Artificial intelligence is used for industrial purposes for quite some time now. Yet, just a year ago, generative artificial intelligence entered into service and its acceptance was overwhelming. In essence, users were surprised by the facility that can churn out text, speech, videos, and complex code that resembles human-like work. The remarkable technology has indeed the potential to disrupt much of the work we perform on a day-to-day basis.
The addressable market is important. AI-enabled tools, delivered through the cloud, can address offline services in the value of $6 trillion in advertising, e-commerce, and travel. According to a research paper published by Morgan Stanley, some 40% of all activities, are potentially subject to be disrupted by generative AI. In the US, the associated labor opportunity cost is estimated to $4.1 trillion while in Europe, the same could exceed $4.4 trillion.
Embedded AI-enabled software will most likely perform personal services. This will not only have a front-end touchpoint impact but effects will be sensed throughout the entire service channel. Generative AI is expected to make processes more efficient, and more productive, and most importantly, it will contest day-to-day tasks that are presently performed by majority of the humanity. In other words, AI is challenging us with the archetype question of what is the purpose of humans on earth? While we can start philosophizing about this question, the immediate crux of AI is that it will have a deep impact on how we train and skill, actually reskill so that the workforce can continue to enjoy the benefits of any professional activity performed.
As for now, the foundational opportunity of AI offers software and software consulting enterprises to leverage and automate workflow processes. This workflow process review is expected to generate a revenue opportunity of some $210 billion in the next three years.
The current innovations in the field of NLP-based generative AI addresses the needs of entry-level activities such as sales, aftersales services, data entry, billing, proofreading, and switch-boarding, amongst others. Once generative AI applications will become more empowered, more sophisticated roles could become practicable. Typically, we would look at mid-level management functions, service management, discretionary management processes, and nursing, among others. Yet, generative AI in the space of enterprise software is still far away.
As of now, one of the major applications of AI is in the field of building video games. This includes the development software that allows creative work and writing. The video entertainment industry is therefore in a unique position to transform and enhance its business model as consumers spend some $300 billion on video displayed via mobile, PC, and consoles. The combination of these investments and AI-driven efficiency could result in more complex and ambitious product offerings, potentially boosting engagement and increasing game spending. Finally, we note that the level and speed of disruption in the field of e-gaming are expected to be fast as there are almost no entry barriers.
Investment ramification
AI will likely remain the key growth driver for the next generation of semiconductor demand. This trend is expected to stay strong well beyond 2025. Global research suggests that profit growth could reach 50% in 2024 and a slightly lower figure is projected for 2025.
Software and AI-enabled platforms have a higher performance potential than the remaining sector players as more industry sectors will switch their operations to some kind of AI-enabled processes. Therefore, software companies, software consultancy groups, and cloud providers are particularly well-positioned to monetize their products.
While IT companies are generally early-cyclicals, the sector offers exposure to late-cycles too. In essence, these are well-established companies that were successful in the transition to consulting and now engage with AI while maintaining outdated technology processes in place to secure important revenue streams.
The speed at which the artificial intelligence-powered chatbot ChatGPT moved from an embryonical studio experiment to boardroom acceptance is highly remarkable.
While up until very recently, open ChatGPT technology was governed by a non-profit Foundation. The board-level conflict that erupted some time ago was about how the ChatGPT technology should look in the future. The naïve perception of the foundation council that AI would not become fit and proper for commercial purposes, opened the gates for Microsoft to take a lead with a huge bet on the technology. The company made a strategic allocation of roughly $10 billion to take a grip on AI by catching up on the ChatGPT business opportunity.
For now, the collective AI fascination has some resemblances with hypes observed around ET, Star Wars, The Matrix, or The Terminator. This excitement occurred on the back of the fact that the global AI-based funding doubled to around $67 billion in 2021. As a result, a record of 65 AI companies reached a $1 billion-plus valuation. In 2024, the valuation of companies interconnected with AI is expected to progress further.
For investors seeking exposure to AI, here are some opportunities.
265 AI-related opportunities grouped by activity:
- Automation and Robotics
- Cloud services
- Cybersecurity
- e-Commerce
- Education/Schooling
- Energy/Environment
- Entertainment
- ERP / CRM services
- Financial services sector
- Healthcare
- Manufacturing/Engineering
- Vehicles/Transportation
Within the entire AI opportunity, our preferred plays are:
NVIDIA Corp
NVDA is the leading graphics chip company and as such, it has taken advantage of the AI boom. The graphics cards the company engineers are becoming the de facto standard in data centers around the world. Machine learning’s training phase demands a lot of GPU (graphic processing unit) capacities while the production phase, also known the application phase that follows, requires less.
Nvidia’s data center business represents a steadily increasing share of the company’s total revenue and looks set to top gaming in revenue in fiscal 2022. This segment isn’t all AI-related — Nvidia’s graphics cards are used to accelerate a wide variety of data center applications. But AI is one of the driving forces behind the company’s growth. Nvidia has a relatively large operational specter with its GPU cards. For instance, they are used in the coin mining process, a segment that somehow lost some of its attractivity given the crypto winter. Self-driving cars are another area of focus. Nvidia develops platforms, including hardware and software, that power and enable driver-assistance features. This segment will, over time, evolve into fully autonomous driving facilities.
A self-driving car must process massive amounts of data from multiple sensors and cameras in real time, detect objects such as pedestrians and other vehicles, and make complex decisions. They require a tremendous amount of computing power, and that’s exactly what Nvidia’s platform delivers. Finally, we note that its professional visualization segment, which includes its omnivores, is also growing quickly – revenues generated by the division were doubled in 2021 and another leg of 50% was added in 2022. Nvidia’s graphics cards could someday be supplanted by more specialized processors designed for AI, but for now, the company is in an enviable position.
