Emerging Technologies and the Future of Work (with Jasper)

PLEASE NOTE: As an Executive MBA class experiment, this article was partly prepared using the AI content-generating platform Jasper. Any typos or grammatical errors are Jasper's fault :-)

What mark would you give it if the assignment question was:

Summarise the emerging technologies likely to have a profound impact on the future of work over the next few years; the opportunities and threats for organisations across a broad spectrum of industries. Use case examples to support your answer. (Word Count: approx 3,000 words).

For the avoidance of doubt, this is not an assignment I would actually use on an Executive MBA Programme - we are testing something here.

All comments and feedback are very welcome.

Introduction

The final session of our 'Leading Digital' programme provides a brief overview of some emerging technologies likely to have a profound impact on the future of work over the next few years.

As forward-thinking future leaders, it is important to be aware of the potential impact of these technologies in order to make informed decisions on the best way to leverage their full potential for the benefit of your own organisation and society as a whole; building a better future for all.

The Gartner Hype Cycle

A useful starting point is the recently published Gartner Hype Cycle for Emerging Technologies 2022. This identified 25 must-know technologies across five major trends - see Figure 1 below.

• Web 3.0: The next generation of the internet, powered by blockchain and other emerging technologies.
• Metaverse: A shared, virtual space where people can interact with each other and digital objects in a realistic way.
• Blockchain: A distributed database that allows for secure, transparent, tamper-proof transactions.
• Artificial Intelligence: Machine learning and other forms of AI that are redefining how we interact with technology.
• Augmented Reality: Technology that blends the physical and digital worlds to create new experiences.

While many of the 25 emerging technologies have multiple use cases, Gartner identifies three major themes as summarised below.

Theme 1: Evolving/expanding immersive experiences

Technologies that provide individuals with more control over their identities and data, expanding their range of experiences into virtual venues and ecosystems that can be integrated with digital currencies. For businesses, these technologies provide new ways to reach customers, strengthen or open up new revenue streams, enhancing both the customer and employee experience in the process

The following technologies are included under this theme - Digital Twin of the Customer (DToC); Decentralized Identity?(DCI); Digital Humans; Internal Talent Marketplaces; Metaverse; Non-Fungible Token?(NFT); Superapp; Web3?

Theme 2: Accelerated AI automation

According to Gartner, expanding AI adoption is a critical way to evolve products, services and solutions. It means accelerating the creation of specialized?AI models, applying AI to the development and training of AI models, and deploying them to product, service and solution delivery. Outcomes include more accurate predictions and decisions and the faster capture of expected benefits. The role of humans becomes more focused on being consumers, assessors and overseers.

Technologies under this theme include the following - Autonomic Systems; Causal Artificial Intelligence (AI); Foundation Models; Generative Design AI; Machine Learning Code Generation.

Theme 3: Optimized Technologist Delivery

Technologies that focus on the key constituents in building a?digital business including Cloud Data Ecosystems; Augmented Finops; Cloud Sustainability; Computational Storage;?Cybersecurity Mesh Architecture?(CSMA); Data Observability; Dynamic Risk Governance?(DRG); Industry Cloud Platforms; Minimum Viable Architecture?(MVA); Observability-Driven Development?(ODD); Opentelemetry; and Platform Engineering.

Figure 1 Gartner Hype Cycle for Emerging Technologies, 2022

Source: Gartner (August 2022)

Use Case Examples

One way to convey the disruptive impact of these technologies is to consider use case examples.

The following sections identify use case examples of emerging disruptive technologies across a broad range of industries; the opportunities and threats for organisations.

Web 3.0

The next generation of the internet will be based on decentralized storage, blockchains, and peer-to-peer networking. Hopefully, this will lead to a more democratic and user-centric network compared to the oligarchical controlled platforms dominant now. Web 3.0 has the potential for creating a truly global, open, and secure internet where users control their own data.

