Evangelos Simoudis’ Post

Excellent summary of the challenges in maximizing and mainstreaming enterprise AI usage by Evangelos who has advised on AI usage across the numerous industries and for his Synapse Partners investments. His thoughts mirror what I am seeing across the industry and with my consulting clients. Most companies are not putting the same energy, investment, and passion into making their data 'AI ready'. Too many AI projects are staffed and led by AI experts, not industry, consumer, and business data experts. They tend to lean on open source and commoditized AI models that are too often non-differentiated and they under-invest in the data which is the biggest differentiator and biggest inhibitor. Getting the data right matters more than ever, especially when the goal of AI is to reduce human expert oversight ;-) If you like this, check my 'AI Ready Data' blog post, it skews to CPG, retailers, and media, but most of the points apply for across verticals, especially to anyone dealing with consumers. https://lnkd.in/dHJ8p55E

I've been seeing way more front desk AI automation startups that are targeting private practices. Some are founded by physicians and others by non physicians. Here's what they're both getting wrong about private practice SMB as a customer. 1. The persona willing to adopt AI automation is rarely looking to scale into a traditional private practice model with the traditional panel of patients. Their willingness to adopt is not related to their willingness to pay. Meaning you will not hit venture revenue scale with this customer. 2. The persona that is willing to scale into the traditional private practice model is not willing to adopt AI automation. Once they do scale they most likely will do so using traditional staff or traditional managed services, NOT AI AUTOMATION. Instead the staff or managed services will use AI, but not the practice itself. Meaning the TAM is a lot smaller if your only value is just an AI tool. I've seen startup after startup over the last 6+ years struggle with this issue. They'll encounter a few early adopters and get convinced that their excitement applies to the entire TAM of physicians when in reality, they are the outliers and the market consists ONLY of one of the two options listed above. #PrivatePractice

The defining factor isn't the size of the company or startup, but the vision behind it. Take OpenAI, for instance. Until last year, unless you were deeply embedded in the ML world as a computer scientist/researcher, or enthusiast, you might not have heard of OpenAI. Meanwhile, a giant like Google was dominating the scene. However, a few years back, OpenAI was just another small startup. Now, it's rapidly evolving into a major player in big tech. Why and how? It comes down to having a long-term vision, a clear roadmap, patience, and solid execution (i.e., talents). Even in the context of healthcare AI, where (small) startups face many challenges (including the ones mentioned), the principles of vision and strategy apply. While merging with big tech might seem like an option for some, if a startup truly believes in its vision and has a well-defined path to achieve it, it should forge ahead independently. The landscape is evolving, and like OpenAI, today’s small startups with clear, visionary goals could be tomorrow's industry leaders. #starup #founders #openai #google #healthcare

A nice article in Thinkbusiness.ie highlighting Irish businesses that are developing best in-field AI solutions. Good to see several EdTech Ireland members listed, as AI is the key driver for Innovation and enhanced teaching and learning. #edtech #aiforeducation #innovation #teachingandlearning

Getvisibility is simply brilliant….just imagine if you could build #classification across, and #taxonomy around, every single piece of your unowned/ unassigned/ legacy data…🤔 now THAT is powerful. Want to know more? Call Gradian on 01276 534771.

Hippocratic AI raises $141M for creating AI agents to handle patient-facing tasks On Thursday, Hippocratic AI, a firm developing AI solutions for non-diagnostic patient-facing tasks, revealed that it had raised an impressive $141 million in Series B funding. The funding comes five months after Hippocratic AI raised $17 million from Nvidia and nine months after the company raised $53 million from General Catalyst and Andreessen Horowitz. Hippocratic AI addresses the lack of healthcare personnel by developing agents that can carry out basic activities including pre-operative procedures, remote patient monitoring, and appointment planning, whereas the majority of healthcare-generative AI businesses concentrate on lowering administrative hassles. Hippocratic agents are able to use data from medical records, verify patients' identities, answer questions about medications, procedures, and services, create call reports, and much more to cover as much manual labor for personnel as possible. The firm has agreements with 23 insurers and health systems as of 2024. Hippocratic is utilizing fresh funding to take the product into new areas and abroad. Impressive achievements for company founded only 2 years ago! What do you think about this use of AI technologies in Healthcare industry? #amgrade #startup #outsourcing #softwareengineer #webdesign #software #fullstack #laravel #websitedevelopment #mobiledevelopment #website #business #saas #news #ai #healthcare

Through the collaboration, General Catalyst portfolio companies will use AWS’ services to build and roll out AI tools for health systems more quickly. Aidoc, which applies AI to medical imaging, and Commure, which automates provider workflows with AI, will be the first two companies to participate.

Based on the extensive research by Andreessen Horowitz, it seems that GenAI is no longer just a hype: Budgets are expected to triple in 2024. • Most GenAI projects focus on cost efficiency in customer service (Fortune 500 companies spend $6 per call on average). • Top executives believe there will be a positive ROI within three years, but this is not guaranteed. • The control and customizability of open-source solutions are driving budget reallocations from proprietary technology. • There is a lack of GenAI talent -- https://lnkd.in/gAryJNmC

🚀 Abridge, founded in 2018, develops an AI-powered platform that helps improve understanding of medical data. Their technology is specifically designed for medical conversations, automating the documentation process and allowing doctors to spend more time with their patients. 📊 Abridge's flagship product is a system that transforms doctor-patient conversations into structured clinical notes in real-time, integrated with electronic medical records (EMR). The platform uses a unique approach where AI generates notes mapped to the original information, allowing doctors to quickly verify and trust the results. 💰 In February 2024, Abridge raised $150 million in a Series C funding round led by Lightspeed Ventures to streamline the documentation process. https://lnkd.in/g7Zpg7PJ #AI #HealthTech #MedicalTechnology #Startups #Investments #DigitalHealth #Automation

Five Actions Enterprises Can Take to Accelerate GenAI Adoption https://lnkd.in/gnBY_gwE #genai