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What is the Fourth Industrial Revolution?
The Fourth Industrial Revolution (4IR) describes how modern technologies like artificial intelligence, big data, robotics, virtual reality, and 3D printing bridge the gap between the human experience and its digital counterpart. It’s a dramatic leap in manufacturing and productivity, changing the way we work, live, and interact with one another in real time through software, analytics, connectivity, and human-machine interaction.
Also referred to as Industry 4.0, 4IR builds on the Third Industrial Revolution (or digital revolution), which began in the 1950s with automated machinery and the first wave of digital technologies, including computers, the Internet, and household electronics.
In 2011, 4IR was first introduced by a team of scientists developing advanced technology for the German government. Klaus Schwab, founder of the World Economic Forum, brought the term into wider circulation with his 2015 Foreign Affairs article titled “The Fourth Industrial Revolution” and further the following year after publishing his book of the same title.
In the same way the First Industrial Revolution revolutionized production with steam and mechanical power, the Second Industrial Revolution harnessed mass production through electricity, and the Third Industrial Revolution used electronics and information technology to automate production, 4IR is characterized by a fusion of technologies blurring the boundaries between the physical, digital, and biological.
- Industry 4.0
What Technologies are Driving 4IR?
The Fourth Industrial Revolution is creating a world of smart machines, advanced robotics, autonomous systems, and pervasive networks. At its core are the following eight technologies:
Faster Computer Processing
The exponential growth in computer processing power over the past decades —following Moore’s Law — has been a critical enabler of 4IR. Modern processors now possess capabilities several orders of magnitude greater than their predecessors, such as machine learning and natural language processing (NLP).
This leap in technological innovation has enabled process automation and the development of Everything-as-a-Service (XaaS), whereby customers access highly scalable software, services, and data through subscription-based platforms.
In the future, quantum computing will take processing speeds even further, creating complex data models in seconds and finding solutions to abstract problems that traditional computing can’t yet solve.
Big Data Analytics
The ability to manage, process, and analyze large volumes of data — often in real-time — has allowed businesses to extract valuable insights and make informed decisions.
In the financial services industry, for instance, faster processing capabilities have given birth to high-frequency trading, where millisecond differences in processing times can translate to significant competitive advantages.
Machine-learning algorithms, driven by advanced processors, now analyze market trends, make predictions, and execute trades at lightning-fast speeds, redefining the landscape of global finance.
In everyday life, companies use big data to improve the customer experience, deliver personalized product recommendations, and suggest relevant content.
Artificial Intelligence (AI)
AI, another offshoot of the processing boom, has disrupted traditional business models across various sectors.
Deep learning algorithms, once computationally prohibitive, can now be trained on large datasets in a feasible timeframe, leading to innovations like IBM Watson and Google’s DeepMind, which can exhibit human-like decision-making capabilities.
AI is also being used to automate repetitive tasks traditionally performed by humans, such as data entry, customer service, and security monitoring.
Thanks to big data and rapid computer processing, AI can also accomplish new tasks humans themselves can’t carry out, such as facial recognition, sentiment analysis, and personalization at scale (e.g., algorithmic targeting).
Robotics stands as one of the clearest testaments to 4IR — it has gone from machines executing simple production tasks to sophisticated systems performing intricate operations. And now, it is not only revolutionizing industries but also enhancing the quality of human life.
Human safety is in the hands of robotics at some of its critical moments, such as in aerospace, mining, and surgical operations. In others, like B2B manufacturing and warehouse automation, robots eliminate certain safety risks altogether.
An industry set to grow 21% each year, 3D printing adds a physical element to computer-aided design (CAD), allowing manufacturers to create prototypes and one-of-a-kind items quickly and cost-effectively.
Its inherent flexibility means it requires less expensive tooling than traditional manufacturing methods, dramatically reducing the capital investment needed to produce a diverse range of products (and the R&D required to develop a new one).
Rapid prototyping capabilities also cut production times, enabling quicker time-to-market and fostering an environment of rapid innovation and customization on a scale previously thought unattainable.
Blockchain technology is the backbone of cryptocurrencies like Bitcoin. But it has many applications beyond that, including:
- Smart contracts — immutable, automated agreements between parties that can execute transactions without human intervention
- Decentralized autonomous organizations (DAOs) — a digital representation of a business, community, or microeconomy that can self-execute operations and manage assets without the need for a centralized authority
- Tokenization — the process of converting real-world assets into digital tokens that can be bought, sold, or traded using blockchain technology (e.g., NTFs).
- Secure data storage and transfer — offering a layer of security against cyberattacks
- Distributed ledger technology (DLT) — used for distributed, verifiable, and immutable record-keeping
These technologies enable the transfer of value without a trusted third-party intermediary, reducing transaction costs and bringing efficiency and transparency to financial markets.
They’re also used to store digital identities, manage intellectual property, and streamline supply chain processes.
