Amit Rawal

Chief AI Officer |  Apple AI Leader | Stanford | AI Professor | Keynote Speaker | AI Strategy Advisor to Leaders & C-Suite | Building an AI-powered Life OS to help you find meaning, clarity & connection

Disclaimer: Opinions expressed here are my own in a personal capacity and do not represent the views, policies, or positions of my employer (currently Google Inc) or its subsidiaries or affiliates.

Driving AI-led business transformation across Google’s Platforms, Devices & Services. My mission is to inspire, educate and empower 100 million founders and individuals to live an AI-powered life.

I help founders, entrepreneurs and young tech professionals to use AI in their daily life. I also teach AI to leaders, helping them apply it for storytelling, strategic decision-making, and data analysis.

Head of Product: Digital 360 - Global Analytics & Insights

Part of the Global Digital Center of Excellence. Lead a global team of product managers, engineers, analysts, and program managers responsible for the analytics platform enabling Apple’s global Digital Channel Sales.  

- Scoped, designed, and implemented E2E Data and Analytics strategy enabling 360 performance measurement on the world’s largest retail platforms such as Amazon, Walmart, JD, Best Buy, etc.

Google just gave AI a whole new playground.

The Google AI Ecosystem is bigger than most people realize
and if you’re not using these tools, you’re leaving serious productivity on the table.

Here’s what’s inside the wheel:

🛠 Developers

∙ Gemini – Google’s flagship AI model
∙ AI Studio – build and test AI apps fast
∙ Gemma – open-source models for developers
∙ Code – AI-powered coding assistant

☁️ Cloud Systems

∙ Google Cloud – scalable AI infrastructure
∙ Firebase – build and deploy apps with ease
∙ TensorFlow – open-source ML framework
∙ BigQuery – analyze massive datasets instantly

📊 Data & Analytics

∙ Looker Studio – turn data into visual reports
∙ Google Sheets (AI-enhanced) – smarter spreadsheets
∙ Firebase Analytics – track user behavior in real time

🔍 Browser & Research

∙ Chrome – now with built-in AI features
∙ NotebookLM – AI that reads YOUR documents
∙ Gemini in Search – answers before you even click

📝 Productivity

∙ Gmail, Docs, Slides, Sheets, Calendar, Meet – all with Gemini built in

🎨 Creativity

∙ Veo 3 – AI video generation
∙ Lyria – AI music creation
∙ Google Photos – smart editing and search

This isn’t just a tech stack. 
It’s an entire AI-powered operating system for work, creativity, and building.


🔁 Save this. Share it with your team. Start with one tool today.

Which one are YOU already using? Drop it below 👇​​​​​​​​​​​​​​​​


Follow for more AI drops!

___________________________________________

👋 I’m Amit Rawal, an AI practitioner and educator. Outside of work, I’m building SuperchargeLife.ai , a global movement to make AI education accessible and human-centered.

♻️ Repost if you believe AI isn’t about replacing us…
It’s about retraining us to think better.

Opinions expressed are my own in a personal capacity and do not represent the views, policies, or positions of my employer (currently Google LLC) or its subsidiaries or affiliates.

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Choosing the LLM is the easy part.

AI agents are 95% plumbing, not prompts.

Most teams obsess over the 5%:
• Which LLM?
• Bigger context window?
• Token cost?
• Benchmarks?

But that’s not where agents fail.

The real work is the other 7 steps:
workflows, routing, memory, tools, retries, logging, evaluation.

You’re not “prompting a model.”
You’re engineering a system.

Because the hardest part is orchestration:

Knowing when to stop, retry, ask for help, or escalate.

Without infrastructure (tools + memory + testing),
you don’t have an AI agent.

You have a chatbot that hallucinates with confidence.

Stop chasing intelligence. Build the glue.

And when the SOTA model updates?

Your agent shouldn’t break.
Your system should adapt.

Which part of the agent pipeline breaks for you most? 👇
(Orchestration, tools, memory, evals, monitoring?)

___________________________________________

👋 I’m Amit Rawal, an AI practitioner and educator. Outside of work, I’m building SuperchargeLife.ai , a global movement to make AI education accessible and human-centered.

♻️ Repost if you believe AI isn’t about replacing us…
It’s about retraining us to think better.

Opinions expressed are my own in a personal capacity and do not represent the views, policies, or positions of my employer (currently Google LLC) or its subsidiaries or affiliates.

Google AI Transformation Leader | Former Apple | Stanford | AI Educator & Keynote Speaker

Most people call everything “Agentic AI”… but it’s not.

Stop calling everything AI. 

LLM chatbots simply respond to prompts.
RPA follows fixed scripts and rules.
RAG retrieves data and helps the LLM answer better.

Useful? Yes.
But none of these can plan, decide, and act.

