Progression of Machines
The Industrial Revolution, referred to as a turning point in history ushered in an era of mechanization. Goods were produced using machines e.g., steam engines used steam pressure to perform mechanical work and it powered factories, mining operations, and also used to power trains for transportation.
The 20th century introduced innovation in machine technology such as electricity, computing and electronics. Machines such as the telephone, typewriter and automobile are available for individuals which transformed the way we communicate and move from one place to another.
The digital age came with an innovation, namely computers, which evolved from smaller devices to more powerful devices changing the way we work and communicate. The introduction of the Internet, and in more recent times artificial intelligence have brought about technology that was thought impossible years before. We now have AI-powered electronics and more advanced computing systems, etc
This recent technology includes Machine customers, and in its fullest capacity, it would shift from humans engaging in self-service or instructing machines to granting machines the authority to act dependently or autonomously as customers. In many industries machine-to-machine interactions are already fully operational.
In industrial IoT, IoT systems utilize sensors to collect information about equipment, and processes in real-time. For example, sensors can detect issues and predict maintenance needs.
Decision-Making: Machine customers would be able to make data-driven decisions using market trends, behavioural patterns, historical data, etc. The machine customer can make purchasing decisions and take into consideration different components like price, product availability, quality, user preferences, etc
Predictive Ability: Machine customers can predict needs and make decisions. For example, an industrial system can detect if a particular ingredient for production is about to run out and make a request to purchase a refill. The predictive capabilities ensure that everything regarding production runs smoothly.
Learning and Adaptation: Machine customers can learn from previous interactions using AI and machine learning, and can also adapt to the changing market or user needs.
Efficiency: Unlike human’s machines work tirelessly, making them less likely to be fatigued and they perform tasks effectively compared to humans who are prone to errors.
Security: Machine customers are created with security in mind, they can protect against disinformation and also securely interact within or with other systems.
Autonomous Vehicles: Autonomous Vehicles or self-driving cars communicate with payment systems using IoT technology to make real-time decisions like paying for tolls, and parking without human interference.
IoT Devices: A smart refrigerator, for instance, uses IoT sensors to track inventory, integrated with an e-commerce platform to make orders when items are about to run out.
Modern Printers: Paper printers can determine when their ink has run out and purchase a cartridge independently.
Automated Trading System: These trading systems are linked to a direct access broker and use predefined criteria to buy or sell stocks. They interact with stock exchanges to execute trades without human intervention.
Everything has its downside, and for machine customers the limitations include;
Job Displacement: There’s a concern that machines could cause job displacement. For example, AI-powered chatbots are replacing human customer representatives, and in industries like manufacturing, machine customers can perform tasks like placing orders or completing transactions faster and more efficiently than humans, possibly reducing the cost of labour.
Security Exploitation: Machine customers can be exploited by hackers, there may be vulnerabilities that allow these hackers to steal sensitive data, hijack transactions or disrupt operations leading to financial, and loss of reputation amongst others.
Flawed Data: Machines rely on data to make decisions therefore if the data is incorrect, or incomplete this may lead to incorrect decisions and outcomes. It can make the machine customer inefficient which leads to dissatisfaction and security risk.
Ethical Concerns: Ethical concerns arise in the use of AI in customer transactions especially concerning manipulation and decision making. AI can be customed to use techniques to manipulate individuals in making decisions.
With the introduction of machine customers, would businesses start to appeal to humans or machines?
This is quite interesting because businesses would be machine-focused, and a lot of adjustments would be made in the processes that involve machines and humans.
According to staffing industry analysts quoting the World Economic Forum, businesses will divide work between humans and machines equally. 80% of business executives are planning to digitize work processes and 50% are planning to make some roles automated. Even with the concern of machines replacing humans, the World Economic Forum reported that the robotic revolution would create 97 million jobs.
While machines are taking over certain tasks, they are creating new jobs for humans that may involve humans working alongside machines or performing roles that machines cannot handle.