The article argues that a widening “AI gap” is emerging between organizations that are able to effectively adopt and scale artificial intelligence and those that are falling behind, driven less by access to models and more by data readiness, infrastructure, and skills. While powerful AI tools are becoming more widely available, companies without clean, well governed data and modern platforms struggle to turn experimentation into real business value. The gap is also reinforced by talent shortages and organizational inertia, as teams that lack AI literacy or executive alignment move more slowly. As AI becomes embedded in everyday workflows, the article suggests that laggards risk compounding disadvantages over time, making early investment in data foundations, culture, and strategy critical to staying competitive.
