OPEN Tech Talks: Technology worth Talking| Artificial Intelligence |Tools & Tips

Generative AI Adoption Maturity Model The last two weeks' articles on the Generative AI adoption Maturity framework sparked discussion within the AI circle. Thank you for sharing the comments and feedback, and even triggering a few thought-provoking views on this topic. We have started a journey to develop a Gen AI Maturity Model or framework as a joint effort with a few organizations' colleagues, friends, and leadership teams. Earlier work: 1. Where Are You on the Generative AI Maturity Curve? [https://aitechcircle.kit.com/posts/where-are-you-on-the-generative-ai-maturity-curve] 2. Generative AI Maturity Framework for Structured Guidance [https://aitechcircle.kit.com/posts/generative-ai-maturity-framework-for-structured-guidance] 3. Why Maturity matters and levels of Gen AI Maturity model [https://aitechcircle.kit.com/posts/dubai-ai-week-highlights-and-advancing-the-ai-maturity-framework] This week, we will continue this journey: Generative AI Maturity Model Overview The model defines six sequential levels and six dimensions. The full article with the slide is available here: https://www.otechtalks.tv/mapping-your-generative-ai-maturity-from-aware-to-transformative-part-1/ [https://www.otechtalks.tv/mapping-your-generative-ai-maturity-from-aware-to-transformative-part-1/]

Welcome to this edition of AI Tech Circle, brought to you by Open Tech Talks, your briefing on the latest developments in AI technology, strategic deployment, and measurable impact. This week’s focus is on key takeaways from Stanford HAI’s 2025 AI Index Report [https://hai.stanford.edu/ai-index/2025-ai-index-report], which is a comprehensive snapshot of the state of AI across investments, performance gains, enterprise integration, and national-level infrastructure initiatives. AI on the Rise: Global Momentum, Tangible Impact, and Breakthrough Performance The 2025 AI Index Report marks a clear inflection point in the AI timeline. With record-breaking capital inflows, widespread business adoption, and accelerating improvements in model capabilities, AI is no longer speculative. It’s operational. Costs are falling fast, governments are investing at scale, and productivity metrics are beginning to validate the economic promise. The era of “potential” has ended; the execution age is here. Read the full report at AI Tech Circle [https://aitechcircle.kit.com/posts/ai-on-the-rise-from-global-investments-real-world-impact-to-performance-breakthroughs]: https://aitechcircle.kit.com/posts/ai-on-the-rise-from-global-investments-real-world-impact-to-performance-breakthroughs [https://aitechcircle.kit.com/posts/ai-on-the-rise-from-global-investments-real-world-impact-to-performance-breakthroughs]

Welcome to Open Tech Talks. This episode features Sébastien Night, Co-Founder and CEO of OneTake AI. He has a strong background in entrepreneurship, having led the Free Entrepreneur Movement, which reached hundreds of thousands across 41 countries. Today, it focuses on building an AI product from scratch, validating the idea, managing development, handling challenges with LLMs, and navigating growth and marketing as a tech founder. This is a hands-on conversation for creating, scaling or optimizing AI-powered products. This episode gives a practical look at how to take an AI product from concept to scale. From validating the idea and building the core system to managing AI challenges and marketing the product effectively, the conversation offers real lessons that apply to any founder or builder. For more structured insights on AI, product growth, and tech leadership, stay tuned to Open Tech Talks.   Episode # 156 Today’s Guest: Sébastien Night, Co-Founder, OneTake AI He is the CEO of One Take, and Before this, he founded the Free Entrepreneur Movement, which attracted close to 300,000 entrepreneurs in 41 countries. * Website: OneTake [https://www.onetake.ai] What Listeners Will Learn: * Product Idea Validation: Learn how to test a new product idea with early users and feedback loops before building at scale. * Building an AI Product from Scratch: Understand the steps involved in developing a product with a strong AI foundation, from design to execution. * Integrating AI into Products: Gain practical insights into how to add AI features to products in a structured and effective way. * Challenges with LLM Integration: Learn about the challenges of using large language models, including technical constraints and performance reliability. * Marketing as a Tech Founder: Understand the difficulties tech founders often face when managing product and marketing efforts simultaneously. * Marketing Metrics and User Acquisition: Explore how marketing success is measured and how product teams track growth, subscriptions, and engagement over time. Resources: * OneTake [https://www.onetake.ai]