According to the World Economic Forum, the decentralised web will have a major impact on operating models, organisational structures, labour markets, and the future of work. In a recent paper entitled How Will Web3 Impact the Future of Work WEF argues that:

"The combination of the metaverse and a decentralized web3 has the potential to radically transform operating models and the labour market. As decentralized autonomous organizations are adopted more widely, new types of businesses will emerge that would look more like cooperatives and less like corporations. Leadership will rely on soft power and empathy, using culture and shared values to align the interests of disparate stakeholders to a common mission and purpose.

In a DAO there are no officers, directors, or managers, and therefore leadership roles are more fluid and impermanent, giving more opportunities to members to rise up. This shift from hierarchical structures to flat, widely distributed networks and ecosystems run by stakeholder communities instead of boards and executives, will have a profound impact on the future of work.

Web 3.0 technologies will enable organisations to be more decentralized and autonomous, which will result in a more democratic and meritocratic workplace. Web 3.0 technologies will also enable individuals to own their data and to be paid for their attention. This will lead to a more equitable distribution of wealth, as well as a more efficient and effective allocation of resources."

Metaverse

A virtual world built on Web 3.0 technologies, the Metaverse is a decentralized and user-owned platform allowing people to interact with each other, and with artificial intelligence, in a realistic and immersive 3D environment. It has the potential to enable a new form of human-computer interaction, which will be more natural and intuitive than current forms of interaction. Using blockchain technology, users can create, share, and monetize content providing a new way to build relationships, and interact with each other and businesses online.

In the Metaverse, users will own their data including personal data and the content they create and share on the platform. Users can also be paid for their attention creating the potential for attention-based economic models e.g. viewing ads or participating in marketing campaigns.

While still at an early stage of development, the Metaverse has the potential to disrupt a wide range of industries as shown in Figure 2 below.

Figure 2: Metaverse Use Case Examples

Source: All You Need to Know About The Metaverse

In education, for example, the pandemic has accelerated the demand for online learning. Used effectively, the metaverse has the potential to significantly enhance the online learning experience. In healthcare, the metaverse, Web 3.0, and connected medical devices offer endless possibilities for providing virtual, personalised care services. In manufacturing, companies could use digital twins within the metaverse for emulating manufacturing and logistics processes reducing maintenance costs through predictive planning. In real estate, the metaverse is expected to be used as an immersive tool for pre-screening a property through 360-degree virtual property tours.

Please follow the link shown above for the full list of case examples provided.

Artificial Intelligence

Simply put, artificial intelligence (AI) is the simulation of human intelligence by machines. AI systems are able to learn and work on their own, making decisions based on data. This can be done through a number of methods, including machine learning, natural language processing, and data mining.

• Machine learning: A type of AI that allows computers to learn from data without being explicitly programmed. Machine learning algorithms are used to improve given tasks by building models from example data automatically.
• Natural language processing: NLP enables computers to understand human language. Algorithms are used to process and interpret human language in order to perform tasks such as text classification, sentiment analysis, and entity recognition.
• Data mining: The extraction of patterns from large data sets using algorithms to discover relationships and trends within the data.

The use of AI in the workplace is already growing rapidly delivering real business and efficiency improvements through process automation, faster and more accurate decision-making, enhanced customer service through a better understanding of individual customer needs, maximising up and cross-selling opportunities through personalised recommendations, and so on.

With the potential for AI to replace jobs, ethical and security issues remain a continuing source of concern.

A recent article from MARKTECHPOST.COM summarises the top trending AI applications and technologies for 2022 and beyond. These will have a disruptive impact on a broad range of industries and sectors.

• Natural Language Generation
• Speech Recognition
• Decision Management
• Robotic Process Automation
• Text Analytics and Natural Language Processing (NLP)
• Cyber Defense
• Content Creation
• Emotion Recognition
• Marketing Automation
• Virtual Agents
• Machine Learning?Systems
• Peer-to-Peer Network
• Deep Learning Systems
• AI Optimized Hardware
• Smart Devices
• Self-Driving Cars
• Augmented Reality
• Chatbots
• Internet of Things (IoT)
• Image Recognition
• Biometrics

Please consult the reference above for a more detailed summary of each technology/application.

