Size of Industry
$228,350,000,000
What is it?
While a number of definitions of artificial intelligence (AI) have surfaced over the last few decades, John McCarthy offers the following definition in this 2004 paper (PDF, 106 KB) (link resides outside IBM), " It is the science and engineering of making intelligent machines, especially intelligent computer programs. It is related to the similar task of using computers to understand human intelligence, but AI does not have to confine itself to methods that are biologically observable."
However, decades before this definition, the birth of the artificial intelligence conversation was denoted by Alan Turing's seminal work, "Computing Machinery and Intelligence" (PDF, 89.8 KB)(link resides outside of IBM), which was published in 1950. In this paper, Turing, often referred to as the "father of computer science", asks the following question, "Can machines think?" From there, he offers a test, now famously known as the "Turing Test", where a human interrogator would try to distinguish between a computer and human text response. While this test has undergone much scrutiny since its publish, it remains an important part of the history of AI as well as an ongoing concept within philosophy as it utilizes ideas around linguistics.
HOW does it work?
Artificial Intelligence garners more frontpage headlines every day. Artificial Intelligence, or AI, is the technology enabling machines to learn from experience and perform human-like tasks.
Ping-ponging between utopian and dystopian, opinions vary wildly regarding the current and future applications, or worse, implications, of artificial intelligence. Without the proper moorings, our minds tend to drift into Hollywood-manufactured waters, teeming with robot revolutions, autonomous cars, and very little understanding of how AI actually works.
This is mostly due to the fact that AI in itself is describing different technologies, which provide machines the ability to learn in an “intelligent” way.
In our coming series of blog posts, we hope to shed light on these technologies and clarify just what it is that makes artificial intelligence, well, intelligent.
How is artificial intelligence applied?
Popular misconceptions tend to place AI on an island with robots and self-driving cars. However, this approach fails to recognize artificial intelligence’s major practical application; processing the vast amounts of data generated daily.
By strategically applying AI to certain processes, insight gathering and task automation occur at an otherwise unimaginable rate and scale.
Parsing through the mountains of data created by humans, AI systems perform intelligent searches, interpreting both text and images to discover patterns in complex data, and then act on those learnings.
What are the basic components of artificial intelligence?
Many of AI’s revolutionary technologies are common buzzwords, like “natural language processing,” “deep learning,” and “predictive analytics.” Cutting-edge technologies that enable computer systems to understand the meaning of human language, learn from experience, and make predictions, respectively.
Understanding AI jargon is the key to facilitating discussion about the real-world applications of this technology. The technologies are disruptive, revolutionizing the way humans interact with data and make decisions, and should be understood in basic terms by all of us.
Machine Learning | Learning from experience
Machine learning, or ML, is an application of AI that provides computer systems with the ability to automatically learn and improve from experience without being explicitly programmed. ML focuses on the development of algorithms that can analyze data and make predictions. Beyond being used to predict what Netflix movies you might like, or the best route for your Uber, machine learning is being applied to healthcare, pharma, and life sciences industries to aid disease diagnosis, medical image interpretation, and accelerate drug development.
Deep Learning | Self-educating machines
Deep learning is a subset of machine learning that employs artificial neural networks that learn by processing data. Artificial neural networks mimic the biological neural networks in the human brain.
Multiple layers of artificial neural networks work together to determine a single output from many inputs, for example, identifying the image of a face from a mosaic of tiles. The machines learn through positive and negative reinforcement of the tasks they carry out, which requires constant processing and reinforcement to progress.
Another form of deep learning is speech recognition, which enables the voice assistant in phones to understand questions like, “Hey Siri, How does artificial intelligence work?”
Neural Network | Making associations
Neural networks enable deep learning. As mentioned, neural networks are computer systems modeled after neural connections in the human brain. The artificial equivalent of a human neuron is a perceptron. Just like bundles of neurons create neural networks in the brain, stacks of perceptrons create artificial neural networks in computer systems.
Neural networks learn by processing training examples. The best examples come in the form of large data sets, like, say, a set of 1,000 cat photos. By processing the many images (inputs) the machine is able to produce a single output, answering the question, “Is the image a cat or not?”
