Artificial intelligence (AI) is now growing rapidly and started helping several business. In India, the firm increase home sales conversion rates by as much as 20 percent as developers lean into technology to streamline customer experiences, optimise pricing and speed up decision-making.

AI helps developers lift home sales

“From our conversations with sector experts, the most immediate impact of AI is visible in sales, marketing and pricing strategies,” said Shekhar Patel, president of the Confederation of Real Estate Developers’ Associations of India (CREDAI). “AI-powered chatbots, virtual site walkthroughs and predictive customer analytics are helping developers personalise offerings and improve conversion rates by up to 20 percent.”

Developers are using AI across the board—from customer-facing platforms to backend operations—to refine every aspect of the value chain.

Tata Realty and Infrastructure has implemented AI tools like Salesforce Marketing Cloud and Einstein AI to enhance homebuyer engagement and reduce friction across digital touchpoints. These tools have allowed the company to personalise interactions and optimise lead qualification in real time.

“Since implementing AI-led tools, we have achieved a 20 percent reduction in CPQL (cost per qualified lead), and booking conversions rate have grown by 10 percent year-on-year,” said Sanjay Dutt, MD and CEO of Tata Realty. “The improvements stem from sharper targeting, real-time campaign optimisation and improved homebuyer interactions.”

In 2025 there were several AI tools launched and most apps try to replace human tasks entirely. But Granola in this case performed the best option and took a different approach—and Silicon Valley noticed big time. This simple AI note-taking app has raised over $60 million in funding and caught the attention of major tech companies, proving that sometimes the best AI doesn’t replace humans but makes them better.

The Problem That Started It All

Anyone who’s ever sat through back-to-back meetings knows the struggle. You’re trying to pay attention, participate meaningfully, and capture important details all at once. Traditional note-taking apps make you choose between being present or being thorough. Voice recorders create hours of audio nobody wants to review. Meeting bots feel awkward and impersonal.

Granola saw this gap and decided to build “the only one putting the human first.” Instead of trying to replace human note-takers, they created an AI-powered notepad that works alongside your natural note-taking habits.

How Granola Actually Works

The concept is beautifully simple. Granola works by installing locally on your Mac and connecting to your calendar. It captures audio from popular meeting platforms like Zoom, Google Meet, and Microsoft Teams without requiring any meeting bots to join. You jot down the things that matter to you during the meeting, just like you would with a regular notepad.

The magic happens afterward. Granola uses AI to transcribe the entire meeting in the background, then combines your handwritten notes with the full transcript to create comprehensive, useful notes. No awkward meeting bots – just beautiful notes for you and your team, every single time.

Why Silicon Valley Went Crazy for It

The milestone showcased an incredible story. In October 2024, Granola raised a $20 million Series A funding round despite just 5,000 weekly users. That number has grown consistently by 10% each week since, reaching around 50,000 users by early 2025. Then in May 2025, AI-powered notetaking app Granola is raising $43 million in funding at a $250 million valuation.

But it’s not just about the money. Since launch, Granola has quickly gained traction among senior tech leaders at companies like Vercel, Ramp, and Roblox and top venture capital firms including Benchmark, Sequoia, Accel. These aren’t just any users—they’re the people who see hundreds of AI tools every week and choose what’s worth their time.

The Human-First Philosophy That Won

What makes Granola different isn’t just its technology—it’s its philosophy. They advocate a message that resonated across Silicon Valley: AI should support human thought, not replace it. In a world where AI companies rush to automate everything, Granola’s approach feels refreshingly human.

The app doesn’t try to think for you or make decisions about what’s important. Instead, it amplifies your own judgment and note-taking style. You decide what to write down in the moment, and AI fills in the gaps later. This approach respects both human intelligence and the irreplaceable value of being present in conversations.

AI Tools

Granola’s success represents something bigger than just good note-taking software. It shows that the most successful AI tools might not be the ones that replace human tasks entirely, but the ones that make human capabilities stronger. We worry a lot about AI replacing humans, sometimes AI tools can just make better humans.

The app also proves that simple concepts, executed well, can beat complex solutions. While other companies built elaborate AI meeting assistants with dozens of features, Granola focused on doing one thing exceptionally well—making meeting notes better without changing how people naturally work.

As remote work continues and meetings multiply, tools like Granola become more essential. The company’s rapid growth and high-profile funding rounds suggest that Silicon Valley believes AI-assisted note-taking is just the beginning of a larger trend toward human-AI collaboration.

For professionals drowning in meetings, Granola offers hope that AI can actually make work more human, not less. By handling the tedious parts of note-taking while preserving the human elements of attention and judgment, it might just represent the future of how we’ll work alongside artificial intelligence.

The lesson for other AI companies is clear: sometimes the best way to grab Silicon Valley’s attention isn’t to replace what humans do, but to make them better at it.

