US is ranked as the number one country for AI across all categories & aspects such as , number of companies & experts, funding, patent applications & papers published on AI etc.
In addition, historically, majority of funding has also been invested in the US.
- Definition / Scope
- Market Overview
- Key Metrics
- Market Risks
- Market Trends
- Industry Challenges
- Technology Trends
- Other Key Market Trends
- Market Size and Forecast
- Market Outlook
- Technology Roadmap
- Competitive Landscape
- Competitive Factors
- Key Market Players
- Strategic Conclusion
Definition / Scope
Artificial Intelligence or AI is the simulation of human intelligence processes by machines especially computer systems. Generally, these processes include reasoning, learning and self-correction. Some of the applications of AI include, expert systems, speech recognition and machine vision
An AI can be categorized as either weak or strong. For instance, a weak AI is known as AI whose system is limited to performing certain tasks only whereas strong AI is also known as artificial general intelligence, which is a system with generalized human cognitive abilities. In such case, AI is able to find solutions without human intervention
In case of USA, the AI application ranges across several industry verticals that include:
Transportation: In transportation, US is mostly focused on drones and self-driving vehicles. The use of drones is being researched on areas such as delivery of household goods, improve safety of dangerous occupations and expand access to life-saving medical supplies.
Similarly, the deployment of automated vehicles has potential to reduce serious car crashes, which is expected to be the result of 90% of human error. The application of such vehicles will also present new transportation options for Americans with disabilities & senior citizens
Healthcare: In America, the Trump administration is investing advance medical research to treat 250,000 American lives against a dominant condition called Sepsis. AI is set to enable innovative solutions to treat sepsis via machine learning algorithms.
In addition, CMS is distributing up to $1.6 million to encourage AI and real-world application in healthcare. Further, FDA is also for the first time allowing marketing of AI technology that can detect eye problems caused by diabetes
Manufacturing: The AI is planned to be deployed across several areas in manufacturing which include, defense industrial base, supply chain, employment etc.
The National Institute of Standards & Technology (NIST) is also working to provide guidelines and best practices for introducing wireless technology into smart manufacturing.
In April 2018, the institute also published guidelines and best practices for introducing wireless technology into smart manufacturing and AI is set to mitigate the threats related to cyber security as well
Financial Services: The department of treasury is growing at a fast pace and it is pursuing policies to promote the adoption of innovative tools such as AI and machine learning.
In addition, the US Securities Exchange Commission is also aggressively implementing machine learning algorithms to monitor and detect possible investment market misconduct.
Also, Consumer Financial Protection Bureau (CFPB) has also issued new policies to allow for an increased use of data & ML algorithms in financial products and services
Agriculture: One of the biggest challenge that the agriculture sector is facing today is need of feeding 2 billion people by 2050 and the US department of agriculture has positioned farmers, scientists, educators and American public to benefit from AI through innovation.
Some of the uses & application of AI into agriculture that the government is set to foster include, agriculture production, rural community support, sensor development, workforce development, weeding pesticide application, fruit harvesting, watershed models to maintain resilience of agricultural systems
Defense: USA is set to invest in AI & other emerging technologies for military applications. The department of defense is also funding for technologies supporting AI such as quantum information science, strategic computing etc.
In AI, the DoD aims to deliver AI-enabled capabilities to its end users and also develop common foundation of shared data, reusable tools, frameworks and standards essential in scaling the impact of AI across DoD
US is ranked as the number one country for AI across all categories & aspects such as , number of companies & experts, funding, patent applications & papers published on AI etc. In addition, historically, majority of funding has also been invested in the US
US also has highest number of start-up’s venturing into AI sector with funding more than $1 billion. The US government is also spending more on long term research & development activities rather than independent research conducted by companies in the field which has positioned US as the most innovative country for AI
In the global scenario, US dominates the AI from several perspective. For instance, US has the second highest number of patent filed in AI after China i.e. 24.8% of the total global share.
US has highest number of experts/talent in the field i.e. 16.5% of the global AI talent. Next, US has also the highest number of companies in the sector i.e. 41% (2,028) of the total companies operating in AI belong to US
Some of the major risks that AI technology poses for the overall consumer and industrial markets and overall humanity are as follows:
AI could be programmed to do something destructive. For instance, autonomous weapons are artificial intelligence systems that are programmed to kill.
If these weapons fall in the hands of wrong person, these could lead to mass casualties. In addition, AI arms race could involuntarily lead to an AI war that also could lead to mass causalities, as these weapons would be designed to be extremely difficult to simply turn off and humans could lose control of such situation.
