Today organizations are accelerating their AI ambitions, and the biggest opportunity to become truly AI-ready may already exist within ongoing/planned ERP or CRM transformation programs. Rather than treating data migration as a simple lift-and-shift exercise, enterprises can use these initiatives to assess, cleanse, standardize, enrich, and govern their data before moving it into new systems.

AI is only as effective as the quality, context, and trustworthiness of the data it relies on. And migrating duplicate customers, fragmented supplier records, inconsistent product definitions, and outdated business rules into a modern platform simply transfers old problems into a new environment.

By combining business knowledge, governance, human validation, and AI-driven intelligence, organizations can transform migration projects into strategic data transformation programs that create trusted enterprise data foundations. The goal is not to move all data, but to move the right data, in the right condition, with the right context. When done well, ERP and CRM transformations become catalysts for better analytics, more reliable AI copilots and agents, stronger automation, and greater business value. Before asking how to make AI relevant, organizations should first ask a simpler and more important question: How good is our data, and what can we do today to make it more valuable for tomorrow?

Read more: Before you become AI-Ready, become Data-Ready

A recent study by UiPath has shown that 93% of US IT executives are “extremely or very interested” in applying agentic AI to their business, with 45% ready to invest this year. This growing interest shows a huge shift in the world of artificial intelligence, moving beyond the capabilities of current AI systems, such as ChatGPT, which primarily focus on generating content in response to specific prompts. Instead, we are entering the age often referred to as “The Third Wave of AI” i.e. agentic AI, the next generation of AI that can operate more autonomously, making decisions and taking actions with minimal human intervention. This shift has the possibility to overturn various industries and aspects of our daily lives.

Read more: Agentic AI – When machines act, not just react

Is India’s AI revolution leaving its own people behind? We’re building AI for the world, but is India benefiting from its own AI advancements?

Is AI in India empowering or excluding? Who is really benefiting from our AI boom? If AI is the future, why is it still so inaccessible for most Indians?

I know, all these questions might sound very negative, but I really wanted to ask questions precisely, so that we can evaluate better answers for us, us I mean, 𝙪𝙨 𝙩𝙝𝙚 𝙄𝙣𝙙𝙞𝙖𝙣𝙨.

→ On one side, Indian startups like Uniphore, Fractal Marketing & Analytics, and Innovaccer are making global waves.

→ The Government of India is actively pushing AI initiatives, projects like BHASHINI to tackle language barriers and the IndiaAI Mission to build a national AI ecosystem.

But there is another side of the story that we all shy to speak about:

AI in India is booming as a service provider to the world, but, within the country, its benefits aren’t reaching to its own millions of people.

Why?

Read more: Is India actually AI ready? Do we have AI for Bharat?

Cricket has always been about gut feeling, experience, and figuring things out after the game. But now, artificial intelligence (AI) and generative AI (GenAI) are changing the way we receive the real-time updates, i.e. right where it’s happening.

Picture this: a fast bowler charging in, the batsman getting ready, and up in the commentary box, an AI’s already guessing where the ball’s gonna go, checking past data, and changing the odds of winning, all before the ball’s even left the bowler’s hand! And yes, this is not some sci-fi talk, it’s what has started happening already.

AI is constantly reading player biomechanics, identifying fatigue before injuries occur, and even suggesting optimal field placements based on a batsman’s weaknesses.

And when you think further, even broadcasters are leveraging AI based storytelling, which helps them to personalize highlights based on fan preferences, and even translating commentary into multiple languages in real time. At the same time, social media AI engines are tracking sentiment shifts with every six, wicket, and turning point, giving a real-time pulse on fan reactions across the globe.

So the point is that, AI is saving thousands of research hours that once went into manual video analysis, performance tracking, and match reviews. The result? Faster insights, sharper strategies, and an enhanced viewing experience like we have never seen before.

In this newsletter we will explore the same.

Read more: AI playing a big role in ICC (Cricket) Champions Trophy 🏆

OpenAI ChatGPT and DeepSeek AI is not only learning chatbots, they’re full-fledged AI assistants that can write, code, problem-solve, and even weigh in on ethical questions. I have been working with them side-by-side since past one month and my findings stunned me in more ways than I can explain. So, drafting my learnings so far with the intent that it might help you to decide which one is the right choice for yourself.

Let’s break it down:

👉 ChatGPT (OpenAI): It is known for its smooth, natural conversations, creativity, and adaptability. I believe, its a go-to for content creation, brainstorming, and engaging dialogues.

👉 DeepSeek: Cool and budget-friendly option that leans on logic, technical accuracy, and efficiency. It is more focused on getting precise answers than creative storytelling.

But here are the parameters I evaluated them on:

🔹 Performance: Which one responds faster and with more reliability?

🔹 Cost vs. Value: Is DeepSeek’s lower price worth it?

🔹 Coding & Content: Who does better at complex programming and writing tasks?

🔹 Ethics & AI Safety: How do they handle biases and responsible AI use?

Artificial Intelligence (AI) was initially confused with RPA (Robotic Process Automation), which focused on automating repetitive tasks. RPA was essentially rule-based, handling processes like data entry, invoice processing, or customer service inquiries. It wasn’t “smart” in the way AI is today—it followed strict, predefined commands.

Back in 2000s, RPA was the closest thing to AI that many companies were implementing. It made work faster but didn’t involve any decision-making or learning. Think about early chatbots or even Microsoft Clippy Assistant. These tools could execute commands but couldn’t “learn” from their interactions.

The global AI market was already worth more than US$150 billion by the end of 2023. According to one of the reports, the global AI market will reach US$1350 billion by 2030, and this upward journey surely begins from 2024. The idea of this icon 👽 might have set the tone of my predictions for this year. Trust me, we are going to witness unimaginable AI implementations in 2024. The breakthroughs of Generative AI in 2023 has setup a dramatic momentum for 2024, and our expectations have risen to a next level. Everyone is waiting for the “Aliens” to appear this year, I mean not literally, but I guess you understand the sentiments.

Before I start, there are pretty obvious things which are going to happen in 2024, like OpenAI‘s GPT-5 will be launched, Generative AI will become a technology risking most jobs by any tech-disruption, and on contrary setting up stage for people with plethora of opportunity in new job-roles — like prompting efficiently. And the start of the year will face a dramatic AI startup-stress because of the business models that are too much affected by OpenAI’s release of add-ons.

“It has become appallingly obvious that our technology has exceeded our humanity” — Albert Einstein

I am very optimistic about this year, but at the same time I am cognizant of the fact that this year is also going to daunt us a lot. And its because we haven’t yet lifted ourselves to the maturity which this technology demands, and I am specifically concerned with the pace of Generative AI’s access to common people in its raw form. So to start with, the table of contents below should clear how I am picturing this for the year 2024.

Its amazing to see how AI adoption happened in the year 2023. With all the Generative AI use cases and new products, last year felt like evolving at an unprecedented speed. Reading through all the stories and posts by AI Influencers, Entrepreneurs, Domain Experts, and literally “Common People“, was so overwhelming. I would call the year 2023, an year of defining the new AI tech-disruption of this decade…