This process analyzes data many times to find associations and give meaning to previously undefined data. Through different learning models, like positive reinforcement, the machine is taught it has successfully identified the object.
Cognitive Computing | Making inferences from context
Cognitive computing is another essential component of AI. Its purpose is to imitate and improve interaction between humans and machines. Cognitive computing seeks to recreate the human thought process in a computer model, in this case, by understanding human language and the meaning of images.
Together, cognitive computing and artificial intelligence strive to endow machines with human-like behaviors and information processing abilities.
Natural Language Processing (NLP) | Understanding the language
Natural Language Processing or NLP, allows computers to interpret, recognize, and produce human language and speech. The ultimate goal of NLP is to enable seamless interaction with the machines we use every day by teaching systems to understand human language in context and produce logical responses.
Real-world examples of NLP include Skype Translator, which interprets the speech of multiple languages in real-time to facilitate communication.
Computer Vision | Understanding images
Computer vision is a technique that implements deep learning and pattern identification to interpret the content of an image; including the graphs, tables, and pictures within PDF documents, as well as, other text and video. Computer vision is an integral field of AI, enabling computers to identify, process and interpret visual data.
Applications of this technology have already begun to revolutionize industries like research & development and healthcare. Computer Vision is being used to diagnose patients faster by using Computer Vision and machine learning to evaluate patients’ x-ray scans.
Additional Supporting technologies for Artificial Intelligence
Graphical Processing Units or GPUs are a key enabler of AI, providing the massive computing power necessary to process millions of data and calculations quickly.
The Internet of Things, or IoT, is the cumulative network of devices that are connected to the internet. The IoT is predicted to connect over 100 billion devices in the coming years.
Intelligent data processing is being optimized using advanced algorithms for faster multi-level analysis of data. This is the solution to predict rare events, comprehending systems and unique situations.
With the integration of Application Processing Interfaces or APIs, aspects of artificial intelligence can be plugged into existing software, augmenting its normal function with AI.
Artificial Intelligence is a diverse topic
As we have learned, AI is describing a set of different technologies. Each of these technologies require detailed explanation. Staying up to date and understanding the differences of these technologies is a difficult task. Keep up with the latest changes and stay tuned for our upcoming posts.
Next, we will introduce Big Data and explore the applications of artificial intelligence solutions to structuring, connecting, and visualizing large data set to accelerate insight and empower decision-making.
Use Case
Practically every business process will be changed and taken over by artificial intelligence, since AI can be trained to do almost everything that involves a process, and do it better than a human.
How can you identify which business processes will be the first to go to AI?
The business processes with the three traits below are most likely to be replaced by AI:
Repetitive processes
High-volume processes
Rule-based processes
Think about order processing or data handling, which are activities that are still being done by human workers in many companies. Because these tasks typically involve repetitive, high-volume, rule-based processes, they will be among the first to be done by artificial intelligence.
1. AI and Personal assistants
AI-powered personal assistants like Amazon Echo, Google Home and Apple HomePod are examples of virtual assistants that can perform basic tasks, but will become increasingly smarter over the years to come, getting better and better at handling most of our daily activities. For example, Amazon has launched a smarter new microwave that works with Amazon Alexa (AI technology that powers Amazon Echo devices). However, some consumers fear that it will be able to listen to their conversations and invade their privacy, perhaps by suggesting products to buy, analyzing their voices to detect if they are ill, or worse.
I also recommend to read this New York times article Hey, Alexa, Why is Amazon Making a Microwave?
2. AI and Market research
Several AI-based applications like IBM’s Watson can perform comprehensive research for businesses, completing tasks such as comparing their competitors and producing detailed reports. In the future, these types of tools will use companies’ internal data to provide surprisingly accurate predictions regarding the potential success of new products or services.
3. AI and Sales
AI can be used to improve every step of the sales process—from generating leads, to categorizing them, to offering personalized marketing messages for them. All the major providers of CRM software are already integrating AI features into their tools, such as predicting customer needs and analyzing their buying processes on a granular level.