This risk at present is narrow but as the levels of AI intelligence and automation grows, so will the risk of AI war
Even though AI system might be programmed to do something beneficial, the technology itself could attract destructive method of achieving its goals.
For instance, if a super intelligent system is tasked with ambitious geo-engineering project, it might wreak havoc with our ecosystem as a side effect and could misunderstand human attempts to stop it as a threat
Thus, it is essential that the goals of AI need to align with the goals of humans so that AI could be beneficial for humanity.
Federal Funding: In the US, government has placed R&D for AI as a top priority. In June 2019, AI & National Science Technology Council released an updated version of National AI R&D Plan that includes several strategies to guide the portfolio for AI R&D investments.
The President’s upcoming FY2020 Budget has also allocated about $1 billion for AI R&D for the year naming it as the second highest priority after security for American people. In addition, in 2018, the US Department of Defense also announced that it would dedicate about $2 billion in the period of next 5 years for advancements & innovation across AI.
The existing funding that the government has deployed is already supporting 20 projects and dozens of projects are in queue to be funded. Thus, government funding and initiatives to support AI businesses financially & technically is encouraging startups growth in the AI sector
VC firms are also responsible for driving growth in the AI sector. As AI is one of the most potential technology, US VC firms are positive about realizing fair ROI’s and are aggressively looking for promising AI startups to invest in.
In the US landscape, Y Combinator is the most popular investor with 34 rounds in 25 AI startups including companies: Sift Science, Chute, Qventus and SimpleLegal. Among AI fields, computer graphics & imaging has the largest number of investors i.e. 239 to be exact followed by robotics and machine learning.
Among the top VC firms in the sector, each VC firm in an average has made around 22 investments
In the US, in 2018, 28% of the companies have reported that they are not using AI. The primary reason for doing so is budget constraints (50%), followed by lack of technical expertise (36%), unproven ROI (30%) and lack of C-suite or Broad Buy- in (16%) respectively.
Some of the technical challenges presented by the AI technology are as follows:
At present, AI technology face multiple real-world challenges, for instance, machine learning generally requires large amounts of human intervention to label the training and data necessary for managed learning
Next, gaining access to data sets that are sufficiently large and comprehensive to be used for training for instance, creating enough clinical-trial data to predict healthcare treatment outcomes more accurately is also challenging
The complexity of deep learning techniques also creates challenge of “explainability” or showing which factors led to decision or prediction and how.
This has to be considered especially in applications where trust matters and predictions carry societal implications, as in criminal justice applications or financial lending. Thus, there is need of models that lead to increased transparency
The final challenge is that of building generalized learning techniques. As AI techniques continue to have difficulties in carrying experiences from one set of circumstance to another it is necessary to embed ‘transfer learning’ feature into the system, in which an AI model is trained to accomplish a certain tasks and then quickly applies that learning to similar but different activity
The AI technology is disrupting several sectors and is helping to solve problems that currently exist. So far, the technology has 37 applications across several industry verticals which are as follows:
In healthcare: There are four basic application being undertaken in the sector which include, medical imaging & diagnostics, clinical trial enrolment, improved healthcare biometrics and efficient drug discovery.
The first one, medical imaging reveals the internal aspects of a body through noninvasive process of imaging. The smartphone device is becoming all-in-one-tool for at-home diagnostics.
Second, with the help of AI, information available in the medical records can be compared to ongoing studies which in turn results to effective treatment.
Finally, healthcare biometrics is opening doors to retinal scans, examining and recording skin color changes among others that is set to unlock potential to new & convenient diagnostic methods
In retail/ecommerce: One of the biggest advantages of AI is search technology where SaaS companies have arrived to deliver search technologies to third-party retailers.
Second, companies such as Amazon Go are introducing Checkout free AI system where customers can checkout simply through their smartphones without requiring a cashier to scan the products or make a bill.
For logistics & warehousing, companies are utilizing proficient robots that will be able to work 24×7 and finally, retailers are also set to use crypto currencies for payment options at their store/sites
In public/government sector: Some of the major applications across the public sector include, facial recognition where it is being used mostly across security agencies and across governmental departments as a part of biometric authentication.
Next, surveillance is being handled via computer vision. Computer vision in addition with drones is also aiding in surveillance at crowded places
In transportation: Self-driving vehicles are one of the core examples of use case of AI in transportation. The technology is set to deliver $173 billion of cost savings across the overall OEM supply chain.
