When the leader of the world’s largest bank composes 700+ official words on the impact of AI using the company letterhead, it’s a big deal. 

On April 10th, Jamie Dimon, Chairman and CEO of JPMorgan Chase, published his much-anticipated letter to shareholders as part of the company’s 2023 Annual Report. One of the most talked about sections was his “Update on Specific Issues Facing Our Company,” leading off with the extraordinary impact AI will have (and is already having) on the business. While Dimon’s statements, whether focused on the economy at large or JPMorgan Chase exclusively, are always parsed and scrutinized by the media and business world, his likening of AI to disruptive innovations like the printing press, the Steam Engine, and the Internet created instant media headlines, social media reactions, and even a few mini-rebuttals. 

Why? It’s likely because they represent a financial titan’s endorsement of a prevailing outlook—not even a hot take at this point—that AI will change the world as we know it. Even the biggest and oldest companies should act accordingly to seize the moment.  

“As transformational as some of the major technological inventions of the past several hundred years.” 

After summarizing the company’s 2023 results, Dimon pivoted to the forward-looking perspective, starting with his unequivocal statements on the massive impact of AI. 

“While we do not know the full effect or the precise rate at which AI will change our business — or how it will affect society at large — we are completely convinced the consequences will be extraordinary and possibly as transformational as some of the major technological inventions of the past several hundred years: Think the printing press, the Steam engine, electrioncity, computing and the Internet, among others.”

Let’s put that statement into bullet points so it fully sinks in. No less than Jamie Dimon just said he and his colleagues at the 200+-year-old megabank holding about $3.9T in assets are “completely convinced” that AI’s impact could rival:

• The printing press 
• The steam engine
• Electricity
• Computing
• The Internet

These inventions catalyzed the Enlightenment, the first and second industrial revolutions, and the information age (i.e., the third industrial revolution). JPMorgan Chase wouldn’t be the same company without those historically significant technological breakthroughs enabling it to grow and prosper. And if Dimon’s right, it won’t be the same company after the AI era, often put forth as the galvanizing technology that will spark a fourth industrial revolution.

Dimon pointed out that since he first cited AI as a strategic initiative in his 2017 shareholders’ letter, the company has ramped up its AI activities substantially and continuously, with more than 2,000 AI and machine learning experts and data scientists using predictive analytics across over 400 use cases in production today. He said that these AI projects “are increasingly driving real business value across our businesses and functions. We’re also exploring the potential that generative AI (GenAI) can unlock across a range of domains, most notably in software engineering, customer service and operations, as well as in general employee productivity. In the future, we envision GenAI helping us reimagine entire business workflows.” 

Moreover, he observed that many of these projects already pay for themselves. Capitalizing on the company’s troves of rich data using AI to serve its customers and shareholders better is the apparent goal—a process already well underway.

“Finally, as a global leader across businesses and regions, we have large amounts of extraordinarily rich data that, together with AI, can fuel better insights and help us improve how we manage risk and serve our customers. In addition to making sure our data is high quality and easily accessible, we need to complete the migration of our analytical data estate to the public cloud. These new data platforms offer high-performance compute power, which will unlock our ability to use our data in ways that are hard to contemplate today.”

Finishing up his statements on AI, Dimon announced the company has created a Chief Data & Analytics Officer who will sit on the company’s operating committee.

“Elevating this new role to the Operating Committee level — reporting directly to Daniel Pinto and me — reflects how critical this function will be going forward and how seriously we expect AI to influence our business. This will embed data and analytics into our decision making at every level of the company. The primary focus is not just on the technical aspects of AI but also on how all management can — and should — use it. Each of our lines of business has corresponding data and analytics roles so we can share best practices, develop reusable solutions that solve multiple business problems, and continuously learn and improve as the future of AI unfolds.”

Will AI be more like the steam engine or the Internet?