A real AI Agent has an orchestrator that manages:

• planning + reasoning
• memory
• tool usage (APIs, CRM, email, deployments)
• feedback loops + retries
• multi-agent coordination

That’s what makes it agentic: it can break a goal into tasks, choose the right tools, and complete work end-to-end.

Question: Which part of agent building is hardest for you? 👇


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___________________________________________

👋 I’m Amit Rawal, an AI practitioner and educator. Outside of work, I’m building SuperchargeLife.ai , a global movement to make AI education accessible and human-centered.

♻️ Repost if you believe AI isn’t about replacing us…
It’s about retraining us to think better.

Opinions expressed are my own in a personal capacity and do not represent the views, policies, or positions of my employer (currently Google LLC) or its subsidiaries or affiliates.

New research from Google DeepMind just dropped, and it’s honestly one of the clearest signals of what’s coming next in AI.

It’s called “Intelligent AI Delegation.”

The core idea is simple:

Future AI agents won’t just help you.

They’ll delegate tasks to other agents and humans, manage workflows, assign roles, monitor execution, handle failures, and still deliver results.

But here’s the real problem…

Right now, most agent systems use basic heuristics.
They’re brittle, unpredictable, and break when things go wrong.

DeepMind proposes a framework that includes:

•	clear roles + boundaries
•	authority + responsibility transfer
•	accountability for outcomes
•	trust + reputation mechanisms
•	performance monitoring
•	failure recovery

Because as agents enter delegation networks and even virtual economies, we can’t afford “random automation.”

We need structured delegation protocols.
This is basically the foundation of the agentic web.

Paper 👉🏻: https://lnkd.in/gpafnRyi

If you’re building with AI agents, this isn’t optional reading.
It’s the blueprint.

Question: Do you think AI agents should have accountability like humans?


🔁 Repost if this helped.
➕ Follow me for more AI agent breakdowns. 

___________________________________________

👋 I’m Amit Rawal, an AI practitioner and educator. Outside of work, I’m building SuperchargeLife.ai , a global movement to make AI education accessible and human-centered.

♻️ Repost if you believe AI isn’t about replacing us…
It’s about retraining us to think better.

Opinions expressed are my own in a personal capacity and do not represent the views, policies, or positions of my employer (currently Google LLC) or its subsidiaries or affiliates.

CGR Ventures

Innovation Consultancy for digital transformation and growth working with top global financial services clients including BBVA, Citi, & Standard Chartered Bank. 

Developed, designed and executed open innovation programs working with the fintech ecosystem (venture capital, best-in-class entrepreneurs, top accelerators, and universities) culminating in over 50 Proof of Concepts, Pilots and Commercialization across key financial services focus areas. 

Select companies with deep involvement include Pindrop Securities, Riskified, Forter, Sift, Signifyd, Clinc, Wise (formerly Transferwise), Marqeta, Ayasdi.

Founder & President

Bank of the West

Led open innovation to accelerate digital transformation and growth.

Head Open Innovation

Vantiv

Led emerging products team to develop and commercialize new products and capabilities for Vantiv's customers. Product lead for Vantiv's developer platform.

Vice President Emerging Products and Technologies

Citi Ventures

Leading a variety of incubation and venture investing efforts at the intersection of next generation technology and financial services for Citi’s Global Corporate Venture arm

Partnering with startups and leading firms in areas such as natural language processing, data analytics, customer authentication to build new capabilities inside Citi

Venture Leader

VogueMagnet.com

Pioneered and launched the luxury retail ecommerce experience in India.  Built product, raised capital, and forged strategic alliances with American Express and Ruelala.

Founder & CEO

Citi

Worked directly with the CEO to restructure Citi’s Personal Wealth Management business as a fee-based advisory model

Head of Strategy (SVP) – Citi Personal Wealth Management

Managed complex and high-visibility projects working directly with the Chief Administrative Officer on cross enterprise efforts such as the annual shareholders meeting, public affairs and policy, and government relations
   
Led a global, cross-functional, cross-business team to devise and implement a strategy to de-risk Citi’s Embassy Banking business faced with significant compliance challenges

Senior Vice President – Chief Administrative Office Consumer Banking North America

Selected into Citi's fast track leadership development program designed to groom the next generation senior managers

Experienced in wide variety of businesses and roles including corporate and consumer banking, risk management, finance, marketing, strategy and M&A

Global Management Associate

CitiFinancial International

Focused on managing the global marketing effort of the international consumer finance operations across 22 countries

Marketing Associate

Brother Computers & Software (I) Ltd.

Senior Manager

Brown Brothers Harriman and Co.

Regional Quality Control Analyst

State Street

Analyst

Focus on innovation and commercial development of next generation financial services products. Domain expertise spans:

 -  Payments & Commerce 
 -  Wealth Management  
 -  Lending 
 -  Risk & Fraud management
 -  Data Analytics

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