How Emerging Technologies Are Impacting Industries

An analysis on leading strategies leveraging technology

Introduction

This article serves as a briefing on how various industries can strategically utilize emerging technologies in and around the world today. This is not an exhaustive list, but rather an introduction to the leading visions and practices across major industries.


Technology Definitions

Artificial Intelligence

A branch of computer science that creates intelligent machines, which can perform activities such as speech recognition, learning, planning, and problem solving. Machine learning — a core subfield of AI — provides the ability for systems to cognitively learn and improve from experience without being explicitly programmed.

Internet of Things

A network of physical objects — appliances, equipment, vehicles, devices, etc. — embedded with sensors, connectivity, and the capability to collect, exchange, and act on data, typically without human interaction.

Blockchain

Blockchain is an incorruptible digital ledger of economic transactions that can be programmed to record not just financial transactions but virtually everything of value.

Virtual, Augmented, and Mixed Reality

Altered realities generated through hardware, which may range from totally immersive artificial environments to the minor merge of a virtual world with the real world.


Industry / Technology Matrix

The matrix gives a condensed description of one value-adding concept for each industry / technology.


Digging Deeper

The following section consist of an expanded explanation of one concept from each industry with examples and/or additional readings.

Blockchain-based smart contracts will play an important role in real estate property transactions (purchase, sale, financing, leasing, and management). Smart contracts hold self-executing code on a blockchain that can automatically execute certain actions when a particular condition is met.

For example, smart contracts have the power to self-execute the movement of funds between bank accounts, transfer property titles, and reconciliation of payments if a condition of the pre-agreed contract is met. This is in contrast to traditional contracts that are typically stored across multiple databases and rely on third parties to drive the deal forward.

Smart contracts will decrease transactions costs for both parties by cutting out administrative and intermediary costs associated with completing a deal.

Example:

Midasium

Additional reading:

“Blockchain in commercial real estate: The future is here”

Organizations such as, IBM Watson are building out cognitive applications that quickly generate a list of potential treatment options ranked by applicability. This is achieved by using AI to analyze data in clinical notes and reports in combination with relevant information such as, clinical expertise, external research, and data.

For example, in a recent double-blinded study, results show that Watson was consistent with the Tumor Board recommendations in 90% of breast cancer cases.

When optimized, cognitive decision support applications will increase the productivity of physicians and help combat regions facing physician shortages.

Example:

Watson for Oncology

Additional reading:

“AI will redesign healthcare”

The soaring amount of connected sensors is allowing insurers to collect enough data to offer usage based insurance (UBI) models. UBI effectively creates and insures a “segment of one” by producing individualized rates where costs are dependent on continuously compiled data from a single customer.

UBI has recently become popular in auto insurance, as risk evaluations are made based on data gathered from connected cars that generate real-world driving behaviours such as, speed acceleration, average time and distance driven, and other parameters. These metrics can then be used to assess more accurate individualized premiums.

When effectively implemented, UBI providers suggest the solution has the potential to reduce claims costs by 40%, reduce policy administration by 50%, and reduce acquisition costs, which should at least partially be rolled over to the consumer.

Additional reading:

“Building innovative solutions for usage based insurance”
“IoT insurance: Trends in home, life, and auto insrance industries”

In retail, blockchain will enable legitimate accountability and transparency across a company’s complex network of supply chain of suppliers. Blockchain has the power to record where all raw materials and manufacturing has been sourced to ensure traceability across various characteristics such as, ethical, environmental, and social impacts of products.

If companies move towards a transparent supply chain, backed by blockchain they should see improved brand equity and customer loyalty from socially responsible shoppers.

Example:

Provenance

Additional reading:

“Global supply chains are about to get better, thanks to blockchain”

Autonomous vehicles, which should fill our streets over the next decade are powered by machine learning. A less talked about example are the driverless long-haul trucks being built by the Tesla’s and Daimler’s of the world. The most immediate opportunity for autonomous trucks may be through “platooning”, which uses sensors to connect multiple trucks via IoT to travel together. Platooning is where several connected autonomous trucks take direction, communicate, and follow the lead of a truck with a human driver. With this model a single driver could deliver multiple truckloads of goods all at once.

This solution will decrease the cost and speed of deliveries for most organizations, rollover the saving to end consumers, and most likely make online purchases even more appealing.

