Reflections

  Where is AI Adoption Stuck? This is something I read on, experiment with in my job, and think about often. While cogitating, a couple of points stuck out to me in my AI updates - the state of data preparedness for AI being at an abysmal 8.4%, and the two data points on Pilot projects and their progression / status. Clearly, they confirm what I have been seeing, commenting on and writing about - that experimentation with AI is in vogue, but actual adoption lags behind by a long margin. Committing beyong the pilot is true adoption - and that clearly isnt happening. But even more worrisome is the 8.4% data point - that should have us all deeply worried - and I dont see that happening at all!        The fact that we are not ready for AI, in terms of data, can possibly hide behind it a large lacuna, which people people arent speaking too much, and which I indicated to in some of my previous writings. And that is the reality that our companies do not yet have ...

Most mobile advertising doesn’t fail because it’s on a phone. It fails because it interrupts. Most mobile advertising is fundamentally broken because it forgets a basic law: advertising should never be intrusive. An ad that blends into what I’m already doing gets a hearing; an ad that blocks what I came to do gets closed, as fast as my thumb allows. Over the past few months, my own phone has been the experiment: Instagram introduced me to products I ended up trying, while a mobile game made me resent a brand I’d otherwise have clicked. Same screen, same person, very different result. When you analyze how new customer acquisition and brand building work across digital ecosystems, the contrast between Instagram and traditional mobile ads couldn't be clearer - and gives us a direction in which to move.      1. Why Instagram Works: Speed, Simplicity, and Seamless Context ...

  Part 2 of Show Me the Market | By Vishal | October 2026 In my previous piece, I argued that AI cannot pay for itself at current pricing tiers. Roughly $3 trillion of debt and obligations sits behind the industry, and a subscription-based market, modelled generously, comes to tens of billions to low hundreds of billions of dollars a year. The gap is too large to close with seats at $20 a month. Neither is the expectation that each individual can sustain multiple 20$ subscriptions – that leaves the B2B revenue stream. That, while looking attractive, is, on deeper analysis, not quite as compelling a case for AI sustenance. The B2B industry operates on a concept of share of profits or percentage of revenue or a similar metric when it comes to technology spends – and they have to spread it across multiple solutions, with being but a share of it. Clearly something has to give – either the models have to change, or the market has to crash – or even both. Current approaches are sim...