What Cellular Waves Can Teach Us About the AI ​​Tsunami

We may be living in unprecedented times, but there is indeed a historical parallel to today. artificial intelligence The mobile wave that began with the launch of the iPhone in 2007 offers some lessons that can help businesses move forward with their AI plans.

That is the point of view of Scott Snydera senior fellow at Wharton, visiting professor at Penn Engineering, and chief digital officer at EVERSANA; and Julie askeda technology futurist, author, and former vice president and principal analyst at Forrester Research.

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AI, in all its forms, has been criticized for not delivering a return on investment, but all of this is familiar, as they point out in a recent report article posted at Knowledge at Wharton.

“From the beginning, most business leaders failed to grasp the scale of the mobile wave for their customers and employees,” Snyder and Ask note. “They focused on ‘building apps’ rather than transforming their business and operating models to fully unlock the mobile opportunity.”

Similarities Between AI and Mobile Devices

Both mobile AI and next-generation AI are disruptive technologies that are changing the way people work and think about their jobs. Here’s how the current wave of AI reflects the mobile wave:

• Bring your own X. The advent of smartphones gave rise to the “Bring Your Own Device” movement, which was often resisted by organizations concerned about the lack of security concerns about employees’ personal devices. Smartphones have become ubiquitous in the enterprise anyway, and technology leaders have opened up tools that users feel help them do their jobs better. Likewise, the self-driven, off-premises nature of ChatGPT and other generative AI tools means that the technology’s use arises outside the walls of enterprise technology. Both are examples of the call to “empower your employees, or they will innovate around you,” Snyder and Ask illustrate. “Companies must now adopt “BYOAI” with appropriate controls to enable employees to use the latest generation of AI tools to increase productivity and innovation while protecting enterprise data.”

• Both the mobile AI movement and next-generation AI represent democratized approaches to computing. Mobile devices and their associated app stores have provided “an intuitive interface, combined with a powerful computing platform, that has attracted users globally,” Snyder and Ask point out. “Similarly, the latest generation of AI offers unprecedented new capabilities that can generate content, conduct analytics, and allow humans to interact with machines in more natural ways.”

• Both mobile and AI are built on an ecosystem of partners and supporting technologies. The rise of mobile-enabled services has been made possible through “large and ongoing investments in advanced device technology, cloud computing, developer platforms, data centers, and mobile networks,” Snyder and Ask point out. “The same goes for next-generation AI.”

• Mobile and AI leverage data — and lots of it. Ultimately, both waves of technology consume data and are working together. “AI companies are creating personal AI devices that help us envision a future of virtual assistants and agents accessed through natural language. As with mobile devices, innovative products and business models will follow,” they illustrate.

The difference

There are differences, too. Snyder and Ask point out. “While mobile computing has seen steady adoption and growth globally, AI’s self-improvement capabilities, coupled with increasing regulatory scrutiny, will create a nonlinear, unpredictable trajectory, unlike the steady rise of mobile.” The impact of AI will be different from mobile due to the following factors:

• Mobile is hardware dependent, AI is mostly software for end users. “Consumers will adopt AI faster than mobile devices because consumers don’t need to buy new devices,” the co-authors point out. “The growth of mobile devices initially depends on consumers upgrading their smartphones every 18 to 24 months as well as building more capable networks or infrastructure. While hardware manufacturers are building their next generation of devices with local LLM, most of the big computing will be done in the cloud, which means consumers can start with the devices they already own.”

• The pace of change will be even faster on mobile because AI will work automatically. “Capabilities are advancing rapidly despite the need for resources such as GPUs, energy, data, and human training, as well as ethical, safety, and regulatory concerns,” Snyder and Ask note. As AI capabilities develop, “these tools will begin to create their own experiences and no longer rely on human labor. Agents will begin to self-regulate and work together.”

• The cost of customer and business acquisition will be higher for new mobile app entrants. “Gen AI will initially augment existing services. Think Siri or Microsoft Copilot for employees. Apps will need history and data about the individual to evolve into true virtual assistants. Anticipating needs and providing contextual or personalized experiences will ultimately increase switching costs.”

• Factors beyond the control of LLM practitioners will limit growth. Large language models face more hurdles than business models or mobile ecosystem capacity constraints, the coauthors observe. “State-of-the-art models require more data or training content. While LLM can generate synthetic data, further advances rely on content and physical world data that is not readily available.” In addition, physical constraints on AI include “access to GPUs for training or the electricity, water, and manpower required to train models.” There is also the specter of government regulation of AI.

Snyder and Ask advise embracing the lessons learned from the mobile wave.

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“Too many companies are rushing into next-generation AI experiments with little or no idea how they expect to measure real business impact,” Snyder and Ask warn. “Like mobile devices, next-generation AI brings new superpowers to end users and has the potential to dramatically transform how companies operate and deliver value to customers. Leveraging the lessons from the mobile wave can only help us be better prepared for what’s coming.”