Blockchain

The technology behind Bitcoin, Blockchain is a distributed database that allows for secure, transparent, and tamper-proof transactions. Because it is distributed, there is no central authority that controls the data. This decentralization makes it incredibly secure, as there is no single point of failure. Furthermore, the transparency of the ledger means that all transactions are public and verifiable. Finally, the tamper-proof nature of Blockchain means that once a transaction is recorded, it cannot be changed or deleted.

Blockchain use examples can already be found across a broad spectrum of industries. In banking, for example, blockchain is being used to support cross-border payments. The healthcare sector is looking at blockchain for applications such as secure medical record sharing and prescription drug traceability. In supply chain management, blockchain is being used for end-to-end tracking of goods and materials. Governments are experimenting with the blockchain for a wide range of applications including tax compliance and benefits payments.

A top ten of blockchain use cases are presented in this 2021 article Practical Blockchain Use Cases - also in the video shown below.

Source: https://youtu.be/fy9t1kY0hBw

Big Data

Simply put, the term big data refers to the large volume of data being collected by organizations on a daily basis; generated from a variety of sources including website traffic, social media, transaction records, CRM and ERP systems, workplace analytics, and numerous other sources.

The defining properties of Big Data are often described as the 3Vs:

• Volume - the very large volume of data being generated.
• Velocity - the speed at which that data is generated.
• Variety - the range of data types (e.g. structured, unstructured, text, images, etc from a very diverse range of sources).

The challenge for organizations is to make sense of this data, turning it into actionable insights that improve business performance. When properly analyzed, the actionable insights derived from big data analytics can help organizations make better decisions across all value chain activities.

There are already numerous case examples of Big Data in action:

• Retailing: The use of big data to track customer behaviour and preferences to ensure that the right products in the right quantities are in stock.
• Telecommunications: Tracking call patterns and user behavior in order to improve network performance.
• Insurance: The use of big data and analytics to price insurance premiums more accurately.
• Healthcare: Actionable insights derived from data to improve patient outcomes by identifying trends and risk factors.
• Manufacturing: The use of data analytics to optimize production processes, reduce waste, and for predictive maintenance.
• Oil and Gas: Big data is being used to find new oil and gas reserves and for predictive maintenance.
• Food and Drink: More accurate tracking of food safety and quality issues.
• Transportation: More efficient vehicle routing and reduced traffic congestion.

The benefits of big data are wide and varied:

• Improved decision-making from actionable insights that would otherwise be unavailable.
• Improved operations by identifying inefficiencies and areas of improvement.
• Improved customer service by identifying and addressing areas of improvement.
• Increased revenues by improving marketing efforts, product quality, and operations.
• Improved competitive advantage by providing insights into competitor data.

The main challenges of big data include:

• Data volume: The sheer volume of data that organisations collect can be difficult to manage and process.
• Data complexity: The complexity of big data can make it difficult to obtain useful insights from the data.
• Data storage: Storing all of the collected data can be a challenge for organisations, especially if they do not have the necessary storage infrastructure in place.
• Data security: Securing all of the collected data can be challenging, especially if the data contains sensitive information.
• Data privacy and governance: Ensuring that the collected data is used in a way that does not violate privacy laws

The very rapid growth of artificial intelligence and machine learning provides further exciting opportunities for organisations to leverage the full potential of big data analytics, especially in the area of predictive decision-making.

The Internet of Things (IoT)

Within a very short time period, we have moved rapidly from the Internet of People connecting through social media channels to the Internet of Things, the growing network of inter-connected physical objects.

As more and more devices, vehicles, buildings, factories, machinery, etc become embedded with electronics, software, sensors, and network connectivity, collecting and exchanging data, the future potential of IoT is enormous.

We are already seeing use case examples across a diverse range of industries and applications - wearables, medical devices, connected cars, smart home appliances, industrial machines, smart buildings, farm equipment, soil monitoring in agriculture, pipe monitoring in oil and gas, smart aircraft, transportation, logistics, supply chain management - the list goes on.

