The conversation around artificial intelligence has swiftly moved from chatbot experimenting to generative use cases, and now embedding the technology into enterprises for customer interactions, and enhancing business decisions.Obviously, AI investments are getting heavier for the enterprises and they are seeking ways to maximise the Return on Investment (ROI). Success, though, depends on scaling personalised experiences, consolidating trusted data, and automating decision making-in no particular order.ADA, a company that positions itself as a ‘Data and AI-Experience’ platform, has recognised and understood the shift and has made it a part of their global strategy. The company has built an integrated stack that is built to scale outcomes, and engineer business growth-for all of their 1500 enterprise clients, across the 34 global markets they cater.ADA’s clientele spans industries including Retail; Consumer Packaged Goods; Banking, Financial Services and Insurance; Healthcare, Telecommunications, and others.The Product You See Isn’t the Product I See | How AI is Personalizing Retail Experiences | Srinivas Gattamneni, CEO, ADAEvery time you click “buy,” AI has already decided what you see, what you pay, and why you’re seeing it. And it’s different for everyone in the room. In this candid conversation, ADA CEO Srinivas Gattamneni pulls back the curtain on the data and AI engine powering pricing, personalization, and purchase decisions for 1,500 global enterprises. With over 20 years of customer data, 250 million customer profiles managed and over 150 proprietary models, ADA’s AI and Data experiences allow brands to increase revenue per visit by up to 46%. In this conversation, Srinivas breaks down India's role as ADA's "lighthouse market" for global innovation, the company's outcome-based model where they only get paid when clients make money, and his candid take on whether we'll trust AI more or less a decade from now. . #AI #Retail #DataAI #Ecommerce #ArtificialIntelligence #Personalization #StartupInterview #ADA #TechLeadership #FutureOfCommerceGlobally, companies have done the same, with heavy investments in their AI integration projects. Not everyone has succeeded in driving business growth, however. The difference, ADA says, is “trust” which is at the heart of scaling AI and getting meaningful outcomes.How important is trust? Many enterprises that have invested in AI in the past couple of years have not figured out how to consolidate fragmented data, and disconnected systems.Not for ADA. The company has its Data and AI Experience stack woven around four major pillars-including Trust, Intelligence, Personalisation, and Scale. The philosophy that connects these four pillars is what is driving the growth for ADA.The company maintains: lack of trust means lack of reliable data; lack of reliable data translates into lesser intelligence; and without the intelligence (AI) personalisation cannot scale. This philosophy at ADA, and many other enterprises globally, implies that AI cannot be used/looked at in isolation. AI has to be a pan-enterprise capability.Moreover, this enterprise wide integration has to be done to attain autonomous execution wherein the AI systems are capable of making independent decisions to optimise operations and minimise human intervention. Is that achievable?The next frontier: The need right now isn't for agents that simply converse or take commands, it's for agents that can pull trillions of scattered data points into a single customer view, then act on it at every touchpoint.ADA has stretched its portfolio exactly in sync with what the future needs. Data flows in from every domain: consumer, product, supply chain, commerce, into one customer profile, and AI agents take it from there: fraud detection, demand forecasting, revenue optimisation, customer sentiment analysis, inventory planning, and more, automating workflows and personalising every touchpoint along the way.Personalisation, a growth enabler: The capabilities ADA has added into its AI armory, has indeed a significant impact in pushing forth the company’s growth, and the growth of its clientele.As ADA, and other companies deploying AI on similar lines, make progress, one of the pivotal growth impetus has been personalisation. To put it in simple terms, personalisation at an enterprise level translates into understanding the customer.With the rise and rise of e-commerce, quick commerce, and online transactions the generic customer experiences have become “run of the mill”, and are fast losing their appeal and effectiveness.What AI has allowed enterprises, including ADA, to do is understand the customer better, decipher their intent in real time, and deliver tailored solutions. ADA, through its personalisation engine, has added predictive analytics, customer intelligence, AI-powered recommendations, content orchestration, promotions that are dynamic, and increasingly personalised customer experiences.The company maintains that integrating these capabilities have the potential to push revenue up by around 40%. Besides, the intelligence can also be used for demand forecasting, pricing models, promotional orchestration, and the most significant AI-generated content.The commerce content ADA’s AI-powered creative stack produces can reduce content production lead times by around 70%, and lower livestream production costs by 56%. The AI stack by ADA uses product information to create AI videos, avatars, and more for promotion, in minutes, without increasing the content cost.The takeaway: ADA is shaping the future, through 34 markets globally and with more than 1500 customers across sectors. The most significant takeaway from their strategies, which we have spoken about at length in this article, is the assertion that enterprise AI has ceased to be about individual tools.The way AI is evolving, and changing the workplaces along the way, integrated platforms are needed to drive growth.Trusted data infrastructure remains at the core of the whole process, and the message for enterprises reads: simple access to AI will not be enough, connecting trusted data to decision-making, personalising customer interactions, automating business operations, and building trust into every digital experience.