Reflections

  In the midst of today's atmosphere when everyone is gung-ho about AI, few if any are speaking of the specifics of AI adoption and implementation inside companies. AI is not a magic wand—it needs to be fit into the organisation, its processes, and made a part of the life of the people who populate the organisation. It won't get its due just by hyperbole and constant focus on the promises of AI. Someone, and a lot of someones, has to get down to the hardcore practicalities of using it. Individual AI usage ≠ organisational AI implementation. A company can buy an excellent AI tool and still fail because it doesn't know how to integrate it into actual workflows.       People don't resist AI merely because they fear AI. They resist disruption to functioning processes. And therefore: the first implementation objective should not be transformation. It should be integration. That creates a two-stage implementation model: Stage 1: Fit AI into the existing process. S...

Two Words That Stopped Me I recently came across two Marathi advertisements that used the words "हैराण" and "झिजणे". Both stopped me — not because they were grammatically wrong, but because neither sounded like the Marathi an ordinary Marathi consumer would naturally speak.        That is where my mind turned to autotranslation and technology. It is the age of technology even in advertising, and it has known benefits — there is no argument to that. But the same technology is also creating shocks in the system, as well as giving rise to problems. The bigger issue is that the industry seems to be blissfully unaware of the downrange as well as the immediate challenges being raised by the entry of technology into this field — a domain that was, hitherto, purely creative-based, human-based.   The Real Danger ...

The rising usage of AI in Creativity is a perfect stand-in for what is in my opinion the biggest risk facing Industry and Business today: the acceptance of substandard solutions, and the concomitant rise in mediocrity along with the loss of domain expertise. This is readily apparent in the content space on any social media nowadays with the advent of AI written posts filling our feed. Now, apparently you don’t need real skill to write a post – this is worrying. While AI is a great equaliser, unplanned-   it can be a greater destroyer of skills.        This is not an article about creativity and usage of AI – rather, it uses this field due to the author’s profession of being in Advertising as well as in AI Software companies as a Fractional CMO to raise a fundamental issue relating to this industry – the rising acceptance of the mediocre. AI in the field of creativity needs a dedicated treatment – but here, I analyse mediocrity through the lens of AI usage ...

  What makes innovation and new technologies like artificial intelligence commercially scalable? — the answer is deceptively simple yet diabolically hard: someone has to create the market, educate buyers, establish use cases and reduce adoption friction. Innovation does not automatically create a market. There is a missing middle between building the product and having customers willing and able to buy it. That is precisely where marketing, industry development and senior leadership come in.   People oftentimes make the error of placing the innovation engine all by itself - that results in sunk costs with no commercially viable enterprise; this is one of the reasons why startups fail so often. They forget - any product or service has to have an addressable market, and a total market. Not just a market - but an addressable market, one that can interest and desire, has a willingness to pay etc etc. And in innovative or new product lines, often these are missing; and this d...

  One of the key roadblocks to wider AI adoption especially in India is, apart from an understanding of the specific benefits in real-world detail, the lack of understanding of the risk associated with them. In customer conversations, this is an element that is now beginning to crop up more and more – alongside deep, workflow-specific questions. Sadly, most AI companies do not do a good job on either front – addressing specific workflows, or specific risks. This is where hype around risks can emerge.        For example, AI Agents in particular, and AI in general, going rogue is a nightmare scenario that I am sure many of us have heard of. However, the real problem with AI is not simply whether an AI can go rogue. It is whether organisations have any practical framework for quantifying the risk of autonomous exec...