Blockchain technology isn’t just important for its financial applications, but also as a tool to facilitate secure data transfer and storage. On a blockchain, data is distributed, encrypted, and immutable, meaning it can only be accessed by authorized parties.
In that sense, it’s the ideal solution for storing sensitive consumer or enterprise information.
Web3, often referred to as the “decentralized web” (and grouped together with blockchain), is a term that encapsulates modern technologies like blockchain, distributed computing, and peer-to-peer networks.
These technologies enable applications to operate on a network of computers without the need for a centralized server, which provides users with more control over their data than ever before.
Web3 also allows developers to build autonomous systems that interact with each other directly, connecting different devices and platforms in an interconnected web of trust.
Take the current web as an example: users interact with centralized services like Google and Facebook.
The “problem” with this model is that users give up control and data privacy in exchange for the ability to use their platforms.
Web3 (which is still in its infancy) aims to change this, allowing users to interact directly and securely with distributed applications.
Its current problems include scalability, usability, and carbon emissions. Even at the scale it currently operates at, producing the amount of energy required to power its networks has a significant environmental impact.
Nanotechnology is a field of science that deals with matter at the atomic level, manipulating individual atoms and molecules to create new materials.
Already used in electronics, biomedicine, energy production, information processing, and other industries, it has vast potential for further development.
For example, a biotechnology firm could use it to construct microscopic robots capable of entering cells to repair tissue damage or develop miniature solar cells capable of harvesting energy from the sun.
Through increasingly smaller microchips and semiconductors, nanotechnology is one of the primary reasons for faster computer processing. In that way, it facilitated the creation of the entire Software-as-a-Service, cloud computing, and artificial intelligence ecosystems.
Connectivity, Internet of Things (IoT), and 5G
The Internet of Things (IoT) describes the increasing communication between objects, facilitated by computing and connectivity technologies. The way computers were first used to connect people, they now help objects “think” and “talk” to one another.
IoT has streamlined supply chains since the early 2000s, but its usage is growing exponentially thanks to 5G networks. 5G offers faster connection speeds and reduced latency (the time between requesting data and receiving it), which improves response times between interrelated objects.
In the near future, it will monitor and optimize virtually everything — from medical devices to building infrastructure — all through interconnected networks of sensors.
Virtual Reality (VR) and Augmented Reality (AR)
VR and AR are two related technologies that allow users to interact with digital content in a simulated environment.
VR offers an immersive experience, allowing people to explore virtual worlds and interact with objects as if they were real. It’s already been used in various industries, including gaming, entertainment, healthcare, education, manufacturing, and business.
The most recognizable example of VR is the headset, which provides users with a suite of sensors and software to simulate physical spaces.
AR builds on this concept by overlaying digital elements onto the real world. It’s used in industries like construction, engineering, marketing, retail, tourism, and gaming.
Amazon’s AR View, for example, allows customers to visualize furniture and home décor in their own space before they buy it.
How the Fourth Industrial Revolution Affects Businesses
An important distinction between 4IR and its three predecessors is how completely it permeates all aspects of business operations. Whereas the first three Industrial Revolutions only affected certain parts of production (steam, electricity, electronics), current technologies driving 4IR impact every aspect of a business — from product design and supply chain management to customer service and support.
At the heart of 4IR is a profound shift in how businesses operate and deliver customer value. It involves an in-depth, systematic overhaul of systems, processes, workflows, and corporate culture.
Digital transformation isn’t limited to a single department or function, either. It infuses each organizational level, enhancing companywide collaboration and effectiveness.
Consider the enhanced data flow between CRM software and an ERP system in a digitally transformed business. Traditionally siloed, they now interact seamlessly, providing a holistic view of each customer from initial contact and sales to post-sales support and service (in addition to internal business processes).
With tools like McKinsey’s Dynamic Deal Scoring, digital transformation also unlocks the potential of predictive analytics. Business leaders can use advanced analytics to predict future trends and behaviors to focus on the right sales opportunities, drive marketing campaigns, and support customer success.
Depending on the type of organization, automation might look different.
- In a manufacturing context, automation involves using robots and other machines to reduce manual labor.
- In logistics, it might involve autonomous delivery trucks or unmanned aerial vehicles (UAVs) to deliver goods more efficiently.
- On the retail side, automation could be used to track customer behavior and preferences so businesses can personalize products and services in real-time.
- For sellers, sales automation scales customer interactions, centralizes communication, scores leads, and helps reps deliver more value to their prospects.
- Billing and accounting departments automate payments and invoicing to reduce manual labor and eliminate common bookkeeping and payment collection errors.
Because of how commonplace software has become, most businesses use automation in ways they don’t even realize.
CPQ software, for example, generates quotes and contracts automatically. Though a seemingly small accomplishment, it saves sales teams hours of manual work each week.
Roughly 92% of employees work remotely at least one day, but the concept of a distributed workforce won’t always be what it is today.
A distributed workforce is a model where employees aren’t physically co-located in a single office space. Instead, they span across multiple cities, countries, or even continents. To manage this effectively, businesses rely on digital tools to collaborate and communicate instantaneously, irrespective of geographical boundaries.
