Depending on which advisory firm or investment bank you ask, the total addressable market for artificial intelligence technologies in coming years could range from $1.3 to $4.4 trillion dollars annually, with a compound annual growth rate above 40 percent.
Those are absolutely “wow” numbers. To put that in perspective, $1.3 to $4.4 trillion is comparable to the GDP of entire nations, from Türkiye to Japan. It’s no wonder venture capitalists are tripping over themselves to invest in AI startups.
Those rosy projections are set against a more pessimistic backdrop. The release of DeepSeek has likely ushered in an era of commoditized AI, and possibly upended business models of major players. High AI deployment costs, unclear ROI, chip shortages and power constraints have slowed adoption. Concerns over AI-driven cybercrime, environmental impact and ethical risks like bias and data inaccuracy have made some wary. Fewer than 7 percent of U.S. companies used AI in 2024, according to a survey from the U.S. Census Bureau.
Looking to past technology cycles, some have pointed to the bursting of the dotcom bubble in early 2000 as a foreboding blueprint for the future of AI adoption. I think the rise of mobile technology is a more salient model.
Lessons from mobile technology
To make the comparison between AI and mobile, I want to introduce a rubric that has informed some of my thinking: the difference between a digital evolution and a cultural revolution.
Technology becomes a digital evolution when it fundamentally changes how businesses operate. It improves processes, enhances accessibility, delivers economic benefits and integrates with other technologies. It evolves over time through feedback and innovation.
Mobile technology has profoundly changed the business environment. With over half the world connected, mobile tech has fueled e-commerce, banking and app-based services. It enhances accessibility, delivers economic benefits and integrates other technologies like cloud computing, GPS, cameras and sensors, to name a few. It has been especially transformative in underdeveloped areas, improving access to digital infrastructure for those who might otherwise lack access.
A cultural revolution goes further, reshaping society and daily life.
Mobile technology has altered how we communicate, work, learn, shop and entertain ourselves, and has created new social norms and behaviors. It has influenced language through texting slang and sparked phenomena like selfie culture. Particularly transformative in financial inclusion, mobile banking has brought financial services to underserved communities. Although mobile technology raises regulatory issues like data privacy, these are generally well-managed through established frameworks.
Mobile technology is both a cultural revolution and digital evolution. But as you will see, AI has so far fallen short of this dual definition in several ways.
As a digital evolution, AI has driven advancements in healthcare, finance and transportation by enhancing automation and democratizing content creation. Despite these achievements, its impact is limited by the above-mentioned slow adoption rates, high deployment costs and risks like accuracy and bias. The infrastructure for AI, including data centers and specialized hardware, is still developing. Integration challenges with other technologies like IoT devices further complicate its widespread adoption.
AI has cultural effects, but it’s too early to call it a revolution. Most of us experience it through behind-the-scenes applications like recommendation systems and chatbots. AI also presents ethical challenges, including algorithmic bias and privacy issues, with regulatory frameworks still evolving. All of these limit its impact as a cultural revolution.
Strategic directions for AI in business
We know that AI will likely lead to rapid shifts in daily life and in business, but exactly what form those shifts will take is still to be determined.
For businesses, there are strategies to safeguard against future disruptions and seize upcoming opportunities for growth.
First, businesses should prioritize AI projects with clear, measurable benefits to mitigate risk and build capabilities to take advantage of future opportunities.
Second, companies should invest in AI-ready infrastructure, including scalable cloud services, data storage and GPUs. This infrastructure will support the demanding tasks that AI requires and ensure that businesses can scale their AI solutions as they grow.
Third, don’t ignore the talent pipeline. Cultivate an in-house team of AI experts or establish partnerships with AI technology providers to drive innovation. Training existing staff through workshops and courses can also demystify AI and encourage a culture of innovation. Collaborations with universities and tech startups can provide fresh insights and access to cutting-edge research.
Finally, stay informed on AI developments and directives to remain agile and compliant with broader regulations.
Evaluating AI’s current impact and future potential
AI is on a solid trajectory to become a foundational element of digital evolution, akin to mobile technology. However, it is not yet as mature or widespread due to its ongoing development, complex integration requirements, regulatory and ethical challenges and the specialized nature of many current AI applications. As AI continues to evolve and become more integrated into everyday life, its cultural impact is likely to grow, potentially reaching a level comparable to that of mobile technology. But it has not yet achieved that status due to its less consumer-ready visible presence, slower adoption pace, accessibility issues and complex ethical challenges.
This scenario will definitely change, and quickly. In two to three years, this comparative analysis will more than likely present a considerably different picture of AI’s digital and cultural importance. Act soon, stay informed and adaptable and your business may be a part of its dominance.
