What’s the BUZZ? — AI in Business

In this episode, Andrea Isoni (Chief AI Officer) and Andreas Welsch discuss how you can prepare for the E.U. AI Act. Andrea shares his insights on the upcoming regulation as well as AI-related ISO certifications and provides valuable insights for listeners looking to better understand the impact of regulation on their AI products.Key topics:- Understand E.U. AI Act's impact and protective measures - Prioritize AI leaders' top three essential actions - Discover recent developments in the evolving AI Act - Identify critical regulations, compliance efforts, and standardsListen to the episode to hear how you can:- Determine the risk classification of your AI model- Assess your Generative AI cyber security exposure, potential leaks, and attacks- Decide which kind of governance you need for your AI models based on the new ISO 42001 standardWatch this episode on YouTube:https://youtu.be/uRPjhONR0xUQuestions or suggestions? Send me a Text Message. Support the show***********Disclaimer: Views are the participants’ own and do not represent those of any participant’s past, present, or future employers. Participation in this event is independent of any potential business relationship (past, present, or future) between the participants or between their employers.Level up your AI Leadership game with the AI Leadership Handbook:https://www.aileadershiphandbook.comMore details: https://www.intelligence-briefing.com All episodes:https://www.intelligence-briefing.com/podcastGet a weekly thought-provoking post in your inbox:https://www.intelligence-briefing.com/newsletter

In this episode, Daniel Faggella (Founder, Emerj Research) and Andreas Welsch discuss the big trends and predictions for Generative AI in the enterprise. Daniel shares his insights on Generative AI and provides valuable advice for listeners looking to implement AI in business this yearKey topics:- Anticipate key trends for Generative AI in 2024 - Determine focus areas for AI leaders to prioritize AI this year- Drive adoption of AI and Generative AI in your business- Outlook on Generative AI over the next 3-5 yearsListen to the full episode to hear how you can:- Understand why established vendors will lead the first wave of Generative AI- Benefit from an increased level of AI fluency within the C-Suite for AI adoption- Assess risk appetite vs. risk aversion within the enterprise- Expect a significant impact of LLMs on work and the economy Watch this episode on YouTube:https://youtu.be/nbDSvfBClqwQuestions or suggestions? Send me a Text Message. Support the show***********Disclaimer: Views are the participants’ own and do not represent those of any participant’s past, present, or future employers. Participation in this event is independent of any potential business relationship (past, present, or future) between the participants or between their employers.Level up your AI Leadership game with the AI Leadership Handbook:https://www.aileadershiphandbook.comMore details: https://www.intelligence-briefing.com All episodes:https://www.intelligence-briefing.com/podcastGet a weekly thought-provoking post in your inbox:https://www.intelligence-briefing.com/newsletter

In this episode, Enrico Santus (Human-AI Collaboration Leader) and Andreas Welsch discuss designing human-AI collaboration for adaptive processes. Enrico shares his experience in balancing the strengths of humans and AI for optimal results in business processes by gaining trust and sharing a long-term vision.Key topics:- Design processes for humans and AI working together- Learn what makes processes adaptive- Understand key challenges when designing systems for human-AI collaboration- Implement principles for effective collaborationListen to the full episode to hear how you can:- Leverage the strengths of humans and AI- Define AI as a far-reaching goal vs. small projects- Assess complexity, ambiguity, and risk for optimal use of AI- Share long-term goals for using AI to ensure trust and avoid overrelianceWatch the full episode:https://youtu.be/R8rxQN60eGMQuestions or suggestions? Send me a Text Message. Support the show***********Disclaimer: Views are the participants’ own and do not represent those of any participant’s past, present, or future employers. Participation in this event is independent of any potential business relationship (past, present, or future) between the participants or between their employers.Level up your AI Leadership game with the AI Leadership Handbook:https://www.aileadershiphandbook.comMore details: https://www.intelligence-briefing.com All episodes:https://www.intelligence-briefing.com/podcastGet a weekly thought-provoking post in your inbox:https://www.intelligence-briefing.com/newsletter

In this episode, Laks Srinivasan (Founder of Institute for Return on AI) and Andreas Welsch discuss how technology leaders can help their business counterparts develop AI literacy. Laks shares his insights on working with leadership teams and provides valuable advice for listeners looking to help their leaders become more familiar with AI. Key topics: - Describe AI Fluency - Identify level AI Fluency of business leaders - Increase AI Fluency of leadership teams Listen to the full episode to hear how you can: - Help leaders become more comfortable with AI - Choose tools and methods to increase AI literacy - Customize enablement program by leader and role Watch this episode on YouTube: https://youtu.be/7OLb0nbMUO0Questions or suggestions? Send me a Text Message. Support the show***********Disclaimer: Views are the participants’ own and do not represent those of any participant’s past, present, or future employers. Participation in this event is independent of any potential business relationship (past, present, or future) between the participants or between their employers.Level up your AI Leadership game with the AI Leadership Handbook:https://www.aileadershiphandbook.comMore details: https://www.intelligence-briefing.com All episodes:https://www.intelligence-briefing.com/podcastGet a weekly thought-provoking post in your inbox:https://www.intelligence-briefing.com/newsletter

