There are always emerging technologies and our digital landscape is ever-changing. There are eight essential technologies that are a focus of interest today and are said to be changing the world. In no particular order, these eight technologies are Internet of Things (IoT), Augmented Reality, Robotics, Artificial Intelligence, Blockchain, Drones, 3-D printing, and Virtual Reality. At the very least, a general awareness of these technologies is important for all members of society.
If you’re a business leader, your company is almost certainly using at least several of the Essential Eight emerging technologies right now. You’ll likely need to use others soon.
In 2016, we first identified the Essential Eight — settling on the crucial shortlist after analyzing more than 250 technologies in our labs. Since then, much has changed. Several of the Essential Eight have advanced so quickly that the value propositions they offer business have changed. Still other, newer technologies are now becoming instrumental. To help businesses assess where to direct strategic investments, we’ve updated the Essential Eight and organized them into three categories that reflect how business leaders can prioritize their efforts: expand, evaluate and experiment.
Artificial Intelligence
Internet of things (IoT)
Blockchain
Virtual Reality
Augmented Reality
Advanced Robotics
Quantum Computing
Neuromorphic Computing
Though the technologies are at different maturity levels, we believe all eight are essential. They’re also converging to deliver greater impact. While a single Essential Eight technology may help solve a business challenge, combining it with others may enhance the solution.
The right approach to the Essential Eight can help build trust with your stakeholders, prioritize key investments and drive convergence among these technologies that can lead to exponential value.
We are going to talk about the main ones over here such as: Technologies are Internet of Things (IoT), Augmented Reality, Robotics, Artificial Intelligence, Blockchain, Drones, 3-D printing, and Virtual Reality.
The Internet of Things (IoT) refers to the network of interconnected devices that can communicate and exchange data with each other over the internet without human intervention. These devices can range from everyday objects like household appliances and wearable devices to industrial machines and infrastructure components.
Key technologies that enable the IoT ecosystem include:
Sensors and Actuators: These are devices that gather data from the environment (sensors) or act upon it (actuators). Sensors can measure various parameters such as temperature, humidity, light, motion, etc., while actuators can perform actions like opening/closing valves, turning on/off switches, etc.
Wireless Communication: IoT devices typically communicate wirelessly using various protocols such as Wi-Fi, Bluetooth, Zigbee, Z-Wave, LoRaWAN, cellular (2G/3G/4G/5G), and others. The choice of protocol depends on factors like range, power consumption, data rate, and network coverage.
Cloud Computing: Cloud platforms provide scalable storage and computing resources for collecting, storing, analyzing, and managing the vast amounts of data generated by IoT devices. Cloud services also offer capabilities like data analytics, machine learning, and artificial intelligence (AI) for extracting insights and making data-driven decisions.
Edge Computing: Edge computing involves processing data closer to the source (i.e., on the edge of the network) rather than sending it to centralized cloud servers. This approach reduces latency, conserves bandwidth, and enhances real-time responsiveness, making it suitable for time-sensitive IoT applications.
Security: Security is a critical aspect of IoT deployments due to the potential risks associated with unauthorized access, data breaches, and cyber-attacks. Technologies such as encryption, authentication, access control, secure bootstrapping, and over-the-air (OTA) updates are essential for safeguarding IoT ecosystems.
Interoperability Standards: Interoperability standards ensure that IoT devices from different manufacturers can seamlessly communicate and work together within the same ecosystem. Standards bodies like the Institute of Electrical and Electronics Engineers (IEEE), the Internet Engineering Task Force (IETF), and industry consortia develop and promote these standards.
Data Analytics and Machine Learning: IoT generates large volumes of data, and extracting actionable insights from this data is crucial for optimizing operations, improving efficiency, and enabling new services. Data analytics techniques, including machine learning and AI, are employed to analyze IoT data and derive meaningful patterns, trends, and predictions.
Blockchain: Blockchain technology can enhance the security, transparency, and integrity of IoT systems by providing tamper-proof and decentralized ledgers for recording transactions and data exchanges between devices. It can be particularly useful in applications where trust and auditability are paramount, such as supply chain management, smart contracts, and asset tracking.
** These technologies collectively form the foundation of the IoT ecosystem, enabling a wide range of applications across industries such as healthcare, transportation, agriculture, manufacturing, smart cities, and home automation. **
Click in the next video to have a better understanding IoT (Internet of Things)
Augmented Reality (AR) is a technology that overlays digital information, such as images, videos, or 3D models, onto the real-world environment. AR enhances the real world by adding virtual elements to it. AR technology typically involves the use of devices such as smartphones, tablets, smart glasses, or specialized AR headsets.
