# #NextIn 2026: Artificial Intelligence

## Метаданные

- **Канал:** Zoho
- **YouTube:** https://www.youtube.com/watch?v=lBeNUfoGJz0
- **Дата:** 11.03.2026
- **Длительность:** 3:26
- **Просмотры:** 493

## Описание

AI is no longer about how big your model is. It's about how much it knows about you.
 
In Ep. 5 of #nextin, Ramprakash Ramamoorthy, our Director of AI Research, breaks down why contextual AI, a strong digital backbone, and a measured approach to where AI is applied will define enterprise success in 2026.

## Содержание

### [0:00](https://www.youtube.com/watch?v=lBeNUfoGJz0) Segment 1 (00:00 - 03:00)

There is never a dull moment in AI. Over the last couple of years, we have seen countless innovations. We have seen AI evolve to a personal assistant and nothing different over 2026 as well. We will see AI models evolve into contextual AI models. Let me explain. It's no longer about how big your model is. It's all about how much of context does it knows about you. It's all about how much of the enterprise information that is captured in your digital systems is being used by the model contextually. That becomes super important because we have seen AI evolve in the consumer scheme of things. But enterprise AI adoption we still facing issues because there is no clear path to the return on investment with respect to AI. We see that companies have realized that a strong digital backbone is super important to get returns on investment on their AI stack. Over 2026 we will see companies perfecting their system of records so that it evolves into a system of intelligence. Combine that with contextual models, you will start seeing real ROI over the next year. Also, a lot has been spoken about agentic AI in the last year. We will see agentic AI and AI being used interchangeably because today every AI is an agentic AI system. We will see that evolve in 2026. The governing laws and frameworks which have been draft laws will start materializing. They no longer be just presentations and PDFs, but they will be integrated into actual systems. Especially when you combine that with agentic systems, it's not about fancy automation anymore. It's all about how well do you offer value? use the data in your system to your advantage and also it'll be the time where companies start saying no. I see that this is a bit counterintuitive but saying no to using personally identifiable information that is PII in your models so that you get slightly better quality prediction. Saying no to using data that would hurt local compliance and privacy regulations in your AI model. saying no to the spray and prey approach of AI because this was more of a hacky tool so far where you just try and see if there is a return on investment but from now on AI will become mainstream companies have got a clear idea on where AI could help and more importantly where AI couldn't help. So in essence we will see more contextual models evolve over bigger models that can understand the entire internet. We will see companies upgrading their digital backbone so that their system of records serves right for becoming a system of intelligence. We will see companies taking a very measured approach to where they are applying AI and where they don't. In essence, it's going to be a very interesting year. There's lot more innovations coming out in AI and I see a lot and lot of enterprise adoption for AI in 2026.

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*Источник: https://ekstraktznaniy.ru/video/46050*