RESOURCES

TRENDS

DEEPER DIVE

Layers

ORGANIZATION FACTORS

TEAM FACTORS

Competencies
Behaviors
Capabilities
Situation
Environment

INDIVIDUAL FACTORS

Personality
Emotional and Social Intelligence
Learning Experiences
Technical and Functional Skills
Physical and Cognitive Abilities

TALENT TRANSFORMATION GUILD

The Guild interviews thought leaders who provide information to help you learn and prepare for the future of work. CEOs, CHROs, HR consultants, management consultants, coaches, practitioners, experts, solution providers, researchers, and authors explain how the new the changing world of work affects them. They in turn can help you to position yourself and your organization

3D PRINTERS

The ability to feed computer-aided design into a printer to produce a three-dimensional object is a leading catalyst for industrial change. Creating prototypes easily and cheaply and manufacturing spare parts on demand are among 3D printing’s many attractions. So are reduced just-in-case inventories, transportation costs, waste of raw materials, and carbon emissions. Flexibility is another: 3D printers can process a growing range of materials, and they can add liquids or powdered materials layer by layer to produce strong, durable products. New machines, techniques, and materials available have enabled greater precision and repeatability, making 3D printing viable for large-scale production. No wonder many industries, including manufacturing, healthcare, architecture, defense, and education, are adapting this technology to their needs.

5G

The newest generation of wireless communications technologies supports cellular data networks. With greater speed, lower latency, and higher bandwidth than its predecessors, 5G will improve virtual reality and augmented reality experiences and revolutionize inter-vehicular communications and data collection and disbursement with geographically distributed devices. 5G could make in-home internet connections unnecessary, just as cell phones have replaced traditional landline phones.

ARTIFICIAL INTELLIGENCE (AI)

It is now possible for machines to learn and solve problems using neural networks that imitate the workings of the brain. AI enables a device to learn from data and adapt in a way that increases its ability to perform tasks. For example, chatbots can provide online customer service and improve their performance by learning from customer feedback.

There are several types of AI:

NARROW, WEAK, OR BASIC AI

This form of AI focuses on a domain associated with a specific human ability. You could train a computer running narrow AI to beat a particular chess champion, but this does not necessarily mean that it would beat other chess champions. However, narrow AI can learn the rules of chess and play a version of itself to master the game. As another example, an AI system might be able to convert spoken words to text but not understand their meaning.

ARTIFICIAL GENERAL INTELLIGENCE (AGI)

AGI will have far greater abilities than narrow AI. This technology will allow software to learn and perform tasks like a human. A machine running AGI will be able to learn new competencies and connect the dots across multiple domains. As AGI progresses, these machines will use visual, audio, and touch sensors to hear, listen, and see. These machines will be able to speak, move, interact with their environments, communicate with others, understand, reason, develop hypotheses, strategize, solve unfamiliar puzzles by trial and error, and make judgments with incomplete information.

ARTIFICIAL SUPERINTELLIGENCE (ASI)

ASI represents how machines might eventually become smarter than humans. ASI is appealing to some, but as it starts making independent decisions about the way we should live, it could pose a threat to life as we know it. Questions about the ethics of ASI include who can finetune or disable it if it starts working against the interests of the human race. Who will control these super-intelligent machines? And how?

AUGMENTED REALITY (AR)

Digital augmentation of real-world environments adds useful data to what users see physically. Next time you watch a televised football game, you can thank AR for the lines drawn on the field to explain the plays. Unlike virtual reality, described below, AR provides information in the user’s current physical context, so it does more than just simulate an environment. This capability makes it possible for AR to provide real-time support while employees perform tasks.

BIOPRINTING

Bioprinting, a form of 3D printing, is advancing quickly as a means of producing living tissue, bone, blood vessels, and possibly, whole organs. Another potential use is for generating tissue for personalized treatment. The idea of human organ printing is exciting but raises ethical questions.

BLOCKCHAIN

Blockchain enables trust between the parties in a transaction by providing a distributed ledger of transactions. This ledger, or database, lives simultaneously on multiple computers. Each new transaction, or block, added to the ledger includes a timestamp and a link to the previous block to form a chain. This decentralized structure allows users to manipulate information securely without losing the history of prior transactions. Blockchain has powered the development of cryptocurrency and, in the future, will be used to track micro-credentials.