Picture this: you’re sitting in a doctor’s office, describing symptoms that have been puzzling you for weeks. Your physician furrows their brow, orders several tests, and you’re left wondering if you’ll ever get a clear answer. Now imagine if that same consultation involved an AI system that could diagnose your condition with 85% accuracy while your doctor might only get it right 20% of the time. Sound like science fiction? Well, it’s not anymore.

Microsoft’s latest breakthrough in medical AI has sent shockwaves through the healthcare industry. The Microsoft Medical AI Diagnostic Orchestrator (MAI-DxO) isn’t just another AI tool—it’s a complete game-changer that’s redefining how we think about medical diagnosis. Let’s dive into why this technology is causing such a stir and what it means for the future of healthcare.

What Exactly is Microsoft Medical AI’s MAI-DxO?

Here’s where things get really interesting. The MAI-DxO isn’t your typical AI diagnostic tool that simply crunches numbers and spits out results. Instead, it turns any language model into a virtual panel of clinicians: it can ask follow-up questions, order tests, or deliver a diagnosis, then run a cost check and verify its own reasoning before deciding whether to proceed.

Think of it as having a team of the world’s best doctors collaborating on your case, but they never get tired, never have bad days, and can process information at lightning speed. The system doesn’t just analyze your symptoms all at once—it follows a methodical approach that mirrors how the best physicians work.

MAI-DxO (Image Credit – Microsoft)

Rather than analyzing complete case information at once, MAI-DxO follows a sequential process—starting with limited patient information, asking targeted questions, ordering specific tests, and gradually building toward a diagnosis. It’s like watching a master detective solve a complex case, but instead of hunting down criminals, it’s hunting down diseases.

The Numbers Don’t Lie: MAI-DxO vs. Human Doctors

Now, let’s talk about the elephant in the room—the performance statistics that have everyone talking. Microsoft’s new model-agnostic MAI Diagnostic Orchestrator (MAI-DxO) achieved 85.5 percent diagnostic accuracy—outperforming generalist physicians, who reached the correct diagnosis 20 percent of the time, on average.

That’s not a typo. We’re talking about more than four times better accuracy than experienced human physicians. But here’s the kicker—MAI-DxO also reduced diagnostic costs by 20 percent compared to physicians, with some reports suggesting cost reductions of up to 70% in certain scenarios.

You might be wondering, “How is this possible?” Well, the system correctly diagnoses 85% of diagnostically complex cases published by the New England Journal of Medicine (NEJM), compared to a mean accuracy of 20% among the practicing physicians. These weren’t simple cases either—we’re talking about the kind of diagnostic puzzles that keep doctors up at night.

How Microsoft Medical AI Actually Works: The Magic Behind the Curtain

So what makes MAI-DxO so special? It’s all about orchestration. The system is designed to emulate a virtual panel of physicians with diverse diagnostic approaches collaborating to solve diagnostic cases. Imagine having access to a room full of specialists, each bringing their unique perspective to your case.

Like a human physician, MAI-DxO diagnoses by analyzing symptoms, posing questions, and recommending medical tests. A key feature is its ability to optimize costs, preventing the ordering of superfluous diagnostics that contribute to overspending in healthcare.

The system is incredibly smart about resource management. The MAI-DxO, being an orchestrator, accesses multiple language models and integrates diverse data sources. It is also configurable so that it can be told to operate within defined cost constraints. This means it won’t order unnecessary tests just to be safe—it’s strategic about what information it needs to reach a diagnosis.

Real-World Impact: What This Means for Patients and Healthcare

Let’s face it—healthcare costs are through the roof, and diagnostic errors are more common than we’d like to admit. Traditional medical diagnosis often involves a frustrating cycle of appointments, tests, second opinions, and sometimes, unfortunately, misdiagnosis. Microsoft Medical AI is poised to change all of that.

The practical implications are staggering. When you consider that the team tested their system on 304 diagnostically challenging cases, and it consistently outperformed human physicians, we’re looking at a technology that could save lives, reduce suffering, and cut healthcare costs simultaneously.

Cost Savings That Actually Matter

Healthcare spending is a major concern for individuals and healthcare systems worldwide. The ability of MAI-DxO to reduce diagnostic costs while improving accuracy addresses two critical problems at once. The system can operate within defined cost constraints to help prevent excessive testing, which means fewer unnecessary procedures and lower bills for patients.

Speed and Accessibility

One of the most exciting aspects of Microsoft Medical AI is its potential to democratize access to high-quality diagnostic expertise. While it might take weeks to get an appointment with a specialist, an AI system like MAI-DxO could provide expert-level diagnostic support instantly, anywhere in the world.

The Technology Behind the Breakthrough

What makes MAI-DxO so revolutionary isn’t just its accuracy—it’s how it achieves that accuracy. The system represents a fundamental shift from traditional AI approaches to medical diagnosis.