Ten days after his letter, you’ll find hundreds of results if you google ‘Jamie Dimon AI Steam Engine.’ It seems like many news outlets chose to key in on the steam engine analogy to serve a juicy headline, perhaps because it seems so quaint in contrast to AI, with the steam engine being such a well-known emblem of a changeover technology that brought us from literal ‘horse power’ to figurative horsepower. A thought-provoking opinion piece from Parmy Olson, writing for Bloomberg, challenged this metaphor, taking the opportunity provided by the sudden news cycle to respond to Dimon and others who use oversimplified terms to describe a technology category without clear precedent.

In “AI’s Advances Will Echo the Internet, Not the Steam Engine,” Olson contends: “Analogies are wonderful, but they should be picked with care when language has the power to shape opinion.” While she notes that Jamie Dimon isn’t the first to use the steam engine comparison and that he mentioned it alongside other milestone inventions to create a general frame of reference, not a defining convention, she hopes that we think of the Internet as the more apt example. She wrote: 

“Here’s a better analogy: The Internet. Not only did it seamlessly weave itself into the fabric of daily life, just as AI is doing, it evolved rapidly from its inception, revolutionizing media and the way we socialize and communicate. The ethical problems it created around privacy, surveillance and misinformation are rearing their heads once again with AI, as are those around the concentration of power among a handful of Silicon Valley gatekeepers such as Alphabet Inc.’s Google, Meta Platforms Inc., Amazon.com Inc. and Apple Inc.

Comparing AI to the internet offers a broader and more nuanced understanding of its potential impacts, not to mention one that hasn’t been softened by the passage of time. We can all still feel both the positive and negative side effects of the web on our lives.”

To change the world, address the limitations that slow down everyday workflows

Analogies are fun to think up and debate, but it all comes down to solving specific problems. 

The steam engine, computers, etc., solved a wide variety of industrial or communication issues at speed and scale, which is how they changed the world. 

Steam Engine

• Problem: Scarce human and animal labor for industrial tasks.
• Solution: Harnessing steam power for mechanical work, enabling mass production.

Printing Press

• Problem: Slow and expensive book production, curtailing access to knowledge.
• Solution: Mass production of books through movable type printing, democratizing access to information.

Electric Power

• Problem: Low-scale lighting and power sources, reliance on manual labor.
• Solution: Harnessing electricity for lighting, power generation, and automation, enabling widespread electrification of factories and cities.

Computing Power

• Problem: Tedious, error-prone, and time-consuming manual data processing.
• Solution: Automating data processing tasks through computing devices, enabling faster and more accurate analysis.

The Internet

• Problem: Limited global connectivity, barriers to communication and information exchange.
• Solution: Creating a decentralized global communication and information exchange network, connecting people and resources worldwide.

Artificial Intelligence

• Problem: Tackling complex and dynamic data-dependent problems that defy traditional computational methods.
• Solution: Leveraging machine learning, neural networks, and other AI techniques to analyze vast amounts of data, extract insights, and make informed decisions.

At SparkCognition, we focus on solving critical problems that turn on the ability to predict, prescribe, and automate industrial processes efficiently. One of the problems we address is preventing downtime in industrial assets. For example, on average, offshore oil and gas operators rack up 27 days of downtime annually, creating a $38 million cost for the industry. Using proprietary AI algorithms applied to historical data produced by critical O&G equipment, SparkCognition leverages anomaly detection models to understand a system’s ‘normal’ operating state, continuously evaluating the incoming data stream of sensor data to generate an alert when an irregular condition is detected. With this alert, the O&G operators have more lead time—often as much as thirty days—before a critical issue becomes urgent, so they can schedule repairs, address the problem, and avoid costly downtime. 

AI offers a unique approach to problem-solving, with the potential to tackle a much broader spectrum of problems than ever before by simulating human intelligence and learning capabilities. For JPMorgan Chase, AI use cases will likely take on financial fraud and risk prevention. For SparkCognition’s clients, AI use cases include predictive maintenance, prescriptive insights to speed up repairs, and visual analytics to reduce on-the-job accidents. As we reflect on the evolution of problem-solving through the lens of historical inventions and the emerging impact of AI, the details may change, but the pattern is the same: human ingenuity is unbeatable.  

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