There is incredible excitement about the prospect of a new world with the coexistence of artificially intelligent automata. The popularity of AI assistants is accelerating, and public perception and excitement of their potential seems boundless. At the same time, suspicion of over-hyped promises and looming concerns of rampant speculation are becoming more prevalent.1 The rapid expansion of experiments, prototypes, and deployed products with AI technologies is exacerbated by a swift mainstream adoption of computer programming. This reflects an unprecedented facet of the digital age. The natural tension between the optimistic AI standard bearers and the skeptical pragmatics creates uncertainty with the adoption of AI technology.

What’s going on?

While there are many possible future scenarios that may unfold in the coming years, at least one underlying current will prevail; the application of machine learning, generative AI, and agentic AI will endure for several decades. The progression of the next half-decade will shape the quality of our life for generations. We are approaching an inflection point in the third-stage of the fourth industrial revolution.2 I recognize witnessing and living through substantial change can be scary. It is also exhilarating. During these periods of swift technology adoption, it’s important to look at trends, validate assumptions, and reality-check our fears. The global economy will experience a rapid expansion for the first time since the invention of the assembly line. This is fueled by AI and the digital information technological revolution.

Naturally, these phenomena will cause growing pains, and we will feel the brunt of these changes over the next five years. In times like these, when it feels like the world is changing around us, and we’re afraid of being left behind, it’s essential to ask two questions3:

  1. What’s happening? (i.e., what’s changing?)
  2. What’s not happening? (i.e., what’s stable?)

After answering these basic questions, deeper analysis and reflection are useful. This will lead to more insightful questions with actionable solutions. Consider asking yourself these questions:

Which aspects of my life are likely to be impacted by this change? What skills do I possess that I will rely on? What new skills or knowledge gaps are missing that I will be required to learn? Who will benefit most from these changes? Who will suffer or become irrelevant? What can I do to influence the action or outcome?

When answering these questions, be as specific as possible. Seek evidence to question and reality-check the myths and fears.4

How did we get here?

It took over 2400 years for humanity to progress from the concept of intelligent automata to creating the theoretical foundations of computer science and artificial intelligence5. It took another half-century to produce a viable deep-learning proof-of-concept, and a decade more to deploy a production-grade global-scale AI system2. New versions of generative AI models are released every few months. We need to pay attention. These trends are real, they are becoming more intense, and the events are occurring faster, even if their potential may be over-hyped.6

Three years before ChatGPT took the world by storm in 2022, futurist Amy Webb predicted in 2019 that we would have access to generally available systems with artificial narrow intelligence by 2023; her prediction was only a year late. In the same book, The Big Nine, she predicted humanity would acquire broad access to artificial general intelligence and artificial super intelligence systems by 2049 and 2069, respectively.2 There are many social, economic, and technological hurdles that our society must overcome in the coming decade. We will experience immediate significant changes in our lives. We have time to adapt, but not as much as we will feel comfortable with.7 AI will be a differentiating factor and an amplifier. In other words, over the next three to five years, AI will be a disruptor.

Who uses AI today?

Harvard Business Review published research with Gartner indicating most AI initiatives fail.8 Several sources reported slow adoption of the technology into business processes.1,9 Most industries and companies, including engineering firms, automotive manufacturers, medical providers, and financial institutions, require a high-degree of fault-tolerance, precision, and judgement in their operations. Scaling and distributing engineering and business processes to meet the needs of enterprise-scale computing remains challenging. In the near-term, data analysis, content creation, and well-defined business process automation are likely the next targets of AI disruption.7

The once slow adoption of AI technology will accelerate as more pilots become successful, the technology matures, and people begin to accept and adapt to the changing environment. There will be growing pains, as is indicated by the growing mess of “work slop” being generated everyday.10 We must figure out how to incorporate emerging models and new technology into mission-critical business applications and operations. Artificial intelligence technology will serve as a cocktail composed of the trifecta of change agents. It will act as a disruptor, an amplifier, and an accelerant. We possess the power to combine this technology with the habit of continuous renewal by practicing the endless “learn, commit, do” cycle.11 In his book, Beyond Entrepreneurship, Jim Collins recommends committing to spending a minimum of 1000 creative hours over an annual 365 day period.12 We must commit to learning and adapting to our changing environments. We can thrive in this upward spiral of continuous learning, or we can let life push us around and be subjects to the actions of others.13

What do we do now?

