase in the Hype Cycle for Supply Chain Strategy, 2023, of Gartner.
Today, I will explore what “machine customers” are and what business impact they would have, in this article. To simplify Gartner’s definition, machine customers are computers (or software) that purchase products and services on behalf of humans. IoT devices, represented by Amazon Alexa or AI assistants, could be considered forerunners. What use cases of machine customers do we come up with? For example, an autonomous vehicle could locate the nearest repair shop and request repair services by itself when it detects or predicts abnormalities in it like tires. A smartwatch might notice a person losing consciousness on a deserted street and request emergency services immediately.
Decision-Making Process of Machine Customers
The difference between machine customers and humans is the decision-making process. While machine customers make decisions based just on statistical data and logic, humans could be influenced by emotions, memories, or opinions of other people. In that sense, machine customers are extremely rational buyers and excel at making quick decisions. Because they also have a much larger memory capacity than humans, they can make decisions based on more objective and reliable evidence. Another characteristic of machine customers is that they keep users away from the annoyance of customer service up-selling and cross-selling, enhancing user safety. In summary, I believe the values of machine customers are as follows:
- Rationality
- Immediacy
- Reliability
- Safety
In an era where Spotify and Netflix dominate the market, and people prefer their personalized suggestions, I think people are seeking “ultimate efficiency.” They desire agents that suggest options that seem suitable for them in the most direct way possible. From this perspective, machine customers, who thoroughly eliminate “detours” like emotions and others’ opinions, might be the ultimate in efficiency and are likely to sweep the market in the future.
Gartner describes it as “machine customers’ purchase journey is linear.” However, compared to machine customers, Spotify and Netflix don’t eliminate detours. They propose content that users might like with a bit of randomness. This detour is one of the elements that attract people. In that sense, machine customers might cause a certain unease among users because they are too decisive. Hence, people might prefer machine customers that allow for some detours to completely linear ones.
Additionally, Generative AI is expected to contribute to the advancement of machine customers. Generative AI will not only become an interface for users but is also anticipated to enable more personalized machine customers by incorporating the user’s past choices and experiences as training data. This is the final stage of machine customers proposed by Gartner, known as “autonomous customers.” They would act independently on behalf of users, like digital twins for those users.
How Business Should Change
Businesses will also need to adapt to this change. Traditional interactions between companies and customers were of the following two types:
- Person to Person (P2P)
- Person to Machine (P2M)
However, with the introduction of machine customers, two more types of interactions would be added.
- Machine to Person (M2P)
- Machine to Machine (M2M)
In those interactions, conventional marketing and negotiation methods would become irrelevant. If machine customers, who operate faithfully according to logic and data, were to dominate the market, a market-in strategy would lose significance. In that case, only products thoroughly enhanced in a product-out way might survive.
From the sales side, B2B might become far more important than B2C. In the case of autonomous (and electric) vehicles, it is possible to guide the car to an EV charging stand that has already partnered with the car company. Similarly, vertical integration in companies might progress, surrounding the customers might become a mainstream strategy, and SMBs would stand in the challenging competitive environment.
Security would become more important. Since machine customers can access vital information such as users’ credit card details, many criminals would try to steal it Furthermore, if someone hacks and takes over a machine customer without the user noticing, they could manipulate his purchasing behavior at will.
To address those risks, machine customers need advanced security as well as monitoring and alert systems to detect anomalies. The more you start treating machine customers as your digital twins, the more you need to think about protecting them.
While it’s difficult to foresee the future impact of the rise of machine customers on consumers and businesses, those who discuss and prepare earlier on machine customers would acquire greater benefits.
