Deep AI Verticalization: No Silver Bullets
AI may seem to work wonders under the right conditions, but it is far from a fix for all problems.
Around since the 1950s, artificial intelligence has taken on a new valence over the past decade. In both reality and rhetoric, AI has emerged as a leading subject in business technology discussions and is viewed by many as both a silver bullet and an existential risk to business organizations and society as a whole. Whatever side of the AI debate you are on, no amount of analysis and scrutiny is too much. The worst thing that can emerge from this critical focus is better products, services, and processes. Either way, technology and business leadership must come together to let AI yield the sorts of outcomes that justify the investments made.
The jury is still out regarding the application of AI to business. While there have been profound advances, there have also been a host of false promises and hyperbolic predictions that never materialized. As one particularly famous investor put it, "You promised us flying cars, but you gave us 140 characters."
Indeed, the distinction between “real” and “rhetorical” AI has become a sine qua non of success not only in Silicon Valley but in all of industry. Mere claims can get a company funded- perhaps but cannot deliver real value. Ask any CIO about the historical divergence between promise and reality in technology and you’ll see that it’s no different with AI.