IBM Corp
For many, IBM is considered a legacy tech company because of its historic development as an integrated provider of hardware, software, and services to large enterprise customers. Its AS400 mainframe systems are still ubiquitous in certain industries. The company continues to sign multi-year renewal deals to deliver an outdated technology that is invoiced hundreds of millions of dollars each. More importantly, the business unit seems to be very promising for the future as the company does not seem to plan any exit from it.
Within the AI segment, IBM is to apply its expertise in ways that augment human intelligence, increase efficiency, or lower costs. In the healthcare industry, IBM’s AI technology is being used to create individualized care plans, accelerate the process of bringing new drugs to market, increase the hit ratio in the field of diagnostics, and improve the quality of care. In the financial services industry, via the company’s 2016 acquisition of Promontory Financial Group, IBM is using AI to help clients with the daunting task of financial regulatory compliance.
While the market for AI products and consulting services is highly fragmented, IBM is leading the industry. Market research firm IDC ranked IBM as the leader in AI software platforms with a 13.7% market share in 2020, up 46% from the prior year. IBM is presently streamlining its complicated company structure. The transformation is expected to enhance the corporation’s AI potential. As a well-established technology consulting company, IBM is well-positioned to benefit from the AI boom.
Micron Technology Inc
Micron Technology manufactures memory chips, including dynamic random-access memory (DRAM) and NAND flash memory found in solid-state storage drives (SSD). Most of what the company makes are commodity products, meaning that supply and demand dictate pricing.
Historically speaking, the technical evolution in the SSD market occurs in intervals of around 2 years. Forecasting the consumer perception and the economic conditions vis-à-vis a new technology to be launched years ahead is extremely problematic. This time issue and the fact that MU is one of the purest early cycle companies, leads sometimes to a brutal mismatch in the offer and demand equation, resulting in some cruel boom and bust swings, where an under- or oversupply of chip supply significantly impacts profit margins either way. For instance, for the quarter ending August 31, 2023, the EPS was -$1.31. This was a significant decline from the previous quarter when the EPS was $1.37. Moreover, the EPS for the twelve months ending August 31, 2023, was -$5.34; in comparison, the EPS for the previous year was $5.14.
In 2021, demand for memory chips was strong, boosted by the growth of mobile networks, 5G, and cloud computing. A recovery in the automotive sector and a shortage of semiconductors have helped lift prices for Micron’s DRAM and NAND chips. In the current environment, profits are expected to surge in 2024.
In the future, demand for memory chips will only grow, and that’s especially true in the AI industry. Self-driving cars are a good example. All the sensors and cameras produce a lot of data — around 1 GB per second, according to Micron estimates. Data centers running AI processes need plenty of memory; and so do smartphones that may be doing AI work. Newer iPhones, for example, use AI with the camera function to produce improved images.
Micron will likely remain volatile due to the nature of its business. Even though AI is driving increased demand for memory chips in the long run, supply and demand reign supreme in the short term. Provided the investor can stomach volatility, MU is the company to look at.
Amazon.com Inc
AMZN is most likely the company that uses AI more than anyone can expect. Founder and executive chairman Jeff Bezos has been an evangelist for AI and machine learning. Although Amazon started as an online retailer, technology has always been at the company’s core.
Today, Amazon uses artificial intelligence for everything from Alexa, its industry-leading voice-activated technology, to its Amazon Go cashier-less grocery stores, to Amazon Web Services Sagemaker, and the cloud infrastructure tool that deploys high-quality machine learning models for data scientists and developers.
Amazon’s e-commerce business is also built on AI since algorithms run its engines with AI-enabled processes for any kind of recommendation addressed for consumers, be it e-commerce, video, or music streaming, amongst others. In addition, Amazon uses AI to determine product rankings.
Amazon’s logistics operations benefit from its AI prowess, which helps with scheduling, rerouting, and other ways to improve delivery accuracy and efficiency. Drone delivery is probably a service that is deployed next. If so, it would yet be another AI-supported application to support the business of the tech giant.
It’s difficult to quantify the impact of AI on Amazon’s business, but it’s a key component of the company’s competitive advantage. Throughout its history, Amazon has been at the forefront of emerging technologies such as e-commerce, e-books, cloud computing, video streaming, and voice-activated technology. AI provides much of the infrastructure that helps the company move into new businesses quickly and effectively.
C3.ai
C3.ai is less known by the main street investor. Yet, it may be the closest thing when it comes to AI. While most of the companies in the field of AI are somehow diversified tech giants or chip makers, C3.ai is a pure play in the field of artificial intelligence.
C3.ai is a SaaS company whose software allows companies to deploy large AI applications. The company’s tools help its customers accelerate software development and reduce cost and risk, and they have a wide variety of applications. For example, the U.S. Air Force uses C3 AI Readiness to predict aircraft system failures, identify spare parts, and find new ways to increase mission capability. European utility company Engie is using C3 AI to analyze energy consumption and reduce energy expenditures.
C3.ai has the first mover advantage (or disadvantage in case of failure) and the company stipulates that it isn’t aware of an end-to-end enterprise AI development platform in direct competition with it. That unique positioning could make the company a big winner over the long term, although the AI SaaS market is evolving fast and could attract competition from big cloud infrastructures such as Amazon or Microsoft, among others.