Key characteristics of augmented reality include:
Real-time Interaction: AR applications integrate digital content seamlessly into the user's real-world environment, allowing for real-time interaction with virtual elements. Users can view and interact with AR content as if it were part of their physical surroundings.
Spatial Mapping and Tracking: AR devices use sensors, cameras, and software algorithms to understand and map the user's surroundings. This enables accurate placement and tracking of virtual objects within the physical environment, ensuring that they appear stable and aligned with the real world.
Contextual Information: AR enhances the user's perception of the real world by providing contextual information and visual cues overlaid on physical objects or locations. For example, AR navigation apps can overlay directional arrows or labels onto streets and landmarks to assist users in navigating their surroundings.
Marker-based and Markerless AR: AR experiences can be marker-based, where virtual content is triggered by specific markers, such as QR codes or images. Alternatively, markerless AR utilizes spatial recognition and tracking technologies to anchor virtual content to real-world surfaces or objects without the need for predefined markers.
Applications across Various Industries: AR technology has diverse applications across industries such as gaming, education, healthcare, retail, marketing, manufacturing, and more. For example, AR gaming apps like Pokémon GO overlay virtual creatures onto the user's physical environment, while AR educational apps enhance learning experiences by providing interactive visualizations and simulations.
Wearable AR Devices: Wearable AR devices, such as AR glasses or headsets, offer hands-free access to AR content and experiences. These devices typically feature transparent displays that superimpose digital information onto the user's field of view, enabling seamless integration of virtual and real-world elements.
Remote Assistance and Collaboration: AR technology facilitates remote assistance and collaboration by allowing users to share their augmented view with others in real time. This enables experts to provide remote guidance and support by annotating and interacting with the user's environment from a distance.
The technology in action
Customer experience and engagement: AR is more than playing games. It can help your customers engage with virtual products and services, with virtual versions of physical products and with communities built around brands.
Training and education: AR is often used to provide interactive and context-specific experiences. It can enable remote assistance, allowing specialists to guide and support workers in real time.
Design and visualization: AR can help product designers, interior designers, architects and engineers visualize and manipulate virtual 3D content in the real world.
Augmented Reality is growing quickly to support training, onboarding, product demonstrations, and field service and maintenance. The convergence of AR with AI and IoT will likely help create more advanced and context-aware AR experiences. AI assistants will likely offer ever greater capabilities to act as note takers, researchers, coaches and executive assistants. Transferring between devices within an ecosystem will likely become ever more seamless.
Advanced robotics integrates artificial intelligence into robots so they can perform intricate tasks and autonomously interact and respond to real-world complexities. Leveraging deep learning and neural networks, these robots can process vast amounts of data, adapt to dynamic environments and make real-time decisions.
Advanced robotics is transforming complex, labor-intensive physical processes, enhancing productivity, workforce safety, reliability and data-driven decision-making.
Here are some key aspects of advanced robotics:
Artificial Intelligence (AI) and Machine Learning: Advanced robots are equipped with AI algorithms and machine learning techniques that enable them to perceive and understand their environment, make decisions, and learn from experience. AI enables robots to adapt to changing conditions, optimize their performance, and interact intelligently with humans and other robots.
Autonomy and Navigation: Advanced robots are designed to operate autonomously in dynamic and unstructured environments, without constant human intervention. They use sensor data, such as lidar, cameras, and radar, combined with advanced algorithms for mapping, localization, path planning, and obstacle avoidance to navigate complex terrains and perform tasks safely and efficiently.
Manipulation and Dexterous Control: Advanced robotic systems are capable of performing intricate manipulation tasks with a high degree of precision and dexterity. They are equipped with sophisticated end-effectors, such as robotic hands or grippers, that enable them to grasp, manipulate, and interact with objects of various shapes, sizes, and materials.
Human-Robot Interaction (HRI): Advanced robots are designed to interact with humans in natural and intuitive ways, whether it's through verbal communication, gestures, or physical collaboration. HRI technologies enable robots to understand human intentions, preferences, and emotions, fostering seamless collaboration and cooperation between humans and robots in shared workspaces.
Soft Robotics and Bio-inspired Design: Advanced robotics incorporates principles from soft robotics and bio-inspired design to create robots with flexible, compliant, and biomimetic structures that can adapt to complex and unstructured environments. Soft robots are capable of safely interacting with humans and delicate objects, making them suitable for a wide range of applications, including healthcare, rehabilitation, and exploration.