The proverbial tectonic plates supporting the global economy are shifting. A new paradigm is emerging, like the earth’s mantle erupting, by wedging up through cracks in the crust to create new space. We are no longer living on Pangaea. Similar technological forces are causing drastic shifts in our society today. The evolution of technology is accelerating and the rate of adoption is increasing. We will experience a period of intense swift changes.6 These changes will never stop.

Our ability to learn new skills, unlearn habits, and disregard instincts will be crucial.14 Even with all the advancements of humanity, we still have difficulty predicting the weather. It is far more challenging to predict the future. Therefore, all that is left is to watch for signs of change in the wind, the tide, and plot a course forward, and hope for the best.

The sky isn’t falling. The once quiet, relatively stable ground may be shifting, the land expanding, mountains growing, and ocean tides rising. But, the sky is not falling. We still feel the cool ocean breeze in our hair, the soft sand beneath our feet, and the warm sun on our face. For this, we should be grateful; we have an incredible opportunity ahead of us. Let’s take it. As Gandalf says, “all we have to decide is what to do with the time that is given to us.” 15

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Author’s note:
I use AI for background and content research, to summarize and review articles and current events, for performing well-defined and constrained data analysis, and to automate tedious menial tasks. I do not yet trust it to think for me; and I am skeptical that I ever will. Therefore, I still do my own creative writing and composition.



Works cited

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  2. A. Webb, The Big Nine: How the Tech Titans and Their Thinking Machines Could Warp Humanity, PublicAffairs, 2019.
  3. J. Baldoni, “When the Red Phone Rings: Three Questions to Ask in a Crisis,” Harvard Business Review, Mar. 18, 2008. [Online]. Available: https://hbr.org/2008/03/when-the-red-phone-rings-three
  4. B. Brown, dare to lead, Penguin Random House, 2018.
  5. S. Giannuzzi, “Was Talos, the Bronze Automaton Who Guarded the Island of Crete in Greek Myth, an Early Example of Artificial Intelligence?”, Smithsonian magazine, Apr. 22, 2025. [Online]. Available: https://www.smithsonianmag.com/history/was-talos-the-bronze-automaton-who-guarded-the-island-of-crete-in-greek-myth-an-early-example-of-artificial-intelligence-180986467/
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  7. The Economist, “Stop panicking about AI. Start preparing”, Jan. 29, 2026. [Online]. Available: https://www.economist.com/leaders/2026/01/29/stop-panicking-about-ai-start-preparing
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  9. The Economist, “What if artificial intelligence is just a “normal” technology?.” Sept. 04, 2025. [Online]. Available: https://www.economist.com/finance-and-economics/2025/09/04/what-if-artificial-intelligence-is-just-a-normal-technology
  10. K. Niederhoffer; et. al., “AI-Generated “Workslop” Is Destroying Productivity.” Harvard Business Review, Sept. 25, 2025. [Online]. Available: https://hbr.org/2025/09/ai-generated-workslop-is-destroying-productivity
  11. S. Covey, The 7 Habits of Highly Effective People, Free Press, 1989.
  12. J. Collins, W. Lazier, Beyond Entrepreneurship, Penguin Random House, 1995.
  13. R. Kiyosaki, Rich Dad, Poor Dad, 1997.
  14. A. Grant, Think Again, Penguin Books, 2021.
  15. J.R.R. Tolken, “The Lord of the Rings: The Fellowship of the Ring,” Random House, 1954.
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  17. S. Stolzoff, “Leaders, It’s Time to Build Your Tolerance for Uncertainty,” Harvard Business Review, Jan. 13, 2026. [Online]. Available: https://hbr.org/2026/01/leaders-its-time-to-build-your-tolerance-for-uncertainty
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