Top 9 US AI Stocks for 2022

The hardware backbone of the shift to AI.

• The company’s position as an industry leader in hardware manufacturing for commercial data centers means that its success is tied in closely with the success of AI in revolutionizing the business environment. The more companies incorporate AI into their business’ strategy, the larger Nvidia’s addressable market becomes.
• Nvidia plans to deliver the world’s most advanced enterprise AI infrastructure in their DGX H100 systems. The DGX H100 systems provide 6x more performance in serving most demanding AI computing applications compared to the previous generation.

AI empowers a robust, lightweight and scalable anti-virus.

• CrowdStrike uses AI to train their threat prevention systems helping them deliver a more robust and secure Anti-virus solution than traditional methods. The tiny 15MB AI model processes threat-based telemetry to provide an up-to-date and dynamic risk rating of incoming threats. The scalability, accuracy and low-overhead of CrowdStrike’s AI models provide the company with a competitive advantage over its competitors in the Anti-virus software segment.

Recent acquisitions to push for a first-to-market autonomous vehicle solution.

• If Ford is able to deliver a large-scale market-leading self-driving solution through its partnership with Argo AI, the company will reap the benefits of being first-to-market and will solidify a position in a new automotive ecosystem. Studies conducted by KPMG indicate that self-driving vehicles will drastically reduce traffic deaths, commute times and harmful emissions. Should Ford provide the best self-driving solution, these benefits will be a powerful sales tool for a self-driving fleet.
• The recent acquisition of Quantum Signal in July 2019 shows that Ford is progressing down the self-driving path. The hope is that this acquisition further supports software development and hardware prototyping in their efforts to develop autonomous transportation services.

Allows other companies to onboard AI analytics easier and more cost effectively.

• Gartner still predicts that 85% of traditional AI and ML projects developed within organizations will deliver erroneous outcomes. Palantir addresses this by providing businesses with the data infrastructure off which they can build out their AI analytics tools. Foundry’s latest integrations with Amazon Web Services’ (AWS) AI and ML tools will mean that Palantir’s customers will have access to the benefits of AI without the costly in-house development process.

High customer retention.

• Government contracts are 56% of Palantir’s customer base by revenue. Palantir’s recent annual report details the high levels of retention among Government customers. Provided the number of Government contracts awarded continues to grow, Palantir can drive a high net dollar retention thanks to the relative ’stickiness’ of their customers.

AI fraud detection gives customers peace of mind.

• A booming online shopping industry has opened the door for fraudsters to take advantage of unsuspecting customers. Data from AusPayNet over the 12 months to 30 June 2021 show credit card transaction fraud has increased by 9.2% to $490.1 million in Australia alone, as total spending on cards rose to $847.3 billion. Visa, the world’s leader in digital payments, isn’t usually a name you’d associate with AI; however, they’ve recently announced their AI-driven security has prevented more than AU$354 in fraudulent transactions with Australian businesses last year. Visa’s fraud detection algorithm, which leverages AI analytics, assesses more than 500 risk attributes in about a millisecond to produce a score of every transaction’s predicted fraud probability. By employing AI into their business, Visa has been able to drastically improve fraud detection levels which reduces financial losses and encourages customers to choose Visa as their payment processor - thereby increasing the revenue from transaction fees.

Making credit assessments easier through the power of AI.

• Credit is an important part of life. Housing is getting more expensive relative to income and so it’s becoming a necessity to have access to the appropriate financial services to secure loans. However, with interest rates rising, many families are finding the loan approval process to be time-consuming with approval far from guaranteed. Upstart is an online lending platform that partners with banks and credit unions to improve access to affordable credit. The company incorporates AI into their risk analysis process to improve the accuracy of their risk identification and lower overhead. Their AI model risks like income fraud, acquisition targeting, loan stacking, prepayment prediction and identity fraud. By incorporating more than 1,500 variables, Upstart benefits from a detection algorithm that learns as input data grows. Compared with traditional lenders, Upstart’s AI integration has significant competitive advantages, their model has helped consumers secure higher approval rates and lower interest rates at the same loss rate. Upstart’s lending partners also reap the rewards as they gain access to new customers, lower fraud levels and a more efficient lending process.

Enterprise AI software for a changing business landscape.

• Industry 4.0 will see organizations utilize AI software to increase efficiency, reduce costs and improve operations. Unfortunately, developing company-specific AI solutions is a costly resource intensive process. C3 AI offers a solution to this issue. C3 AI is one of the leading tech companies in the AI space that is partnering with industry giants like Koch Industries, Shell, US Air Force, Petronas, Google, Engie to help them achieve a competitive edge. The company delivers turnkey AI applications for high-value cases and supports this with a family of products that assist with data analysis and further software deployment. The heavier our future relies on AI, the more successful C3 Ai becomes, as its enterprise AI solutions will be in hot demand from companies looking to get a competitive edge.

Revolutionizing healthcare solutions with IBM Watson Health.

• When it comes to AI, IBM’s Watson is one of the oldest and most recognisable names. Watson has grown in scope and reach since its inception, ranking first for market share in IDC’s AI market 2020 report. Watson has had a high level of penetration within some core industries, finding use in upwards of 70% of global banking institutions. To put it simply, a large proportion of the population has their life improved by Watson and they may be unaware of it. New advances in medical technology, growing healthcare demand and changes in medical policy have opened the doors for IBM Watson to enter into the healthcare segment. Thanks to new medical technology, the amount of data the healthcare industry has access to is growing rapidly, yet without the proper tools, this data can go under-utilized. IBM Watson Health has been developed to assist medical practices and healthcare organizations to analyze this data effectively so that they can deliver medical decisions faster, more accurately and at a cost-saving. In assisting medical professionals integrate these new medical technologies into practice, IBM Watson Health can improve clinical outcomes for patients while ultimately reducing the costs and labor overhead associated with dealing with greater volumes of patients.

Developing software robots to emulate human interaction with digital systems.

• When it comes to integrating software into business, the most common source of issues isn’t bugs within the software, rather how we error-prone humans interact with it. UIPath’s Robotic process automation (RPA) aims to solve that by creating software robots to do repetitive and lower-value work, like logging into applications and systems, moving files, extracting and inserting data, filling in forms, and completing routine analyses and reports. Now, it’s important to distinguish that UIPath’s RPA isn’t AI in itself, rather it can be used alongside AI to enhance the use case of the RPA. UIPath’s recent acquisition of natural language processing company Re:infer has allowed the company to implement ML to allow RPA robots to contextualize unstructured documents and communications and transform them into interpretable data for use. AI trained robots can perform higher value processes, like interpreting text, engaging in chats and conversations, understanding unstructured data, and applying advanced machine learning models to make complex decisions. UIPath’s AI enhanced RPA software will help improve enterprise productivity by freeing up time for human input to be allocated where it’s most needed.