Artificial intelligence (AI) essentially refers to computing technologies that are inspired by the ways people use their brains and nervous systems to reason and make decisions, but typically they operate quite differently.
The current AI ecosystem consists of machine learning, robotics, and artificial neural networks (ANNs). In machine learning, programs learn from existing data and apply this knowledge to new data or use it to predict data.
Definition, evolution & revenue potential
Technology, trends & drivers
Application of AI in different industries
Funding, M&A & competitive landscape: Amazon, Apple, Baidu, ebay, etc.
Artificial intelligence (AI) essentially refers to computing technologies that are inspired by the ways people use their brains and nervous systems to reason and make decisions, but typically they operate quite differently. The concept of AI has been the source of inspiration for many science fiction writers and futurologists for over a century. Today, advancements in computing and big data have made it a reality, with machines now being deployed at a large scale across industries. The application of AI technologies is driving growth at individual, business, and economic levels. In fact, AI has started to outperform human beings in a range of work activities, including ones requiring cognitive abilities.
The current AI ecosystem consists of machine learning, robotics, and artificial neural networks (ANNs). In machine learning, programs learn from existing data and apply this knowledge to new data or use it to predict data. The field of robotics is concerned with developing and training robots. Usually, the ability of a robot to interact with people and the world follows general rules and is predictable. However, current efforts also revolve around using deep learning to train robots to manipulate situations and act with a certain degree of self-awareness. ANNs are built to mimic the workings of a human brain. NLP deals with the interpretation and manipulation of human language by computers.
Over the last few decades, the evolution of AI has mostly revolved around the advancement of linguistic, mathematical, and logical reasoning abilities. However, the next wave of AI advancements is pushing towards developing emotional intelligence. At the same time, sequential learning, another feature of Google’s DeepMind, is enabling AIs to learn multiple skills. Over the last few years, deep learning has made vast improvements in enabling machines to comprehend the physical world to a certain degree and is used across industries for various tasks. Among the leading economies, China has invested a lot of research and money into AI in recent years.
One of the major factors driving the current wave of AI growth is the strong interest of Venture Capital (VC) investment in AI start-ups. On the technology front, rapid advancements in computing power are driving the industry to the next level. Similarly, open-source platforms are promoting and enabling collaborative learning, which is conducive for the growth in AI. The current wave of growth in the AI industry is as much about the abundant availability of big data as it is about software and hardware. The amount of big data being generated by today’s increasingly digitized economy is growing at a rate of 40% each year and is expected to reach 163 trillion gigabytes by 2025.
This growth in big data is driving the improvement of AI algorithms. AI solutions are increasingly being customized to serve the needs of the automotive, healthcare, education, finance, entertainment, and other industries. In the automotive sector, AI is primarily used to power autonomous cars, with these systems expected to become standard in new vehicles in the medium to long term. In the healthcare industry, developments in the field of AI and machine learning have not only accelerated the pace of innovation in the industry but are also changing entire operating models. In the education industry, there are attempts to provide customized learning programs for each student using AI, while in the finance industry, AI wealth management solutions can offer higher personalization.
With the rise of AI, more and more start-ups venture into the market. Most work in the field of machine learning applications, followed by natural language processing. Heading into 2020, there were over 2,600 AI start-ups across 13 categories. The AI companies have cumulatively raised around US$239.2 billion in funding during 2015-2022.
Over the years, the number of AI acquisitions have grown steadily, only to dip for the first time in 2020, as the COVID-19 outbreak prompted many businesses to prioritize core operations over new acquisitions. However, the acquisitions gained momentum and the around 312 M&A deals signed in 2021. The number of M&A deals declined in 2022 compared to the previous year and around 259 deals registered during the year.
Companies from various industries are currently developing AI and related applications. Google, IBM and Microsoft are leading AI innovations in the IT industry, while Amazon and eBay are investing in AI to improve their eCommerce platform, and ride-sharing company Uber is using AI on autonomous driving, food deliveries, and mapping research. Collaborative development is on the rise, and leading companies such as Amazon, Apple, Facebook, Google/DeepMind, IBM, and Microsoft are currently working in partnership towards developing AI applications. The acquisition of small-scale AI companies by tech giants like Apple, IBM, and Microsoft in relevant fields is on the rise, leading to a decreasing learning curve. Other leading companies include Baidu, Facebook, and Salesforce.
Evolution of artificial intelligence
Global revenue projection
Robotic process automation
Impact of AI
Artificial neural networks
Natural language processing
Artificial emotional intelligence
Rise of China
Growth in hardware and software
Corporate VC investment
Start-ups: Funding and M&A
Investment by AI enterprises
AI enterprises growth
AI start-ups by funding
Merger & acquisition
Top 5 global AI acquirers
Recent M&A eeals
Statista Consumer Insights
Statista Market Insights
Statista Company Insights
Current artificial intelligence ecosystem
Evolution of artificial intelligence
Leading countries by gross R&D expenditure worldwide in 2022 in billion US$
Global Artificial Intelligence market in billion US$
Worldwide AI for enterprise applications market in million US$
Global Generative AI market in billion US$
Global AI software revenue by industry: COVID-19 impact vs. 2019-2025 CAGR
Revenues from the natural language processing (NLP) market worldwide in billion US$
Chatbot market revenue worldwide in billion US$
Global Robotic AI market in billion US$
Global collaborative robots' market in billion US$
Stages of robotic process automation
Gartner’s magic quadrant for RPA as of July 2022
Leading AI capabilities adoption rate in business 2022
Global AI adoption rate in businesses
Leading use cases for AI in 2022
Expert estimation in the field of most impactful countries in AI innovation between 2022-2025
Potential annual GVA growth rates in 2035 in %
Impact of AI on labor productivity in developed countries in 2035
Impact of AI on workforces in organizations worldwide in 2020-2023
Impact of AI on industry growth in 2035 in %
Impact of AI on industry output in 2035 in trillion US$
Potential incremental value of AI as compared to other analytics techniques
Projected increase of GDP due to AI by industry sector in 2030
Share of projected worldwide AI contribution to GDP in 2030, by region
Illustration of the machine learning process
AI fundings in China in billion US$
China's AI investment by sector in 2019
Share of Tencent’s AI investments in 2014-2017
Global largest patent owners in ML and AI from 2012 to 2021 by number of active patent
Global AI software revenue projection in billion US$
AI-driven hardware market revenue in billion US$
Share of active AI investors in %
Worldwide big data analytics market in billion US$
Focus in this report
Unit shipments of AI-based systems for automotive industry in millions
Impact of deep learning on autonomous driving
Current hours worked in healthcare that could be freed up by automation by 2030
Technologies involved in AI healthcare
Business value derived from AI in banking industry worldwide from 2018 to 2030 in billion US$
Potential aggregate economic impact of AI worldwide in the future in billion US$
Start-ups funding and M&A
Number of AI start-ups
AI start-ups: Annual global funding in billion US$
AI start-ups: global deal share by region in Q4 ’22
Global Leading ML Operations/Platform startups in 2023, by funding in million US$
Global Leading chatbot/conversational AI startups in 2023, by funding in million US$
Number of newly funded AI companies by countries in 2021
Number of newly funded AI companies by countries in 2013–2021
Major fields of investment by leading AI enterprises