Cloud-based technologies have particularly played a critical role in enabling the distributed workforce by allowing for secure access to critical work applications and data from any location, fostering collaboration and ensuring seamless workflow continuity.
Collaboration platforms like Slack and project management tools like Asana have made it possible for teams to collaborate, share documents, and manage projects irrespective of their physical location.
For businesses, a distributed workforce can offer multiple advantages. Businesses lose $600 billion per year due to workplace distractions, and a fully-enabled distributed workforce is generally 35% to 40% more productive, according to Global Workplace Analytics data.
Diversity also brings broader perspectives and skills, fostering innovation and competitiveness. Plus, it results in significant cost savings by reducing or eliminating the need for office space, utilities, and other overhead costs.
Product development is one of the most impactful areas for 4IR. With rapid advances in machine learning, businesses can use 4IR technology to create and test products faster than ever before, whether they’re software or physical.
- Software developers enlist the help of AI-powered development tools like Amazon Machine Learning to identify patterns in large datasets and automate feature engineering tasks. They can also use Environment-as-a-Service (EaaS) to instantly deploy test environments in the cloud.
- Manufacturers employ generative design tools, which leverage AI and machine learning principles to automate product development processes. These platforms create 3D product models optimized for specific performance criteria.
- Industries like aerospace, healthcare, construction, and industrial machinery use additive manufacturing to produce complex, high-precision parts in a fraction of the time.
In addition to faster time to market, product development is less of a guessing game with 4IR. AI-powered analytics can be used to monitor customer usage and satisfaction levels of products in real time, providing businesses with invaluable insights for future iterations.
New Business Models
The macro trend that underscores all these changes is a paradigm shift — new business models are emerging as a result of abundant technology.
Flexible Consumption Model (XaaS)
Instead of a one-time product or service purchase, the flexible consumption model allows customers to pay for what they use, often on a subscription basis. The shift towards flexible consumption (which is only possible thanks to automated technology) gives customers more choice, scalability, and adaptability while offering businesses a steady stream of recurring revenue.
The most recognizable examples of the XaaS model are in the software industry, with Software As A Service (SaaS) offerings like Salesforce and Microsoft 365. But with the rise of the 4IR, this model is rapidly expanding to other sectors.
Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS), and Mobility-as-a-Service (MaaS) are gaining traction. The latter represents the shift in the transportation industry towards integrated, multi-modal services users can access on demand (e.g., Uber, Lyft).
The “Circular Economy” focuses on sustainability by reusing and recycling resources. Enabled by technology, businesses can create closed-loop systems where waste from one product becomes input for another.
For example, an advanced manufacturing company might use 3D printing to turn recycled materials into new products, minimizing waste and lowering costs.
In the same way, businesses can use connected sensors to monitor resource usage and optimize efficiency.
Businesses like Uber, Airbnb, and Kickstarter leverage the power of the crowd — whether it’s providing services, sharing assets, or funding ideas. Enabled by digital platforms, these businesses bring together large groups of people to create value in ways that were not possible before the 4IR.
In an increasingly digital economy, this model is among the most valuable because it enables others to make money. Uber, for example, provides convenience to its riders but also a simple and accessible side hustle to anyone with a car.
Since every business relies on big data to drive decisions, it’s essentially a new currency. For many businesses, it’s the biggest revenue driver.
Research and consulting firms like McKinsey and Forrester collect, aggregate, and analyze data to provide insights or make predictions. Often leveraging AI and machine learning, these companies can offer personalized recommendations, trend analysis, or predictive services, becoming invaluable partners in decision-making processes.
Other companies seemingly offer a tangible product that drives their revenue, but monetize their data behind the scenes.
Tesla, for example, collects data from hundreds of thousands of cars on the road. All this data is fed to their AI models and makes the company’s autonomous driving technology more precise. Eventually, it will sell this data to other car companies that want to enter the autonomous vehicle space but lack the technology to build their computing systems.
Supermarket chains are another example. Although they offer free membership programs with huge discounts to customers, they’re really just collecting data on buying habits. Losing a seemingly large amount of store revenue is with it because they can use this data to understand consumer preferences, target promotions, and optimize product selection and placement.
People Also Ask
What are the benefits of 4IR?
The benefits of 4IR are multifold and difficult to quantify. They improve the human experience by making it more convenient, safe, and efficient. 4IR also contributes to cost savings in areas such as infrastructure, product development, and operations due to automation and machine learning. In addition, it opens up new business opportunities by enabling the emergence of innovative business models such as XaaS (e.g., SaaS) and data brokerage.
What are the challenges of 4IR?
According to Klaus Schwab, the term’s de facto creator, the biggest challenge of 4IR is its potential to uproot labor markets. When automation renders certain skills obsolete, it could create a massive gap between “high skills/high pay” and “low skills/low pay” jobs. Other challenges include international regulation, privacy concerns, and intellectual property rights.