8 Industries That AI Will Change Forever

It would probably be more accurate to say that AI has already forever changed those industries as it is not the technology of the future anymore, it's the reality. And the industry is well-positioned for explosive growth as AI solutions are highly customizable to serve needs across industries. Some estimates suggest that the total global market for robots and artificial intelligence will reach ~$153 billion by 2020, and the adoption of these technologies could improve productivity by 30% in some industries.

The importance and impact of AI across industries have been recognized by professionals researching, developing its capabilities and implementing it. Scientists from Stanford recently published a paper listing some of the industries that AI will transform or have a profound impact on. Some of them are quite interesting examples. We won't be paying attention to robots in manufacturing and warehousing as it no longer a breakthrough, but a given reality and has even become mundane.


With increasingly connected vehicles that in addition are self-driving, AI is replacing the need for a driver at all. Estimates suggest that the installation rate of AI-based systems in new vehicles will jump from 8% in 2015 to 109% in 2025 with the number of intelligence systems used in infotainment and advanced driver assistance systems (ADAS) going from 7 million in 2015 to 122 million by 2025. In other words, AI-based systems are expected to grow to become the standard in new vehicles over the next five years.

Moreover, according to Gartner’s prediction, by 2020, there will be 250 million cars connected to each other and to the infrastructure around them via Wi-Fi systems that will allow vehicles to communicate with each other and the roadways. Throw into that applications that will be able to independently manage a network of devices, and cars will have a self-regulated life, networks and systems of their own. The prediction is not so far from reality given that there is already a software that allows devices to make important decisions locally and a whole set of examples of projects with self-driving vehicles (Google, Uber, taxis in Singapore, etc.).


As we have highlighted before, AI can already diagnose a life-threatening disease and prescribe a treatment (IBM Watson can, for example). At the beginning of August, IBM’s Watson, a supercomputer powered with AI has been reported to successfully diagnose a rare form of leukemia on a patient within minutes – something doctors failed to do after months. Watson managed to make its diagnosis after doctors from the University of Tokyo’s Institute of Medical Science fed it the patient’s genetic data, which was then compared to information from 20 million oncological studies.

If a software is already capable of diagnosing diseases better than doctors and prescribing effective treatment, intelligent and independent robot-doctors will arrive in no-time. In fact, there are already robots that are helping wheelchair-bound patients to walk again and even robotic surgeons.

Home/Service Robots

Speaking of robots – the robotics industry has made a huge step forward with fascinating machines from Boston Dynamics and others conquering terrains, delivering packages, assisting shoppers, etc.

Better chips, low-cost 3D sensors, cloud-based machine learning, and advances in speech understanding will enhance future robots’ services and their interactions with people.

One of the interesting examples is Aido, an interactive social home robot. He’s an all-in-one package that comes with the best of home automation, security, assistance, entertainment and more, as the company promises. Aido will start shipping in October 2016 and is now gathering funds through Indiegogo.

While Aido is claimed to be the first social robot that can move around home/office to help improve one’s lifestyle, there are more initiatives or ready-for-tailoring robots that can be programmed to live and help within households. They are becoming increasingly smarter and sleeker, being able to perform a variety of tasks (even cook meals).

Image source: Moley


The education market is valued at approximately $4.5 to $5 trillion per annum. Moreover, education and learning technology sector contribute billions to economies. With education, the application of AI is one of the most debatable questions. The value of a human teacher cannot be overestimated, and EdTech is considered to be creating a mess by some industry professionals.

Nonetheless, with proper solutions and implementation, professionals from Stanford believe that AI promises to enhance education at all levels, especially by providing personalization at scale. <...> Natural Language Processing, machine learning, and crowdsourcing have boosted online learning and enabled teachers in higher education to multiply the size of their classrooms while addressing individual students’ learning needs and styles.

Low-resource Communities Assistance

Social service is an important part of population’s welfare. While middle and upper class are not particularly vulnerable, low-resource communities are often the ones governments invest efforts in exploring the ways of lifting from a disadvantageous position.

Using data mining and machine learning, for example, AI has been used to create predictive models to help government agencies address issues such as prevention of lead poisoning in at-risk children and distribution of food efficiently.

Public Safety and Security

In the US, drones have been reported to be at the use of the Federal Government for some time already. The Department of Homeland Security has been working on its own drone fleet back in 2013. Moreover, some sources suggest that at that time, the federal government gave local police departments $1.2 million to spend on drones that year. In 2016, there is a reason to believe that federal efforts in drone use for security or other matters have not ceased.

Drones, however, just the part of a whole when it comes to the application of AI for public safety and security. Drones are not mindless machines; they can be equipped with advanced video analytics solutions that are now mostly used by retailers to increase sales and foot-traffic. The same software applied to cameras records from public places and drone cameras will allow the government to rely on AI to assess the behavior and public safety.

By 2030, they will rely heavily upon them [AI technologies], including improved cameras and drones for surveillance, algorithms to detect financial fraud, and predictive policing.

However, as scientists from Stanford note, the latter raises the specter of innocent people being unjustifiably monitored, and care must be taken to avoid systematizing human bias and to protect civil liberties. Well-deployed AI prediction tools have the potential to provide new kinds of transparency about data and inferences, and may be applied to detect, remove, or reduce human bias, rather than reinforcing it.

Employment and Workplace

By 2025, AI is expected to have a $5-trillion-dollar direct impact on the workforce. Moreover, advances in computing technology, machine learning and user-friendly interfaces will have a significant impact on the labor market and will cost $14 trillion by that time.

Financial services are one of the leading industries to adopt AI. Robo-advising, automated trading platforms, automated fraud detection, automated underwriting and a range of other services are at a risk to be impacted the most, according to research performed by BofA. Some estimations predict that application of advanced robotics and AI in financial and legal services could impact as many as 25 million workers in a positive way: it will increase the efficiency by 45–55%. In that case, the total annual economic impact is estimated to hit $0.6–0.8 trillion in 10 years.

Longer term, AI may be thought of as a radically different mechanism for wealth creation in which everyone should be entitled to a portion of the world’s AI-produced treasures. It is not too soon for social debate on how the economic fruits of AI technologies should be shared.


Entertainment has been transformed by social networks and other platforms for sharing and browsing blogs, videos, and photos, which rely on techniques actively developed in NLP, information retrieval, image processing, crowdsourcing, and machine learning. <...> AI will increasingly enable entertainment that is more interactive, personalized, and engaging.

The information feeds across social media are heavily algorithm-curated and not always with positive implications. While they are intended to have a positive impact on user experience, biases at the basis of AI-powered curation are deepening with no human intervention. The industry does not stand in one place, though, and with advances in algorithms and merger of VR with AI, new and fascinating ways of human interaction and new forms of entertainment will appear.