Understanding AI Hype: The DIY Approach

During a recent presentation at the University of Wisconsin-Madison, I urged students to broaden their perception of artificial intelligence beyond conventional uses such as homework or social media applications. This discussion began with a provocative inquiry: ‘Can AI’s impact be both over-hyped and under-hyped simultaneously.’

My answer is a resounding yes, and it hinges on the pivotal notion that our understanding of AI is largely influenced by our willingness and opportunity to engage in do-it-yourself (DIY) training and experimentation.

The Critical Need for Experimentation

Experimentation with emerging technologies is crucial, especially when it comes to AI. Reflecting on my own engagement with AI, I realized that there was ample room for expanding my commitment to DIY experimentation.

By actively experimenting, individuals can alter their mindset and navigate through the ‘trough of disillusionment’ often associated with over-hyped technologies. This approach doesn’t just foster personal growth, but also translates into better service for customers.

Remembering the Moment of Realization

Over the last two years, the rapid evolution of AI has left many, including myself, with a sense of disorientation. I experienced a fortunate convergence when I took a sabbatical just as ChatGPT was launched. This unexpected break allowed me the time needed for self-guided exploration of AI.

While coworkers in corporate roles often lacked the time to engage with new technologies and disregarded AI as over-hyped, my informal experiments proved otherwise.

Navigating the DIY Chasm

The importance of dedicating time for DIY work cannot be overstated. This creative process not only helps in grasping the technology but also leads to authentic insights that foster productivity. I devised my own hype cycle representation to illustrate this journey.

Benefits of AI Engagement

Fast forward two years, and while my commitments in teaching and consulting have limited some DIY experimentation, every engagement still results in eye-opening ‘wow’ moments.

By staying connected to thought leaders in AI, I am reminded that the current version of AI tools represents the ‘worst AI’ we will ever use, a motivational concept for ongoing exploration.

Personalized AI Content Creation

More recently, I examined the MarTech for 2025 report, which emphasizes personalizing content through AI. Certain approaches, such as utilizing AI-generated voice tools for reading articles, have transformed how I ingest information.

Additionally, Google’s NotebookLM has demonstrated powerful utility by converting material into audio formats, enhancing the accessibility and engagement level in learning.

Conclusion: A Roadmap to Personalization

This exploration underscores a broader trend: the integration of evolving technologies in daily operations. As organizations aim to scale these DIY approaches, prioritizing customer requirement remains paramount.