The potential benefits of IoT for organisations are wide and varied:

• Improved decision-making - by providing insights that would otherwise be unavailable, the ability to collect data from a large number of devices in real-time provides for better decision-making.
• Improved operations - the ability to monitor and manage a large number of devices in real-time can help organizations improve their operations by identifying inefficiencies and areas of improvement.
• Improved customer service - the ability to collect data from customers and devices in real-time can help organizations improve their customer service by identifying and addressing areas of improvement.
• Increased revenues - the ability to collect data from customers and devices in real-time can help organizations increase their revenues by improving marketing efforts, product quality, and operations.
• Improved competitive advantage - The ability to collect data from customers and devices in real-time can help organizations gain a competitive advantage by providing insights into competitor data.

Closely related to IoT is the term Industry 4.0 or the factory/oil field of the future.

The fourth industrial revolution, or Industry 4.0, is the current trend of automation and data exchange in manufacturing technologies. It includes a number of new technologies that are being used to improve manufacturing efficiency and productivity, including:

• Advanced robotics: Capable of performing tasks that are difficult or impossible for humans to perform, such as working in difficult or dangerous environments.
• Additive manufacturing: Also known as 3D printing, is a process of making objects from three-dimensional printer models.
• Virtual and augmented reality: Technologies that create immersive experiences that can be used for training, design, and manufacturing.
• The Internet of Things: As explained previously.
• Big data and analytics: As explained previously.

The benefits of Industry 4.0 for organizations are wide and varied including improved efficiency, automation of key tasks and processes, elimination of errors and reduced waste, improved quality, productivity, and competitive advantage.

5G

5G, the next generation of mobile technology, is the key enabler of all of the above.

Summary

Although some of the technologies briefly reviewed above are still at an embryonic stage of development, there can be little doubt that the future of work, life, and society is going to be radically different from the present.

As forward-thinking innovative leaders, we should be embracing change, using these technologies to improve our organisations; building a better future for all. The embryonic nature of the technologies makes them riskier to deploy, but the benefits for early adopters are potentially greater. Leaders should prioritize those with the greatest potential benefit for their organisation; launching proof-of-concept projects to demonstrate the feasibility of a technology for their target use case.

Future possibilities are limited only by our own imagination. So let's get started on building the new future of work!

As always, comments and feedback are very welcome

Dr Jim Hamill & Jasper :-)

Word Count: 2,781 including references.

This is what happens when you ask Jasper to 'add references':

What is Web 3.0? (n.d.). Retrieved from https://www.computerweekly.com/feature/What-is-Web-30

Emerging Technologies and the Future of Work (n.d.). Retrieved from https://www.forbes.com/sites/forbestechcouncil/2019/01/28/emerging-technologies-and-the-future-of-work/#2e07c65f528a

Industry 4.0 (n.d.). Retrieved from https://www.mckinsey.com/industries/high-tech/our-insights/what-is-industry-40

5G (n.d.). Retrieved from https://www.techradar.com/news/world-of-tech/networks/what-is-5g-and-when-will-it-launch-in-the-uk--1324191

https://www.computerweekly.com/feature/What-is-Web-30

"Add more references"

https://www.accenture.com/_acnmedia/pdf-16/accenture-embracing-disruption-industry40-report.pdf

https://www2.deloitte.com/insights/us/en/focus/signals/articles/industry40-future-of-manufacturing.html

https://www2.deloitte.com/content/dam/Deloitte/de/Documents/technology-media-telecommunications/gx-tmt-industry40-white-paper.pdf

https://www.bcg.com/publications/2019/future-workforce-industry-40.aspx?linkId=68357240

"add more references"

https://www.mckinsey.com/industries/high-tech/our-insights/future-of-work-in-a-world-of-ai-and-robotics

https://hbr.org/2018/12/the-future-of-work

https://www.mckinsey.com/featured-insights/future-of-work/jobs-lost-jobs-gained-what-the-future-of-work-will-mean-for-jobs-skills-and-wages

etc etc