The AI Paradox

If the rush to adopt artificial intelligence (AI) seems familiar, it’s because we’ve seen this movie before. In the late nineties, organizations of all sizes, but especially large or enterprise-level businesses, struggled to make the transition from legacy functionality to digital transformation. As late as the COVID-19 pandemic and global lockdown in 2020, enterprise organizations were rushing to complete their digital transitions, particularly when it came to enabling and protecting widely distributed remote workers with home office operations, workflows, and compliance regulations.

What’s more, an AI arms race is well underway, as Microsoft, Apple, and other tech firms invest billions into AI products such as OpenAI. Everyone knows full well, or should, just how intense the race to dominate AI is at the global and corporate levels. It’s that transformative.

AI Altering Business Practices

There’s no question that AI is the next technological advancement that will fundamentally alter our way of life in the very near future, and perhaps for evermore. In fact, it already is and continues to do so. But in these early and heady AI days, there are practicality speed bumps, too.

For example, corporate executives and boards are encountering implementation and control roadblocks that are preventing their organizations from realizing more than just a fraction of AI potential, not to mention justifying the millions of dollars in spending that an enterprise-level AI deployment costs in streamlining their operations, optimizing workflow, harmonizing siloed divisions, and other organizational challenges that enterprise-level organizations struggle to handle well.