Karthik Ramakrishnan’s Post

AI adoption in the enterprise continues to gain steam. My colleagues Karthik Ramakrishnan and Cynthia Kuo wrapped up the most promising enterprise AI companies we’ve been hearing about in our conversations with C-Suite decision-makers. Check it out: https://lnkd.in/eJAChbKE

♟️ "Imagine a chessboard that extends across your entire enterprise. AI helps you see moves you never even knew existed." I recently spoke with Jean Marc Goguikian, CEO at Konko.ai. Our conversation wasn't just about task automation. It was also about AI's potential to help us make better decisions under conditions of extreme uncertainty and complexity, thanks to broad-ranging simulations with "synthetic humans." While, yes, AI models trained on your data will be able to draft your emails, they’ll also be able to run high-dimensional multi-agent simulations, offering you a wide range of scenarios and analyses for critical business decisions (eg., preparing to have a tough conversation with a client or colleague). We also discussed what he's learned from enterprise buyers about the remaining barriers to enterprise integration: data security and change management are still significant hurdles, but they are not insurmountable. Of similar importance is the ubiquitous need for thoughtful partnerships between AI providers and businesses (from SMBs to enterprises) interested in using the technology to catalyze their strategic initiatives and solve real problems (not just razzle dazzle with shiny tech). So, what's next? Where should we expect to see the next great companies come into being as the next generation of AI technology comes online? Jean-Marc emphasized the opportunity that lies in making AI accessible to the early majority, not just the innovators. The next s-curve of AI innovation is likely not about the creation of more complex toolsets; it'll be about crafting user-friendly yet powerful solutions that leverage the technology in nigh-invisible ways. 🔗 Want more insight? Reach out to Jean Marc Goguikian for a personalized touch and guidance on enterprise AI implementation.

🚀 Navigating the AI Revolution in Small Business In the realm of burgeoning technology, AI continues to spearhead innovations that could transform mundane tasks into automated processes, enhancing productivity across the board. For startups and small businesses, staying updated with such advancements isn't just beneficial; it's imperative for scaling efficiently amidst ever-growing competition. 🌐 Key Insights from Orby AI's Latest Development: - 🤖 AI agents developed by Orby are designed to autonomously execute tasks like data entry and form validations, capturing the subtle nuances of everyday business operations. - 🌟 Leveraging both generative AI and symbolic AI, these tools are engineered to adapt to new workflows dynamically—ensuring high-level accuracy even as your business evolves. 💡 How Can Startups Utilize Such Technologies? - 💼 Integrate AI to manage repetitive tasks, allowing your team to focus on more strategic initiatives. - 📈 Harness AI's data-processing capabilities to gain deeper insights into customer behaviors and market trends. Orby AI and similar technologies are not just tools; they represent a strategic pivot to more resilient, agile, and intelligent business operations. As we witness an increasing number of enterprises harnessing AI to maintain a competitive edge, the question for startups and small businesses is not if, but how quickly they can adapt to these changes. 🔗 For more information on how AI agents are shaping enterprise solutions: https://lnkd.in/gbhibuuE #Technology #AI #Startups This post was generated by an AI. Please contact us for more information.

Must read write-up on investments in AI and the market's understanding...

Are you looking for some light reading over the holidays?  Check out our State of Gen AI in the Enterprise report, which cuts through the hype to see what's really happening in enterprise AI, with insights from Naomi Pilosof Ionita and Derek Xiao.  REPORT:  https://lnkd.in/gj_4JVTt Here are a few key takeaways:    In 2023, enterprise spending on AI was surprisingly low. Buyers will not move from "experimentation" to "adoption" until they see real ROI. For now, the market will continue to favor incumbents who integrate AI into existing products. Incumbents are moving faster than ever before and have an advantage over newer entrants because established leaders have brand/trust, distribution, and data advantages.  Three areas where we see the most promising opportunities for AI startups:   Horizontal AI: next-gen workflow automation/agents Vertical AI: industry-specific software Modern AI stack: new infrastructure for AI