4. AI and Digital marketing
Virtually every digital marketing activity can be done better with the correct use of artificial intelligence. One of the most impactful—and at the same time scary—examples of this is content generation, which can be created in written, audio or video form by AI tools. It is impactful because of the huge amounts of time and resources it can save for companies, and scary because it can be used for dishonest purposes such as manipulating voters during an election. To better understand how AI will impact digital marketing, I recommend reading this article by Smart Insights.
5. AI and Email marketing
Many large email service providers are already working tediously to incorporate artificial intelligence functions into their products. In order for AI to work it needs data. In the case of email marketing, most companies already have a lot of valuable data that could be used, which makes AI and email marketing a natural fit. Here are some examples of data that could be used with AI to improve the effectiveness of email marketing campaigns:
Which headlines have generated the highest open rates?
What are the lengths and other characteristics of the email messages that have generated the most engagements?
Which keywords have generated the best results?
These are just some examples, but there are many other ways that AI-enhanced email marketing tools can provide tremendous improvements to companies’ email marketing efforts.
One interesting tool, called Boomerang Respondable, uses AI to analyze the emails you write on Gmail and provide suggestions on how to improve them. You can see this tool here.
6. AI and Leadership teams
As we are living more and more in the digital economy, it is becoming increasingly vital that business leaders use AI and data to make decisions. Several companies, like the Finnish IT firm Tieto, have opted to include AI as part of their leadership teams. As the business world and society become more complex, AI tools that analyze huge amounts of data become crucial, as they can assist leaders in making better decisions based on data and evidence.
7. AI and Customer service
From the customer’s point of view, customer service is getting better and better, as it is becoming increasingly automated and powered by AI-based chatbots.
Many of today’s customer service chatbots are “rule-based,” working without AI, but in the future most of them will be AI-powered and even voice-enabled.
Probably the chatbot that has generated the greatest commercial value is the AliMe chatbot by Alibaba. It uses a wide variety of different technologies such as voice recognition, semantic understanding and personalized recommendations, and helped Alibaba to reach its record sales of $31 billion on Singles’ Day in 2018.
If your company provides customer service, you should already be creating your first chatbot. Even having a basic rule-based chatbot, which would be pre-programmed to answer about 30 – 40 of your customers’ most frequently asked questions, would be better than having nothing at all.
8. AI and Accounting
The financial sector is one of the first industries that is being completely disrupted by artificial intelligence and robotic software like robotic process automation. Since most of the work accountants do on a daily basis is repetitive and rule-based, most of it can and will be automated by AI.
The parts of their jobs that will be the most difficult and take the longest to automate is meeting with clients and explaining things to them. Clearly, those activities will continue to be performed by humans in the near future.
The popular website willrobotstakemyjob.com, which shows the likelihood of different jobs becoming automated by AI, indicates that there is a 94 percent possibility of accountants’ and auditors’ jobs being automated. According to this site, there were over 1.2 million people working as accountants or auditors in the United States as of the year 2016.
You can see these results and other related information here:
https://willrobotstakemyjob.com/13-2011-accountants-and-auditors
9. AI and Human resources
One of the areas in which the application of AI and robots has been most criticized lately is human resources and hiring. Although the use of different AI technologies can save time and resources in the hiring process, critics argue that many of them are biased and unethical. To learn more about the pros and cons of using AI in the hiring process, I recommend viewing this detailed mini-documentary by the Wall Street Journal:
Despite the skepticism, it’s evident that AI can be a very useful tool in the initial screening of candidates in several ways. For example, AI tools can be used to analyze candidates’ video presentations through the use of voice recognition and computer vision technologies. AI can also meticulously analyze any content candidates have posted on social media sites.
10. Law and legal teams
As with accounting, many of the activities conducted by lawyers are repetitive and rule-based. A competition was held between the AI platform LawGeex and experienced human lawyers. The fascinating results illustrated below demonstrate AI’s astonishing ability to outperform a human legal team.
Time limit: 4 hours
Task: Identify legal issues in non-disclosure agreements (NDAs).