In this episode, Mark Stouse (CEO, Proof Analytics) and Andreas Welsch discuss teaching your data scientists about the business. Mark shares his perspective on connecting data science & AI teams with their peers in the business and provides valuable advice for listeners looking to bridge communication gaps, manage expectations, and focus on AI-driven business outcomes.Key topics:- Identify the challenges AI and business teams face when working together- Improve communication between AI and business teams- Understand the impact when data scientists have more context about the business- Learn how AI leaders support their team members to upskillListen to the full episode to hear how you can:- Develop an understanding of the business context and connect with business leaders- Shift from precision to pragmatism- Deliver business value quickly- Operationalize data science & AI quickly and adapt to the fast-paced business environmentWatch this episode on YouTube:https://youtu.be/WE7sopcsFIIQuestions or suggestions? Send me a Text Message. Support the show***********Disclaimer: Views are the participants’ own and do not represent those of any participant’s past, present, or future employers. Participation in this event is independent of any potential business relationship (past, present, or future) between the participants or between their employers.Level up your AI Leadership game with the AI Leadership Handbook:https://www.aileadershiphandbook.comMore details: https://www.intelligence-briefing.com All episodes:https://www.intelligence-briefing.com/podcastGet a weekly thought-provoking post in your inbox:https://www.intelligence-briefing.com/newsletter

In this episode, Keith McCormick (Executive Data Scientist) and Andreas Welsch discuss the key roles to focus on when building your AI team. Keith shares his expertise on Generative AI, Artificial Intelligence, and Machine Learning and provides valuable insight) for listeners looking to support their teams in the jungle of AI terms and technologies.Key topics:- Understand AI teams’ limitations on prompting- Identify the key skills AI teams need beyond prompting- Retain data engineers and data scientists for AI projects- Choose the best time and topic to upskill AI teams onListen to the full episode to hear how you can:- Guide data scientists to lead AI projects- Teach the most critical skill on an AI team- Apply traditional machine learning skills for forecasting, supervised and unsupervised learning- Understand why Generative AI does not replace forecastingWatch this episode on YouTube:https://youtu.be/u33luD5dx04Questions or suggestions? Send me a Text Message. Support the show***********Disclaimer: Views are the participants’ own and do not represent those of any participant’s past, present, or future employers. Participation in this event is independent of any potential business relationship (past, present, or future) between the participants or between their employers.Level up your AI Leadership game with the AI Leadership Handbook:https://www.aileadershiphandbook.comMore details: https://www.intelligence-briefing.com All episodes:https://www.intelligence-briefing.com/podcastGet a weekly thought-provoking post in your inbox:https://www.intelligence-briefing.com/newsletter

In this episode, Tobias Zwingmann (AI Advisor & Author) and Andreas Welsch discuss building Generative AI applications with Open Source technology. Tobias shares his examples on weighing proprietary against open source technology for large language models and provides valuable advice for listeners looking to decide whether to use commercially available LLMs or open models such as Llama 2.Key topics:- What types of use cases does Generative AI enable?- When should you use off the shelf vs open source LLMs?- What components do you need to set up, train, and use Open Source LLMs?- What are the downsides and risks of using Open Source components?Listen to the full episode to hear how you can:- Understand the four categories of Generative AI use cases- Evaluate when off the shelf is more advantageous vs open source- Consider total cost to operate an LLM- Determine the risk of skill shortages for cutting edge technologiesWatch this episode on YouTube:https://youtu.be/g9TNndkfdU0Questions or suggestions? Send me a Text Message. Support the show***********Disclaimer: Views are the participants’ own and do not represent those of any participant’s past, present, or future employers. Participation in this event is independent of any potential business relationship (past, present, or future) between the participants or between their employers.Level up your AI Leadership game with the AI Leadership Handbook:https://www.aileadershiphandbook.comMore details: https://www.intelligence-briefing.com All episodes:https://www.intelligence-briefing.com/podcastGet a weekly thought-provoking post in your inbox:https://www.intelligence-briefing.com/newsletter

Harpreet Sahota, a Developer Relations Expert, discusses augmenting Generative AI models with new data. Topics include techniques to improve results, building RAG-based systems, and overcoming LLM limitations. The importance of data quality and combining fine-tuning with RAG are also explored. Key takeaways include using RAG for current data, comparing fine-tuning and RAG, and building a vector store for better generation quality.

In this episode, Matt Lewis (Chief AI Officer) and Andreas Welsch discuss how you can grow your Chief AI Officer (CAIO) role. Matt shares his journey on transitioning from CDAO to CIAO and provides valuable advice for listeners aspiring to grow into an AI leadership role.Key topics:- Why do you need a Chief AI Officer?- What are the top focus areas of this role?- How can you continuously learn about generative AI?- What are CAIOs most concerned about?Listen to the full episode to hear how you can:- Hear what a Chief AI Officer does and why they should report to the CEO- Understand why cross-domain skills prepare your for a CAIO role and why industry knowledge is key- Get tips how to learn about generative AI while managing your time- Frame AI projects in the context of augmented intelligenceWatch this episode on YouTube:https://youtu.beTecRJLoiZxIQuestions or suggestions? Send me a Text Message. Support the show***********Disclaimer: Views are the participants’ own and do not represent those of any participant’s past, present, or future employers. Participation in this event is independent of any potential business relationship (past, present, or future) between the participants or between their employers.Level up your AI Leadership game with the AI Leadership Handbook:https://www.aileadershiphandbook.comMore details: https://www.intelligence-briefing.com All episodes:https://www.intelligence-briefing.com/podcastGet a weekly thought-provoking post in your inbox:https://www.intelligence-briefing.com/newsletter

Steve Wilson, Project Leader at OWASP Foundation, discusses securing Large Language Models (LLMs) against vulnerabilities. Key topics explored include the most important vulnerabilities of LLMs, underestimation of security risks by developers, how these vulnerabilities will be exploited, and mitigation strategies. The podcast emphasizes balancing innovation and security risks, understanding prompt injections, preventing over-assigning agency to LLMs, and establishing trust boundaries with LLM-generated output.