Example:

Daimler

Additional reading:

“Cars and second order consequences”
“Tesla wants to test autonomous trucks”

Blockchain can provide a viable solution to curb the $75 billion counterfeit prescription drug problem. A blockchain solution presents a standardized, visible, efficient, and economical approach to prescription drug supply chains and distribution. The technology will create traceable supply chains by establishing a time stamped and tamper proof ledger that is accessible by all its participants.

This solution would not only reduce the amount of rogue manufacturers but also boost the incentive for firms to innovate. With no counterfeit products, profits go back to the company who put resources towards R&D to develop a drug, therefore most firms should be more incentivized (and financially capable) to create new proprietary products that add value to society.

Example:

Chronicled

Additional reading:

“US Pharma looks at blockchain tech to track prescription drugs”
“The health and economic effects of counterfeit drugs”

Networks of sensors are being used to benefit the operations and logistics of militaries. For example, Lockheed Martin’s ALIS (Autonomic Logistics Information System) embeds sensors throughout aircrafts to detect performance, predict maintenance needs, and communicate these needs to ground repair staff to ensure the right parts are ready when needed.

Systems like ALIS can also use blockchain technology to create a single united ledger that will form a digital copy of every part to mechanic that touches the plane. This single point of truth offers a legitimate history of that can take the practice of maintenance, safety, and aircraft security to new levels.

Combined these technologies will decrease downtime of essential equipment and increase productivity of military operations.

Examples:

ALIS

Additional reading:

“The potential of blockchain technology for airlines”
“The past, present, and future of IoT in the military”

Homes filled with networks of sensors throughout appliances and devices create a connected home that is able to provide multiple sources of data. Using machine learning connected homes can begin to gauge, learn, and anticipate resident behaviours. Connected equipment such as, heat pumps, boilers, electric car charging stations, and batteries can be controlled autonomously and ensure optimised energy consumption within a building.

The benefits of this technology can be rolled out across larger platforms and entire grids. For example, Googles DeepMind has managed to reduce the energy used for cooling their data center 40% by using neural networks to predict the future temperature and pressure of the data center. Consequently, Google is able to apply the necessary energy to meet the cooling needs, rather than continuously applying a cooler than necessary environment.

Google plans to apply this system more broadly across other applications, as they have recently partnered with UK’s National Grid to help balance energy supply and demand in Britain. If successful, this will create a predictive smart grid that can allocate energy in a way that balances the dips and spikes and reduces energy waste.

If built out, this technology would decrease the cost of energy and save people money on their monthly energy bills.

Example:

Alpiq

Additional reading:

“DeepMind AI reduces energy used for cooling Google data centers by 40%”
“DeepMind and National Grid in AI talks to balance energy supply”

Blockchain has the power to create a centralized database of credentials and achievements that are not subject to loss or fraud. Whether you’re moving to a new school, job, or country a secure online repository could validate credentials.

Taking this concept a step further, blockchain could open up massive open online course (MOOC) certifications to become valued credentials and degrees by creating a tamper proof system to validate various projects, tests, and assignments have been completed for a given class. MOOC providers can begin to establish trustworthy accreditations, which could potentially open the world of accredited higher education to globally and most significantly to developing nations.

This idea could enhance the competitiveness of MOOC providers against brick and mortar Universities and increase the global pool of skilled workers.

Additional reading:

“10 ways blockchain could be used in education”

Cognitive IoT technologies are building a new wave of farms that employ smart agriculture by allowing them to compound data from multiple sources such as, historical weather data, social media posts, soil nutrition sensors, market information, crop images, moisture level sensors, etc. and provide farmers with actionable recommendations that will help them improve crop yields.

Crop quality and productivity as well as resource conservation are just some of the benefits that can be gained from utilizing real-time and historical data in combination with machine learning algorithms. For example, a cognitive crop system can look for patterns and output anticipated recommendations for over/under watering, pest control, and soil content adjustments.

By increasing crop yields, this technology will help fight the problem of feeding growing populations with decreasing agriculture lands.

Additional reading:

“Why IoT, big data, & smart farming are the future of agriculture”
“Five ways agriculture could benefit from artificial intelligence”

Where It All Began

The emerging technologies and their applications were chosen based on a combination of various external reports, investment trends, and concepts of personal interest, for example:

Gartner — Top 10 Tech Trends (2017)

Ben Evans — Ten Year Futures

Forrester — Top Emerging Tech to Watch: 2017–2021

This story is published in The Startup, where 258,400+ people come together to read Medium’s leading stories on entrepreneurship.

Subscribe to receive our top stories here.