Accuracy rate:
Human team: 85 percent
AI: 95 percent
Time:
Human team: 92 minutes
AI: 62 seconds
The results of the accuracy rates are pretty straightforward and similar to those of many other tests. However, what really showcases the remarkable power and effectiveness of AI is the speed with which it was able to successfully complete the task. 62 seconds compared to 92 minutes is an enormous difference, which exemplifies why many companies are looking into implementing AI for tackling their legal issues.
11. AI and Robotic process automation (RPA)
Many large and mid-sized companies start with robotic process automation when beginning the automation process. The basic idea of RPA is to identify repetitive and high volume tasks. One example of this could be processing orders. Most robotic process automation is currently “rule based,” meaning it does not include AI. However, it’s expected that in the future most RPA software will be AI-powered.
The use of RPA can provide many benefits, such as increased productivity and allowing human workers to have more time for creative tasks and those that entail communication with other humans.
Another significant benefit is that RPA can be integrated with a company’s existing business systems and projects, and therefore does not require any major internal changes.
Examples of Business Processes That Artificial Intelligence Will Change
In this section we looks at some of the most common examples and use cases of how artificial intelligence will transform different business industries.
In the following list we can see some examples of how AI is already transforming different industries:
12. Artificial intelligence and Finance
So-called “robo-advisors” and other AI-based applications can perform tasks that previously only human beings could do. Because by nature it has many rules and deals with numbers, involving the kinds of tasks that are easy to train AI to do, the financial sector will be one of the first ones to adopt artificial intelligence.
13. Artificial Intelligence and Travel Industry
AI-enabled virtual assistants and chatbots that help tourists before, during and after their trips will be commonplace within a few years. Several airports, trade fairs and museums are already testing check-in through facial recognition, which will greatly shorten lines and allow for the faster movement of people.
Facial recognition is already being used in an airport in China. The video below shows a traveler simply walking in front of a screen which, thanks to this technology, displays all his travel information for him.
This will surely become commonplace in most airports worldwide. I wrote a complete article which highlights 7 Ways on How Artificial Intelligence (AI) Is Transforming the Travel and Hotel Industries.
14. Artificial Intelligence and Health
Robot-assisted surgery and virtual nursing assistants will help achieve better results and assist doctors in operations. In addition, AI systems are helping to conduct better and more accurate medical research and AI-powered computer vision is being used to analyze X-ray results.
15. Artificial Intelligence and Transportation
Autonomous cars, planes and boats will change the transportation industry completely. 5G-enabled smart transport will allow vehicles to communicate with each other to ensure smoother traffic and less accidents.
16. Artificial Intelligence and Retail
The retail industry is one of those that will be most impacted by the development of AI. Shops and supermarkets without cashiers will be a reality in the coming years. AI technologies will bring great improvements to inventory and supply-chain management. Robot assistants will share shopping information with customers and perform many repetitive tasks in retail stores.
This BBC Click documentary about AI and jobs, which is about 25 minutes long, devotes about 20 minutes to presenting different use cases of robots that are already being implemented in the retail industry. Everyone should watch this video to gain a better understanding of AI’s impact on retail.
I also recommend reading this article in which I cover how robots are being used in education.
17. Artificial Intelligence and Journalism
AI-based applications can be trained to generate large amounts of news stories. Likewise, journalists will be able to use different AI-enabled applications to help them to conduct research more effectively.
18. Artificial Intelligence and Education
AI-powered educational chatbots and tutors will radically improve the educational experience and help to provide personalized education. Also, facial recognition can be used to analyze the effectiveness of teaching and obtain feedback directly from students. In addition, AI applications can be used by students to analyze job opportunities in real time.
18. Artificial Intelligence and Agriculture
Agricultural drones, autonomous tractors and vertical agriculture based on AI technology will completely transform the agriculture industry and allow farmers to consume less water and natural resources.
AI-powered vertical farming can help us to provide healthy food in cities. This documentary by Bloomberg showcases how this technology is being used to grow kale in a factory in New Jersey.
19. Artificial Intelligence and Entertainment
There are already movie trailers edited by AI and pop songs produced by it, and they are getting better. Big Hollywood production companies are also using facial recognition technologies to detect audiences’ reactions during test screenings. This feedback can be used to improve the plots of the movies.