Welcome to your weekly AI Newsletter from AITechCircle [https://aitechcircle.com/]! I'm building and implementing AI solutions and sharing everything I learn along the way... Check out the updates from this week! Please take a moment to share them with a friend or colleague who might benefit from these valuable insights! Today at a Glance: * Increasing the adoption and effective use of AI and Generative AI technologies in various use cases or business processes * Generative AI Use cases repository * AI Weekly news and updates covering newly released LLMs * Courses and events to attend How to Grow AI/Generative AI Inference? This week, I read about Chet Holmes’s Buyer's Pyramid [https://chetholmes.com/attracting-new-buyers/] . This was my first time seeing it, and its source is 'The Larger Market Formula. [https://www.clck.com.au/larger-market-formula/]' Why did this get my attention? I am linking this to the situation of the Generative AI Landscape, which is going on in the market where we all started realizing sooner enough that whatever investment is   Going on the AI Infrastructure is about what and how we will use it, and we need to have an AI Infrastructure in place to do the Inference. The full article read over here: https://aitechcircle.kit.com/posts/generative-ai-engagement-pyramid-for-growing-ai-inference [https://aitechcircle.kit.com/posts/generative-ai-engagement-pyramid-for-growing-ai-inference]

Welcome to Open Tech Talks, where we explore AI, cybersecurity, and the evolving role of technology in businesses. In this episode, we speak with Terry Ziemniak, a Fractional CISO and Partner at TechCXO, who has worked with companies across the healthcare, retail, manufacturing, and government sectors.  The discussion covers cybersecurity risks, strategies for companies of all sizes, the challenges of adopting Generative AI, and governance frameworks for mitigating AI-related risks. Whether you’re a business leader, security professional, or AI enthusiast, this episode provides practical insights into managing security in today’s rapidly changing digital landscape. Before going further, let's understand what these Fractional Roles are: Fractional leadership is an emerging trend that allows companies to hire high-level expertise without committing to a full-time executive role. For example, Fractional CISOs provide the same security leadership as traditional CISOs. Still, they are part-time or project-based, making cybersecurity expertise accessible to businesses that may not have the budget for a full-time role. By following the best security and AI governance practices, organizations can protect themselves against threats while leveraging technology to drive growth. Episode # 154 Today’s Guest: Terry Zimnick, Fractional CISO,  Terry Ziemniak is a Partner in TechCXO’s Product and Technology practice. He is a cybersecurity leader sought by boards, investors, and senior management teams to assist healthcare, service organizations, retail, and manufacturing companies—as well as government agencies and contractors—in his role as a fractional CISO. * Website: TechCXO [https://www.techcxo.com/partners/terry-ziemniak/] * Linkedin: Terry [https://www.linkedin.com/in/terryziemniak/]  What Listeners Will Learn: * Understanding Fractional Roles in Cybersecurity: How businesses leverage fractional Chief Information Security Officers (CISOs) for cost-effective security leadership. * Cybersecurity Landscape: Current threats, vulnerabilities, and trends shaping cybersecurity in different industries. * Security Practices in Large vs. Small Companies: The challenges faced by small and medium-sized businesses (SMBs) in implementing cybersecurity measures compared to larger organizations. * Challenges in Adopting Generative AI: Key obstacles companies face when integrating AI and large language models (LLMs) into their workflows. * Generative AI Risk and Governance: The importance of AI governance frameworks and how businesses can structure policies to ensure compliance and security. * Cybersecurity Strategies for SMBs: Practical steps for small businesses to strengthen security and mitigate risks without requiring large budgets. Resources: * TechCXO [https://www.techcxo.com/partners/terry-ziemniak/]