Next, traffic management is also being predicted & detected with help of AI & advance analytics which is protecting people against road accidents
In manufacturing: The most significant use of AI in manufacturing is predictive maintenance where algorithms deploy constant data collection to forecast equipment failures before they happen.
This has been led by multiple other factors such as sensor dropped costs for sensors and edge computing. Another technology trend being considered highly is collaboration of human and robots that will enhance productivity level of the factory greatly
In finance: In the finance sector, maintaining records on customer data is a kind of second nature. With help of AI financial institutions & banks are examining risks involved in the sector and mitigating them.
Another application is use of algorithms to recognize odd patterns in transactions to identify if fraud has occurred. The final one is particularly becoming useful for insurance companies where AI and data is helping companies determine “risk score” of individuals and also identify fraud claims.
Thus, based on the AI, insurers are able to make claim processing automatic
AI Initiatives by Federal government: In March 2019, the US Federal government successfully rolled out AI.gov to make it easier for everyone to access all AI related initiatives by government currently being undertaken. The site gives insights towards US AI strategy.
- In February 2019, US President, Donald Trump issued an executive order launching American AI initiative. The Order further highlighted that the government not only plays role in funding of AI technologies/businesses but also in promoting trust, facilitating experts, protecting security and interest of the country in regard to AI developments.
- Further, the American AI Initiative stands upon 5 principles which include, driving technological breakthroughs, driving development of appropriate technical standards, training workers with the skills to develop & apply AI, protect American values including civil liberties and privacy, protect US technological edge in AI while promoting an environment for innovation.
- The Executive Order has also assigned NSTC Select Committee on AI to coordinate all AI related initiatives in the country. AA executive departments and agencies are accountable to plan budget for AI into next fiscal year (2020) and thereafter. Some of the determined objectives of the committee in relation to AI include: promoting continued investment in R&D, reducing obstacles in implementation of AI, ensure technical standards to minimize vulnerable attacks, training AI researchers among others.
State & Local AI policies: Several policies have been introduced at state & local levels in the field of AI. For instance, in August 2018, California state issued a policy in support of Asilomar AI Principles- set of 23 guidelines for safe & advantageous development of AI.
In addition, California has also made it mandatory to disclose the identity of a bot that it is not a human. Also, the Consumer Privacy Act passed in June 2018 requires informing public about how their information is being used, this keeps their data protected against being sold to third-party.
- Other initiatives include, AI task force introduced in Vermont in May 2018 and Future of Work Task Force in Washington in March 2018. Both of these state regulations are focused on making recommendations to use of AI across government sector. Other city level notable policies include, Facial recognition ban in San Francisco passed on May 2019 and New York Algorithm Monitoring Task Force which keeps an eye on with how city agencies are using algorithms to make decisions that affect the city inhabitants’ lives.
Other Key Market Trends
In 2018, 93% of the business companies’ executives in the US believe that AI has a positive outcome within their industry compared to 69% in 2017. The implementation has also escalated from just 48% in 2017 to 72% in 2018.
In addition, 64% of the companies also expanded AI across several business processes. Also companies hired more staffs across AI related skills & roles such as, 56% increased data scientists and 54% created new roles focused on emerging technology.
AI also seems to be beneficial for these companies who have deployed the technology. For instance, 57% companies believe that AI is helping them improve product development processes and 54% have found positive results around optimizing control & collaboration.
Finally, AI is implemented most across the financial services and healthcare sector. 60% of the healthcare executives have devised AI related strategies across their operational processes. While 66% of the Financial services executives have incorporated AI & machine learning technologies into their platforms.
Market Size and Forecast
- As of 2018, the market size of overall AI technology in the global market was valued at $20.6 billion and is expected to reach $202.5 billion by 2026 with a CAGR of 33.1% during (2019-2026) period.
- According to the regional analysis, the market share of US market and North American regional markets were as follows:
- The North American market was the dominant region accounting approximately 47% of the total global market i.e. at $9.7 billion market value. The region is dominant in analytical tools, Natural Language Processing and machine learning capabilities.
- US accounts almost 90% of the AI market share of the North American region i.e. in 2018, the market value of AI in the US was around $8.6 billion respectively.
- Among the several segments of AI industry, autonomous robots are rising the fastest at 31% y-o-y and have the largest share of market at $3.5 billion
- Followed by autonomous robots, digital assistants, neurocomputers and embedded systems are growing at 30%, 22% and 19% y-o-y. Their respective market sizes are $2.5 billion, $1.5 million & $877 million respectively.