CLOUD COMPUTING

Cloud computing makes online resources such as computing power, data storage, data replication, backup, operating systems, and applications available without requiring users to manage the underlying hardware and software. Typically, cloud computing resources occupy one or several data centers. Organizations can have exclusive access to a cloud or share it with others.

Organizations that use the cloud need not buy hardware or license software, which would require time and additional purchases to scale up the capacity. Instead, customers can connect to the cloud via “as-a-service” offerings and use just what they need; no more and no less. Here are some examples:

INFRASTRUCTURE AS A SERVICE (IAAS)

IaaS provides a self-service model for accessing, monitoring, and managing data center infrastructures from a distance. Infrastructure includes computing resources (hardware or virtualized), storage, networking (including firewalls), and power.

PLATFORM AS A SERVICE (PAAS)

In addition to delivering the same services at IaaS, PaaS provides and maintains the operating systems.

SOFTWARE AS A SERVICE (SAAS)

In addition to providing the underlying platform and data maintenance, SaaS delivers applications for organizations and individuals to use, freeing customers from maintaining and upgrading them internally.

MACHINE LEARNING AS A SERVICE (MLAAS)

MLaaS is a subset of SaaS that allows users to use pre-configured algorithms and statistical models for fast and accurate pattern recognition.

ARTIFICIAL INTELLIGENCE AS A SERVICE (AIAAS)

AIaaS is a subset of SaaS where clients can use pre-configured AI components for such things as natural language processing, voice recognition, and image recognition.

DATA AS A SERVICE (DAAS)

DaaS provides access to data on demand. The service provider sources accurate data and pre-processes it to meet the client’s needs.

HEALTH TECH

New and blended technologies are transforming healthcare in many ways. For example:

Machine learning is exposing previously undetectable patterns of disease evidence.
Artificial intelligence can sort through numerous, complex options to recognize a disease, provide diagnosis, and suggest potential treatments.
Massive computing power enables researchers to use genetic sequencing to identify at-risk groups and target personalized therapies to those most likely to benefit from them.
3D printers produce customized, low-cost prosthetics and medical devices.
Organic material structures to replace kidneys, hearts, and even skin will follow.
Computing and biotechnologies are creating new cancer treatments with less toxic side effects than current treatments.
Devices embedded within clothing will continuously monitor vital signs. Also, enhanced biosensors will measure bodily functions, making it possible to get a meaningful, affordable, and rapid diagnosis via telemedicine.
Natural language, image, and voice processing will analyze moods and emotions—and potentially prescribe virtual reality sessions to help change behaviors.

INTERNET OF THINGS (IOT)

The interconnection of physical objects and digital communications enables everything from thermostats to cars to collect and share data in real time. The IoT allows you to warm up your house or turn on the lights when you are on your way home. Thanks to this merging of the physical and digital universe, everyday objects become “smart” objects. Data collected from smart devices might alert you to anomalies that need attention. As an example, with IoT monitoring pollen counts or pollution and with your device knowing your allergies, your device could alert you to conditions that might trigger a nasty reaction.

MACHINE LEARNING (ML)

Machine learning systems can, given enough data, learn for themselves to categorize, sort, and find patterns of data that would be impossible to detect otherwise. As an example, ML makes it possible to categorize and identify objects, animals, and people easily. It also enables e-commerce websites to recommend products that pique your interest. If you have looked up similar products, the machine knows something about your needs and preferences. The more the machine “learns” about you, the more accurately it will lead you to products you want to buy, or people you’d like to meet.

MATERIALS

Precisely engineered materials can be lightweight, durable, flexible, transparent, and absorbent. Or perhaps thin, easy to shape, and reusable. Materials engineering makes it possible to tailor the mix of these properties for next-generation products, including vehicles, solar power arrays, wind turbines, batteries, buildings, medical devices, protective gear, packaging, and biomedicine.