Multi-Robot Systems and Swarm Robotics: Advanced robotics often involves the coordination and cooperation of multiple robots working together as a team to achieve common goals. Swarm robotics focuses on the design and control of large groups of simple robots that exhibit emergent collective behaviors, such as self-organization, cooperation, and task allocation, to accomplish complex tasks more efficiently and robustly.
Applications: Advanced robotics has applications across various industries, including manufacturing, logistics, healthcare, agriculture, defense, and space exploration. For example, advanced robots are used in manufacturing facilities for tasks such as assembly, welding, and quality inspection. In healthcare, they assist surgeons in performing minimally invasive surgeries and provide support to patients with mobility impairments. In agriculture, robots automate tasks such as planting, harvesting, and monitoring crops.
Advanced robotics are increasingly becoming more accessible. Thanks to AI, it’s now easier than ever for people to “talk” to robots. This easier communication should foster unprecedented human-robot collaboration. Robotics-as-a-service is also a growing trend, since it can reduce the size of initial investments and enable more cost-effective flexibility and scalability.
Artificial Intelligence (AI) is a branch of computer science that focuses on creating intelligent machines capable of performing tasks that typically require human intelligence. These tasks include learning, reasoning, problem-solving, perception, understanding natural language, and interacting with the environment. AI technologies enable machines to simulate human cognitive functions and adapt to new situations without explicit programming.
Here are some key concepts and areas within artificial intelligence:
Machine Learning: Machine learning is a subset of AI that involves developing algorithms and statistical models that enable computers to learn from and make predictions or decisions based on data. Machine learning techniques include supervised learning, unsupervised learning, reinforcement learning, and deep learning. These algorithms are used in various applications, including image and speech recognition, natural language processing, recommendation systems, and autonomous vehicles.
Deep Learning: Deep learning is a subfield of machine learning that focuses on artificial neural networks with multiple layers (deep neural networks). Deep learning algorithms can automatically learn hierarchical representations of data by extracting features at different levels of abstraction. Deep learning has achieved remarkable success in tasks such as image and speech recognition, language translation, and playing games like Go and chess.
Natural Language Processing (NLP): Natural language processing is a branch of AI that focuses on enabling computers to understand, interpret, and generate human language. NLP techniques are used in applications such as sentiment analysis, language translation, chatbots, virtual assistants, and text summarization. Advanced NLP models, such as transformer-based architectures like BERT and GPT (Generative Pre-trained Transformer), have significantly improved the performance of language processing tasks.
Computer Vision: Computer vision is a field of AI that enables computers to interpret and understand the visual world. Computer vision algorithms can analyze and extract information from digital images and videos, enabling applications such as object detection, image classification, facial recognition, autonomous navigation, and medical image analysis. Convolutional neural networks (CNNs) are commonly used in computer vision tasks due to their effectiveness in learning visual representations from raw pixel data.
Reinforcement Learning: Reinforcement learning is a type of machine learning where an agent learns to make sequential decisions by interacting with an environment to maximize cumulative rewards. Reinforcement learning has applications in robotics, game playing, recommendation systems, finance, and autonomous control. Deep reinforcement learning, which combines deep learning with reinforcement learning, has achieved significant advancements in areas such as robotics and game playing.
AI Ethics and Bias: As AI technologies become more prevalent in society, concerns about ethics, fairness, transparency, accountability, and bias have gained prominence. Ethical considerations in AI include issues such as data privacy, algorithmic bias, autonomous weapons, job displacement, and the impact of AI on society. Researchers and policymakers are actively working to address these ethical challenges and ensure that AI technologies are developed and deployed responsibly.
CLICK in the next video! You will understand how exactly Artificial Intelligence works!
Blockchain can provide transparent, cost-effective and secure ways to store, monitor and transfer information and assets — helping enable new digital business models and revenue opportunities. Growing adoption, interoperability advancements and regulatory clarity are positioning blockchain to become a critical enabler of enterprise innovation and trust.
Blockchain is designed to seamlessly integrate with existing company systems, processes and data sources while also enabling trusted interactions between external ecosystem participants. Its decentralized nature can provide businesses with greater agility, flexibility and new, trusted ways to interact with customers, counterparties and other stakeholders.
The technology in Action
Blockchain technology has the potential to revolutionize various aspects of our economy and society by enabling trustless, secure, and transparent transactions and data exchanges.
Global payments
Asset tokenization
ESG enablement
Technology and data governance
Drones, also known as Unmanned Aerial Vehicles (UAVs) or Unmanned Aircraft Systems (UAS), are remotely operated or autonomous flying vehicles that can navigate through the air without a human pilot onboard.