- Lastly, expert systems are growing at 12% y-o-y and their market size as of 2018 was around $705 million respectively.
- By 2035, the predicted market value of AI sector in the US is $8.3 trillion. The market value is expected to be highest among all leading country markets in the world such as UK, China & Japan. To realize a value of $8.3 trillion by 2035, the US AI market must grow at a rate of 99.8% respectively.
- At an industry level, by 2020, the sectors that would heavily invest in the AI technologies include, Internet, telecommunications, research, retail and marketing & advertising.
- By 2025, there will be about 191 use cases of AI across multiple areas within several sectors. Among those 191 use cases 40% will be related to image & object recognition whereas 60% will be related to big data.
Distribution Chain Analysis
- In 2018, AI startups from over 40 US states catered to different industries such as marketing, healthcare, retail among others. Funding or VC in AI startups is increasing tremendously. In addition, top 3 states for AI deals are: California (48%), New York (12%) and Massachusetts (9%) respectively.
As of 2018, considering the startup scene in the country, US has more than 50 individual consumer-facing AI companies with financing of more than $ 9 billion. In addition, there are 1800 AI investment firms in the US that are continuously supporting the private funding for AI in the country.
As of 2018, the total companies in AI sector in the US were 1,078, which is also 41% of the total 2,542 AI companies present worldwide. Thus US ranks number one in terms of number of companies present. Followed by US is China with 592 companies.
In the US, there are about 78,700 AI experts currently involved in R&D and innovation of AI technology.
The three major factor required for development of AI are: computing power, data and algorithm. As computing power is related directly to chip, the development scene of chip industry in the US is also favorable.
As of 2018, 33 chip companies had a total fundraising of $4.24 billion. In addition, these chip companies are mostly focused on advance capabilities such as GPU and quantum processing which is expected to support advance AI development capabilities.
In 2018, VC’s invested around $9.3 billion into US AI startups which is also 8 times of the funding that was 5 years ago (%1.1 billion in 2013) The four startups that have raised over $6 billion included leading companies such as Butterfly Network (Connecticut, $350 million), Welltok (Colorado, $339 million) and Inside sales.com (Utah, $264 million).
Among top 40 funded companies, the well-funded US AI startup in 2018 is Nuro with approximately $1 billion in disclosed equity funding including a $940 Series B funding from SoftBank.
The startup, Nuro is focused on developing AI enabled feature (last mile delivery) for autonomous vehicles.
Other well-funded companies include, New York’s UiPath ($1 billion) and Illinois Avant ($655 million). Altogether, 14 startups have raised over $100 million in disclosed equity funding including, Argo AI ($500 million), cybersecurity company StackPath ($180 million) and fintech company Opera Solutions ($122 million) respectively. Other 29 startups have raised more than $10 million in equity funding.
|State||Startups||Funding (in million dollars)|
|New Jersey||Opera Solutions||122.2|
Key Market Players
As of 2018, top 9 unicorn startups in the US based on their net worth include:
- Indigo Agriculture
- Butterfly Networks
Some of the pioneer brands in the US that are developing innovative AI application/software include:
- Apple Inc.
|Startups||Type of Business||Market Valuation (in million dollars)|
|UiPath||Autonomous vehicle software provider||$7100|
|Indigo Agriculture||Agtech startup||$3500|
|Nuro||Autonomous vehicle software provider||$2700|
|Insidesales.com||AI-powered predictive sales platform||$1700|
|Butterfly Networks||Healthcare AI||$1300|
|OutReach||Business sales communication platform||$1100|
|Apple||Technology- electronics||$2.4 trillion|
|Amazon||Specialty retail||$ 1.7 trillion|
|Internet, content & information||$1 trillion|
|Internet, content & information||$406 billion|
|IBM||Internet technology services||$791 billion|
|Salesforce||Software application||$84 billion|
Artificial Intelligence is experiencing both innovation and growth in the US market. Investments into AI companies have also grown sharply since past few years in the country and is presently at an all-time high.
However, where AI stands and what will it look like in near future is almost impossible to predict but undeniably it is also one of the most disruptive technologies of all time that is impacting industries, consumers and society as whole.
For the US, AI is set to create a strong economic impact on the GDP as the country is putting a lot of effort and emphasis on becoming the world leader in AI through innovation and cutting-edge research.
With development of other technologies such as quantum computing, AI innovation will surely accelerate in the country.
- DoD- Department of Defense
- ML- Machine Learning