Sumit Bajaj

It is hard to understand Fabric's long-term strategy. On one hand, it was smart to build it around PBI, the leading BI platform. On the other hand, the key to Power BI's success in dethroning Tableau was its' extremely affordable licensing. Competitive licensing is not an element that Fabric's always-on pricing model can boast of at current rates, especially when the likes of Databricks, Snowflake, and other rising platforms are around. Perhaps Microsoft will be content with Fabric always being the 3rd/4th best option?

39

32 Comments

I’ve seen firsthand how Global Capability Centers (GCCs) are becoming the engines of AI-powered retail innovation. From optimizing inventory with predictive analytics to delivering hyper-personalized customer journeys—GCCs are no longer just support hubs; they’re strategic growth drivers. In the latest episode of the InOrg Insights Podcast, I join InOrg’s VP of Delivery, Anurag K. Goswami in a discussion on how leading retailers are leveraging GCCs to stay competitive and future-ready in an AI-driven world. If you’re in retail, AI, or GCC strategy, this one’s for you.  Listen here: https://lnkd.in/g-vHEU98 #RetailInnovation #GlobalCapabilityCenters #AIinRetail #GCCStrategy #FutureofRetail #InOrgInsightPodcast #retail #gcc Nicole de Mocskonyi

70

2 Comments

Pleased to share my latest article with ET CIO: “AI-Ready Culture: Machine Speed, Human Ingenuity” 🔗 https://lnkd.in/gAhpKFiV In today’s enterprise landscape, building an AI-first culture isn’t just about deploying models—it's about aligning mindsets, workflows, and leadership principles to truly unlock value. In this piece, I dive into: #1. Why AI adoption is stalling at the culture layer—not the tech stack #2. The need for cross-functional fluency to operationalize AI #3. How we can balance experimentation with accountability #4. And why trust, explainability, and agility must sit at the core of any AI-ready organization Thank you to the ET CIO editorial team for the opportunity and platform to share my views. #AI #AILeadership #EnterpriseAI #DigitalTransformation #AIReady #DatatoValue

69

One nice upside to handling people who are always sure of themselves is how effortless it becomes to tune out their confidence. Certainty is a signal. Those who wield it boldly are given the benefit of the doubt in the short term… but are given just the doubt in the long term. The “high confidence and certain” strategy stumbles in long-term collaborations as you develop “swagger antibodies.” However, I’ve noticed top-tier leaders have evolved over the past 20 years. They blend uncertainty with strong decisiveness in a compelling and natural way. I am far more willing to “disagree and commit” if the response is: “You make a fair point and this might not work out as we hope. Still, we believe the benefits outweigh the risks here, and we’ll do what we can to mitigate and adapt given your points.” It’s less grudge match and more team huddle. This concept dovetails neatly with the principle “long-term optimist, but short-term pessimist.” The short-term uncertainty and risk is recognized, but the decisive long-term optimism is never lost. This type is not blind to the potholes littering the road, but they’ve got this unshakable faith that the destination’s worth the trek. It feels a bit more gritty and real, yet somehow more inspiring. My takeaways from seeing this in action: Believe in destinations worthy of pursuit. Communicate that vision. Become hyper aware and semi-comfortable with short-term uncertainties. Be decisive, even with inaction.

34

5 Comments

Everyone is talking about AI agents. But Walmart isn’t just talking → they’re building. (This is how legacy giants evolve to stay ahead) Agentic AI is more than a buzzword. It’s becoming core to how companies operate — from search and shopping to support and supply chain. Take this line from Walmart’s latest reveal: “Walmart is developing purpose-built agentic AI tools tailored to retail-specific tasks, using its own data and LLMs to drive real business impact across customer experience and operations.” Translation? They're not waiting around for anyone. They’re training agents on their own data. They’re optimizing for retail-specific outcomes. They’re preparing for a world of machine-led shopping. From customer discovery → to agent training → to marketing infrastructure... Walmart is designing for a frictionless, fully AI-integrated future. Agentic isn’t coming. It’s already here. Full article 👇 https://lnkd.in/d56Wv_5i #agenticAI #retail

16

2 Comments

Last month, Amazon launched Q Suite — an AI assistant. One of the features is that it can connect across multiple sources - email, docs, share point and calendars.  I tried it on one of my large cross-functional initiatives — with multiple teams, documents, and ongoing discussions. I simply asked: “Summarize all project updates, upcoming meetings, and key decisions from the last month.” And within seconds, it pulled everything together — - Read through all my emails on that topic and documents and gave a summary of what happened across these channels - The upcoming meetings on this topic from my calendar - A list of key decisions and owners from past discussions But here’s what I realized — The output quality depends on the input hygiene. So I made three changes: 1. Label emails correctly - in outlook you can add "categories" to label. 2. Folder discipline - one dedicated folder for each project. 3. Consistent naming - Put file names properly with the project or initiative name.

173

8 Comments

15 years back, when we were building voice bots for the US market - one of the key debates used to be whether to declare or not to declare its a bot. Even if not explicitly say things like "I can help you with X,Y, Z queries and you can say things like .... " indicating a limited understanding. Even if the users did not understand what a virtual assistant is - they understood this is not a human being speaking on the other side. European regulations strictly mandate the voice agents to declare before proceeding in a conversation. India is an upcoming market but getting into the space at different stage of maturity of conversational engines - Hence there is a lot of asks to cover up the underlying bot and not by any means show up its a machine. The experience should be "human like" but that does not mean we should hide the machine behind. For an end consumer, its important to know the species they are speaking to and I now see why some of the western paradigms firmly support the declarative approach. Its just more human.

100

3 Comments

Last week I attended an insightful talk by Uber Principal engineer Amrut Joshi at NASSCOM Future Forge conference. Here are the highlights - LLMs are the thinkers — they understand, reason, and plan. Tools are the doers — they fetch data, trigger actions, and run computations. Agents connect the two, orchestrating workflows from user request to final output. Best practices in tool engineering: Modular – one clear task, reusable in different contexts Predictable – consistent formats and outputs Specific – easy for the LLM to choose correctly LLM-friendly – clear descriptions, simple inputs, human-readable error messages Secure – authenticated, authorized, and auditable Why it matters: Without great tools, even the smartest LLM can’t reliably act in the real world. Tool Engineering is as critical as Prompt Engineering in building capable, trustworthy AI agents. #AI #LLM #ToolEngineering #AIagents #PromptEngineering

64

1 Comment