ROBOTS

Robots perform specific tasks and carry out a complex series of actions. They come in all shapes and sizes and serve many different purposes. Here are several types:

CHATBOTS

Chatbots, now commonplace, provide meaningful interactions with customers when they contact banks, government agencies, airlines, and many other organizations. Developers who program chatbots used to guess at every path a conversation might take. But these days, AI-equipped chatbots use natural language processing and learn from previous conversational patterns to provide relevant help at the time of need. They offer convincing imitations of text or verbal conversations, but unlike their human counterparts, they can work 24/7. Chatbots are now deployed at scale to reduce the need for people in contact centers. Marketing, healthcare, and human resources teams are using more and more of these scalable, readily available digital helpers to engage in human-like conversations to answer questions and concerns.

COLLABORATIVE INDUSTRIAL BOTS (COBOTS)

Traditional robots work autonomously on mechanical tasks such as welding and spray painting. Workers do not go near them. Cobots, on the other hand, collaborate with humans. People provide intelligence and direction, and the cobots perform difficult, repetitive, or dangerous tasks. The cobots’ safety features, manageable size, and ability to do a variety of tasks make them easy for people to use. Cobots can also improve efficiency. For instance, a cobot can take cues from a human’s muscle tension to assist with an activity such as lifting a heavy object.

DELIVERY ROBOTS

Autonomous robots, which have begun delivering packages, offer enormous commercial benefits to shipping companies. Now in their infancy, delivery bots will come in many configurations. Some will be heated and some refrigerated. Eventually, they might take off and land from automated trucks or fly from the warehouse directly to the customer’s door. Cameras, speakers, microphones, 5G, and GPS will make it possible for delivery bots to provide safe, timely, and accurate service.

IN-STORE ROBOTS

In-store robots will interact with customers, answer questions, and find products. Using AI, a robot will recognize the customer, understand their voice, respond appropriately, simulate empathy when goods are not available, and provide useful options based on its knowledge of customer data.

INDUSTRIAL ROBOTS

Robots have been assembling physical products such as cars and smartphones with impressive dexterity for many years. The automotive industry, car parts manufacturers, and device assembly operations are the primary users of industrial robots for now. But as industrial robots become lighter, faster, and smarter, thanks to AI, they will learn how to perform increasingly sophisticated tasks.

ROBOTIC PROCESS AUTOMATION (RPA)

RPA uses software to automate business processes and complete repetitive tasks that employees might otherwise perform. RPA technologies eventually will use natural language processing and AI for such things as face and voice recognition. Current RPA tasks include screen-scraping unstructured information from websites and documents to insert into databases, processing paper invoices, completing expense claims, and producing proposals. Banks, insurance companies, and utilities are significant users of RPA, and more industries will follow suit as this technology matures.

WAREHOUSE ROBOTS

A variety of robots work in warehouses, and their numbers will continue to increase. Some of them lift heavy loads to stack racks, while more dexterous robots pick, pack, and ship products. Supply chain management data and consumer demand for immediate deliveries are driving organizations to make warehouse robots more autonomous and efficient.

VIRTUAL REALITY (VR)

Multi-dimensional, computer-generated replication simulates a physical space to create virtual reality experiences. People currently interact with this environment by wearing a helmet equipped with a screen or gloves that have sensors in them. VR technologies will evolve to provide the same experience with less cumbersome hardware. Although VR is a popular form of entertainment, its simulation of real-world places and situations makes it invaluable in the workplace, especially as a means of helping individuals learn new skills.

Large Language Models (LLMs)

A large language model is an artificial intelligence system designed to understand and generate human-like text. It requires and utilizes deep learning techniques, and to be useful requires a vast amount of textual training data to develop a sophisticated understanding of language. Analyzing patterns and relationships in the text, LLMs create a synthetic understanding of context to respond to questions, generate coherent and contextually appropriate responses, and performs various language-related tasks. Large language models are trained on diverse sources, including books, articles, knowledgebases, and the internet, enabling them to acquire a broad knowledge base. They are versatile tools that assist with natural language processing, translation, chat conversations, and more. But, LLMs can produce hallucinations when the model generates responses that may seem coherent and plausible but are incorrect or fictional.