Orchestration vs. Simple Analysis

Most AI diagnostic tools work by analyzing all available information at once and providing a diagnosis. MAI-DxO takes a completely different approach. It acts more like a thoughtful physician who asks strategic questions, considers various possibilities, and builds a case step by step.

This methodical approach allows the system to be more efficient with resources while achieving better outcomes. It’s not just about having more data—it’s about using the right data in the right sequence.

Multiple AI Models Working Together

The “orchestrator” aspect of MAI-DxO is particularly fascinating. Instead of relying on a single AI model, the system coordinates multiple language models, each potentially bringing different strengths to the diagnostic process. It’s like having a medical team where each member has different specialties and perspectives.

Challenges and Considerations

Of course, no technology is perfect, and the integration of Microsoft Medical AI into healthcare systems won’t happen overnight. There are important questions about regulation, liability, and the role of human physicians in an AI-augmented world.

The Human Element

While MAI-DxO’s performance statistics are impressive, medicine is about more than just accurate diagnosis. The human connection between doctor and patient, the ability to provide emotional support, and the nuanced understanding of individual patient needs remain crucial aspects of healthcare that AI cannot fully replace.

Regulatory Hurdles

Before MAI-DxO can be widely deployed in clinical settings, it will need to navigate complex regulatory approval processes. Medical AI systems must meet stringent safety and efficacy standards, and rightly so—people’s lives are on the line.

What This Means for the Future of Healthcare

The success of Microsoft Medical AI represents more than just a technological achievement—it’s a glimpse into the future of healthcare. We’re moving toward a world where AI and human expertise work together to provide better, faster, and more affordable medical care.

Democratizing Medical Expertise

One of the most exciting possibilities is the democratization of high-quality medical diagnosis. Rural areas, developing countries, and underserved communities could potentially access world-class diagnostic expertise through systems like MAI-DxO.

Reducing Healthcare Costs

With healthcare costs continuing to rise globally, technologies that can improve outcomes while reducing costs are desperately needed. Microsoft Medical AI’s ability to cut diagnostic costs by 20-70% while improving accuracy could be a game-changer for healthcare economics.

Supporting, Not Replacing, Physicians

The goal of MAI-DxO isn’t to replace doctors but to augment their capabilities. Imagine physicians having access to a tool that can help them consider diagnoses they might have missed, ask questions they might not have thought of, and optimize their diagnostic approach for both effectiveness and cost.

The Road Ahead: What to Expect

As impressive as these initial results are, we’re still in the early stages of medical AI development. Microsoft AI CEO Mustafa Suleyman talks about the diagnostic breakthrough and the future of medical AI, suggesting that this is just the beginning of a much larger transformation in healthcare.

The technology will likely continue to improve as it processes more cases and learns from real-world applications. We can expect to see more specialized versions of MAI-DxO designed for specific medical fields, from radiology to psychiatry.

Actionable Takeaways for Healthcare Stakeholders

If you’re involved in healthcare—whether as a provider, administrator, or simply someone who cares about the future of medicine—here are some key points to consider:

For Healthcare Providers:

• Start familiarizing yourself with AI diagnostic tools and their capabilities
• Consider how AI assistance could improve your diagnostic accuracy and efficiency
• Think about how to integrate AI tools while maintaining the human connection that patients value

For Healthcare Systems:

• Evaluate the potential cost savings and quality improvements that AI diagnosis could provide
• Begin planning for the infrastructure needed to support AI-augmented healthcare
• Consider partnerships with technology companies like Microsoft to pilot AI diagnostic tools

For Patients:

• Stay informed about advances in medical AI and what they might mean for your healthcare
• Understand that AI tools like MAI-DxO are designed to support, not replace, your doctor
• Advocate for access to the best diagnostic tools available, including AI-assisted diagnosis

A New Era in Medical Diagnosis

Microsoft Medical AI’s MAI-DxO represents a watershed moment in healthcare technology. With its ability to achieve 85% diagnostic accuracy compared to physicians’ 20%, while simultaneously reducing costs, we’re looking at a technology that could fundamentally transform how medical diagnosis is performed.

The implications extend far beyond just better statistics. We’re talking about faster diagnosis, reduced healthcare costs, improved access to expert-level medical care, and ultimately, better outcomes for patients worldwide.

As we stand on the brink of this medical AI revolution, one thing is clear: the future of healthcare will be a collaborative effort between human expertise and artificial intelligence. Microsoft Medical AI has shown us what’s possible when we embrace this partnership, and the results are nothing short of extraordinary.

What do you think about AI-assisted medical diagnosis? Would you be comfortable having an AI system like MAI-DxO involved in your healthcare? Share your thoughts and concerns about the future of medical AI in the comments below.