20. Artificial Intelligence and Government
AI can be used by governments in a variety of ways, such as to increase public safety through facial recognition and other AI technologies. Governments can also use AI to analyze large amounts of citizen data in order to create predictions and better prepare for different situations related to public health, education and other important matters.
The above is just a small summary of the drastic changes that AI is already generating in different industries and sectors. However in the future we will see several other use cases and examples of artificial intelligence.
Companies and managers who are able to understand and prepare for these radical changes will have greater competitive advantages, while companies that ignore them will suffer great difficulties. I recommend to review the 9 reasons on why artificial intelligence is important now and the most common questions and answers of artificial intelligence.
Although there are several AI applications that are still in their initial phases, it is vital that all companies begin to investigate how to apply AI within the next three to four years.
Market
Artificial intelligence (AI) is emerging as one of the promising technologies, against the backdrop of fast paced digitalization and rapidly evolving technology landscape. Growth in the market is driven by increasing adoption in an expanding range of applications in varied industries. With significant improvements being seen in data storage capacity, computing power and parallel processing capabilities, the adoption of AI technology in various end-use sectors is on the rise. The rising adoption of cloud-based services and applications, rapid growth of big data, and the increasing need for intelligent virtual assistants are also contributing to the rapid pace of growth. The advent of face, image, and voice recognition technologies further boosts growth opportunities. AI has emerged as a powerful tool in the war against COVID-19. The predictive technology is being exploited by governments and other stakeholders to determine the way the COVID-19 virus is spreading, identify vulnerable people and finding mutation patterns.
Amid the COVID-19 crisis, the global market for Artificial Intelligence (AI) estimated at US$43.1 Billion in the year 2020, is projected to reach a revised size of US$228.3 Billion by 2026, growing at a CAGR of 32.7% over the analysis period. Services, one of the segments analyzed in the report, is projected to record a 32.4% CAGR and reach US$126.1 Billion by the end of the analysis period. After a thorough analysis of the business implications of the pandemic and its induced economic crisis, growth in the Software segment is readjusted to a revised 30.3% CAGR for the next 7-year period.
The U.S. Market is Estimated at $21.9 Billion in 2021, While China is Forecast to Reach $40.4 Billion by 2026
The Artificial Intelligence (AI) market in the U.S. is estimated at US$21.9 Billion in the year 2021. China, the world`s second largest economy, is forecast to reach a projected market size of US$40.4 Billion by the year 2026 trailing a CAGR of 39.1% over the analysis period. Among the other noteworthy geographic markets are Japan and Canada, each forecast to grow at 27.3% and 28.9% respectively over the analysis period. Within Europe, Germany is forecast to grow at approximately 31.1% CAGR. The dominant share of the US is mainly attributed to the widespread adoption of AI technology in several end-use industries including media, e-commerce and manufacturing. Increased funding for advancing AI technology and applications, increasing demand for intelligent virtual assistants, and a considerably higher level of awareness about AI are also favoring growth. AI-based solutions are being increasingly deployed for responding to the crisis, with use cases spanning facets like diagnostics, triage to COVID-19 patients, screening for infections and identification of people with heart problems. AI, especially machine learning, is being exploited for dealing with large data volumes such as medical images and treatment records. Growth in Asia-Pacific including China is propelled by the increasing adoption of natural language processing (NLP) and deep learning technologies in sectors such as marketing, finance, law, and agriculture.
Hardware Segment to Reach $56.4 Billion by 2026
In the hardware segment, CPUs and GPUs currently lead, due to their high computing abilities that are needed for AI frameworks. GPU, FPGA and DSP are utilized for implementation of deep learning algorithm. AI hardware continues to gain significant attention with several initiatives being undertaken in this space.
In the global Hardware segment, USA, Canada, Japan, China and Europe will drive the 36.6% CAGR estimated for this segment. These regional markets accounting for a combined market size of US$7.3 Billion in the year 2020 will reach a projected size of US$64.4 Billion by the close of the analysis period. China will remain among the fastest growing in this cluster of regional markets. Led by countries such as Australia, India, and South Korea, the market in Asia-Pacific is forecast to reach US$7.6 Billion by the year 2026. More