Profet AI Launches AILM, the World's First Enterprise AI Lifecycle Management Platform for AI Governance Taiwan-based Profet AI has launched AILM (AI Lifecycle Management Platform), the world's first enterprise platform for AI governance. Targeting the manufacturing industry, AILM enables companies to control, manage, and disseminate their core domain know-how, facilitating global expansion. The platform addresses common challenges in AI adoption, providing standardized problem identification, transparent implementation processes, and incentivized reward systems. Profet AI plans to integrate AILM with Generative AI to enhance usage efficiency. The company recently completed a Series A funding round, raising $5.6 million, and expanded its presence to Vietnam, Japan, Malaysia, Singapore, Thailand, and China. #ProfetAI #AILM #EnterpriseAI #AIgovernance #AI LifecycleManagement #ManufacturingIndustry #GlobalExpansion #StandardizedProcesses #IncentivizedRewards #GenerativeAI #SeriesAfunding #ExpansionInAsia #TechInnovation #AIAdoption #AIInBusiness #EnterpriseTech

🚀 Exploring the Strategic Role of CIOs in the Generative AI Revolution 🚀 As we stand on the cusp of a technological renaissance driven by generative AI, the pivotal role of Chief Information Officers (CIOs) cannot be overstated. AI's transformative potential holds immense power and responsibility. 🔍 Balancing Act: Innovation vs. Governance The opportunities with generative AI are groundbreaking, promising to elevate everything from code quality to operational efficiency. However, the rapid adoption of these tools raises significant challenges in managing technical debt and maintaining robust governance. The choices we make now will set the course for the future of technology. 🛠️ Prioritizing Quality and Security Stephen O’Grady from Red Monk points out the real risks associated with increased technical debt. This makes it imperative for CIOs to carefully select and manage AI tools to ensure they are deployed effectively and responsibly. 🚀 AI: The New Catalyst for Operational Excellence Imagine a workplace where every team member has an AI copilot, amplifying productivity and innovation. Leaders like Juan Perez of Salesforce and Neal Sample of Walgreens are making this a reality, showcasing AI's transformative impact across departments. 💡 Enhancing Team Empowerment and Customer Experiences AI isn’t just about automation—it’s about revolutionizing how we work and interact with customers, significantly boosting satisfaction across the board. But successful implementation is just the start. Ensuring the integrity of AI outputs and maintaining ethical standards are crucial. 🔗 Calling All CIOs! Navigating the AI integration journey is complex but filled with opportunities for significant enhancements in our technological and operational frameworks. How are you incorporating generative AI into your strategy? 👇 Share your thoughts and discuss AI’s future in business. For more in-depth insights, check out the full article on how CIOs are navigating generative AI in the enterprise. https://lnkd.in/gJrQe6Th #AI #technology #leadership #innovation #genai

Gen AI is opening up doors to company-wide innovation on a massive scale. But in this new era, leadership must carefully oversee its adoption to maintain code quality and mitigate technical debt. #GenAI #ITLeadership Read more: https://trib.al/jDUlSAO

🚀 Vertical Enterprise AI integration is trending, but are internal teams equipped for success? It's not just about tools; it's a unified vision that counts. Discover why many in-house approaches might miss the mark and the importance of an entrepreneurial touch.

Very good article summarizing the enterprise adoption of Gen AI. Key insights from the article. One interesting observation is the adaptation of open-source models by enterprises, which makes sense because they offer control, customization, and privacy. ·     Enterprise are tripling their budgets for generative AI, signaling a massive opportunity for startups · Open-source models are gaining popularity, with 46% of survey respondents expressing a preference for open-source models in 2024. ·     Enterprises are increasingly using multiple models to tailor to specific use cases thereby avoiding a lock-in. ·     Control and customization are the primary reasons for adopting open-source models, with cost being a lower priority. ·     While enterprises are currently focused on building AI applications in-house, the emergence of innovative apps beyond the "LLM + UI" formula could reshape the market. ·     Enterprises remain cautious about external use cases of generative AI, particularly due to concerns around safety and potential PR issues. ·     The total spend on model APIs and fine-tuning is expected to exceed $5 billion by the end of 2024, driven by increased enterprise adoption and investment. ·     RAG and Fine tuning are two popular methods used by enterprises to customize the models. https://lnkd.in/gAiSfzzG