The Machine Economy evolved from years of rapid developments in society and the transition toward new manufacturing processes. The First Industrial Revolution (the 1760s) saw advances in mechanization, where society shifted from an agrarian to an industrial model. The Second Industrial Revolution (the 1870s) took us a step further, with electricity enabling mass production. The Third Industrial Revolution (the 1990s) saw the introduction of digitization, automation, and connectivity through the invention of computers and the internet.
Today, the convergence of emerging technologies is accelerating the pace of change and bringing us to the edge of the Fourth Industrial Revolution – where the physical and digital world meet. Digital information is continuously materializing from the real world due to the Internet of Things (IoT), cyber-physical systems, and the merger of man and machine.
As we move toward this new automated future, the Machine Economy will influence our daily lives in many ways and unlock trillions of dollars in business value. Connected machines will have the ability to lease themselves out, hire maintenance engineers, and pay for replacement parts. Each machine will have different capabilities, but with one common thread tying them all together — producing and consuming goods and services with one another.
An Equation for The Machine Economy
To understand how the Machine Economy works, we need to grasp its underlying core technologies. Machines are capable of conducting transactions through the convergence of three developing technologies:
- Internet-of-Things (IoT)
- Machine Learning (as part of Artificial Intelligence)
With the number of IoT devices set to reach 75 billion by 2025, this provides the necessary functionality through internet connectivity to enable machine-to-machine communication (M2M) between smart sensors and devices. Forecasts suggest that M2M connections will increase from 33% in 2018 to 50% (14.7 billion) by 2023.
In combination with the real-time data produced by IoT, blockchain, and ML applications are disrupting B2B companies across various industries from healthcare to manufacturing. Together, these three fundamental technologies create an intelligent system where connected devices can “talk” to one another. However, machines are still unable to conduct transactions with each other.
This is where distributed ledger technology (DLT) and blockchain come into play. Cryptocurrencies and smart contracts (self-executing contracts between buyers and sellers on a decentralized network) make it possible for autonomous machines to transact with one another on a blockchain.
Devices participating in M2M transactions can be programmed to make purchases based on individual or business needs. Human error was a cause for concern in the past; machine learning algorithms provide reliable and trusted data that continue to learn and improve — becoming smarter each day.
Data: Key Resource
As we enter an era of radical automation with billions of connected machines, businesses can increase operational efficiency by eliminating manual processes, enabling them to instead focus on value-generating services. With IoT gathering, analyzing, and storing large amounts of data, companies turn information into actionable insights, making more informed decisions that build and sustain a competitive edge.
The Machine Economy opens the door to new business opportunities, but what it comes down to is leveraging data as a valuable asset. In the context of the Machine Economy, four significant stages are emerging to create a new order of business.
Machines are becoming multi-faceted, with sensors, self-monitoring tools, and highly sophisticated communication capabilities. Our everyday tools are becoming highly connected, from consumer goods like fridges and smart locks to autonomous vehicles. Self-monitoring machines will execute services like maintenance, arranging their own insurance, and making decisions without the need for human intervention.
In the third step toward smart services, businesses will move away from buying machines outright. Instead, we’ll see the sharing economy, subscription models, and real-time leasing emerge with self-managed assets sharing their services in a decentralized ecosystem. In the final stage, machines will become increasingly autonomous market participants with their own bank accounts and payment systems that have been built and programmed to support humans on an existential level.
Benefits of the Machine Economy
The Machine Economy promises significant benefits for people, businesses, and the broader economy by:
- Reducing costs and increasing revenue: For example, IoT enables industrial equipment manufacturers to implement process automation, just-in-time (JIT) manufacturing, remote monitoring, and predictive maintenance.
- Improving operational efficiency: M2M sensors enable organizations to monitor and track assets right from inventory across the entire supply chain.
- Creating new value: New marketplaces, industries, and business models will emerge (e.g. “as a Service” business models).
- Mitigating risks associated with owning assets: Reduces the need for businesses to own, maintain, and manage assets.
- Resulting in positive gains across the sales funnel: As the utilization of shared machines increases, this leads to cheaper products and services as cost per unit decreases.
- Transitioning from CapEx to OpEx: Companies can hire/lease out equipment based on specific needs and planned production cycles. By saving on the large upfront investment cost of purchasing machines outright, new businesses can participate as a result of reduced barriers to entry.
- Strengthening workforce and output: With a shortage of skilled workers and increasing complexity, IoT and complementary technologies can support employees in working on machines.
- Increasing transparency through data: The adoption of smart sensors enables companies to strengthen their domain knowledge to satisfy consumer needs and improve on sustainable business practices.
Machines Enable the World of Tomorrow
The future of the Machine Economy can be divided into two forthcoming scenarios.
Decentralized Autonomous Organizations (DAOs)
DAOs tackle the age-old problem of governance and are designed to operate without human oversight by using a model underpinned by a network of smart contracts on a blockchain (e.g., Ethereum). In business, we will likely see many more DAOs emerge in smart property management, autonomous vehicles, and financial services to enable companies to automate parts of their business to achieve rapid scalability without sacrificing the quality of service.
As automation takes over production systems, entire factories will be driven by machines optimizing themselves, communicating with each other, and responding with root cause analysis (RCA) that identifies the origin of problems and develops an approach to solve them with no human presence on-site.
Over the next few years, we will see a profound shift in industrial processes. There’s increased synchronization between different components across the value chain, and machines make decisions and independently react to the world around them. As we transition toward the Machine Economy, for businesses to truly leverage the opportunities that exist, we need machines to do more than automate mundane tasks. We need to add another layer to business solutions to create more value out of machines’ services.
With a backbone of disruptive technologies, machines will have the power to make their own decisions, buy and sell services, and actively participate in the economy as an entirely new class of market participants — the Machine Economy is on the horizon.