Types of Drones:
Multirotor Drones: These drones have multiple rotors (usually four or more) and are highly maneuverable. Quadcopters, hexacopters, and octocopters are common examples of multirotor drones used for aerial photography, videography, inspection, and recreational flying.
Fixed-wing Drones: Fixed-wing drones resemble traditional airplanes and are designed for longer flight durations and higher speeds. They are commonly used for aerial mapping, surveying, agriculture, and surveillance over large areas.
Hybrid Drones: Hybrid drones combine features of both multirotor and fixed-wing designs, offering vertical takeoff and landing (VTOL) capabilities along with the efficiency of fixed-wing flight. They are suitable for applications such as cargo delivery, search and rescue, and environmental monitoring.
Applications:
Aerial Photography and Videography
Mapping and Surveying
Agriculture
Infrastructure Inspection
Disaster Response and Search and Rescue
Delivery and Logistics
Regulations and Safety: The operation of drones is subject to regulations and guidelines established by aviation authorities in different countries to ensure safety and privacy. These regulations typically govern aspects such as drone registration, pilot certification, airspace restrictions, flight altitude limits, and privacy considerations.
3D printing, also known as additive manufacturing, is a process of creating three-dimensional objects by adding material layer by layer based on a digital model. Unlike traditional subtractive manufacturing methods that involve cutting away material from a solid block, 3D printing builds objects layer by layer from the bottom up, offering greater design flexibility and customization.
Printing Process:
Preparation: The process begins with the creation of a digital 3D model using computer-aided design (CAD) software or by 3D scanning an existing object. The digital model is sliced into thin horizontal layers using slicing software, which generates instructions (G-code) for the 3D printer.
Printing: The 3D printer follows the instructions from the slicing software to deposit material layer by layer, typically using one of several printing technologies such as fused deposition modeling (FDM), stereolithography (SLA), selective laser sintering (SLS), or binder jetting. The choice of printing technology depends on factors such as material properties, resolution, speed, and cost.
Post-Processing: After printing is complete, the object may require post-processing steps such as cleaning, curing (for resin-based prints), support removal, sanding, painting, or assembly to achieve the desired finish and functionality.
Materials:
3D printers can use a wide range of materials, including plastics (e.g., PLA, ABS, PETG), resins, metals (e.g., titanium, aluminum, stainless steel), ceramics, composites, and even food-grade materials. The choice of material depends on the specific requirements of the application, such as strength, flexibility, heat resistance, or biocompatibility.
Applications:
Prototyping and Rapid Manufacturing
Customization and Personalization
End-Use Parts and Production
Medical and Healthcare
Education and Research
Virtual reality (VR) can transport you, your employees and your customers into a designed, digital environment that feels increasingly real. Both the metaverse and virtual environments inside individual organizations are hosting more and more business applications. For example, VR environments can already enable agile teams around the world to collaborate on daily sprints.
VR is already a powerful tool for upskilling and workforce collaboration. In the near future, its startling realism could transform employee and customer experiences and companies’ daily operations.
VR technology in action across different domains:
Gaming
Education
Training and Simulation
Virtual Tours and Travel
Therapy and Rehabilitation
Architectural Visualization
Entertainment and Media
VR is poised to enter more everyday business operations. 3D mapping and real-time tracking cameras could soon enable life-like photorealistic representations of people — transforming activities like workplace collaboration, employee recruitment, customer engagement and investor relations. Realistic, easy-to-use virtual workplaces could help offer employees more flexibility while increasing productivity and reducing carbon emissions.
Integrated into VR, GenAI is allowing even non-specialists to create intricate virtual environments, lifelike “metahumans” and 3D models. Together, GenAI and advances in low-cost hardware are helping autonomous virtual agents perform business relevant tasks (such as customer service) in VR environments.
Eight essential technologies are fundamentally changing the way companies do business. As identified by PwC, they include Artificial Intelligence (AI), virtual reality (VR), Internet of Things (IoT), drones and 3D printing.
These technologies are profoundly game-changing in everyday ways: AI is disrupting whole sectors; drones are delivering packages; IoT is being used to remotely monitor fuel levels in generators; 3D printing is being used to create unique parts at scale; and VR is revolutionizing training.
Sometimes business leaders delay implementing new technologies for fear they are overly complex and require a complicated, multi-year effort. But in today's fast changing, hyper-competitive world, smaller steps are best. Trying, and sometimes “failing fast”, are key. Adopting and converging essential technologies requires an openness and flexibility to test and experiment, too.