What’s the BUZZ? — AI in Business

In this episode, Jonas Christensen (Senior Data & Analytics Leader) and Andreas Welsch discuss adopting a data-centric Machine Learning approach for small datasets. Jonas shares learnings on improving data quality before building models and provides valuable advice for listeners looking to improve their results with small data sets.Key topics:- Describe the common challenges businesses still run into with Machine Learning- Evaluate options for working with small data sets- Advise data scientists to get more data and better data- Deliver business value from Machine Learning at a time when everybody wants to chase Generative AIListen to the full episode to hear how you can:- Work toward better data quality over improving your model parameters- Approach data science as a team sport that requires actively influencing your business stakeholders- Share with your stakeholders how you use the data downstream to get them excited about their contributionWatch this episode on YouTube:https://youtu.be/C_GlTgRmeL8Questions 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, Jeremy Ravenel (Founder naas.ai) and Andreas Welsch discuss building AI agents for business with a mixture of assistants. Jeremy shares his journey from corporate finance to building a technology platform for AI agents and provides valuable insight) for listeners looking to increase efficiencies in their business with the help of AI agents that act as personal assistants.Key topics:- Learn why businesses need a specialized kind of intelligence- Assess when AI agents useful in business- Enhance AI apps with knowledge graphsListen to the full episode to hear how you can:- Be skeptical about the output that LLMs create- Map your internal knowledge with a knowledge graph to make it accessible to LLMs and AI agents- Describe your business in processes and workflows to spot potential areas for using AI agentsWatch this episode on YouTube:https://youtu.be/_E4YS-ypS9IQuestions 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

Senior AI CoE Leader, Srujana Kaddevarmuth, discusses scaling enterprise AI products, applying a product mindset, raising awareness of AI risks in deployment, deciding between Machine Learning and Generative AI, and increasing diversity for inclusive results. Topics include data democratization, data wrapper creation, edge AI, energy consumption, and building inclusive AI products for societal impact.

Kence Anderson, Founder & Machine Teaching Expert, discusses preparing AI agents for enterprise decision-making. Topics include machine teaching, complex reasoning, and building high-performance AI systems. Learn about data understanding, deep reinforcement learning, and creating hybrid business-technology teams for AI products.

In this episode, Philippe Rambach (Chief AI Officer, Schneider Electric) and Andreas Welsch discuss driving sustainability and energy efficiency with AI leadership. Philippe shares (their story/journey/insights/perspective/learnings/examples) on (specific aspect of topic) and provides valuable (advice/tips/insights) for listeners looking to (achieve specific outcome/learn more about topic).Key topics:- Get support for AI projects within your company- Prioritize AI scenarios based on business value and momentum-building- Anticipate future expected energy use for AI and its impact- Seize opportunities for AI in manufacturingListen to the full episode to hear how you can:- Start from business value instead of the AI technology- AI can optimize energy consumption and lower carbon emissions depending upon its use case- Select AI technology based on cost and emissions - Machine Learning remains highly relevant for processing structured data and forecastingWatch this episode on YouTube:https://youtu.be/i5lwGFvYU_cQuestions 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, Randy Bean (Founder, Data & AI Leadership Exchange) and Andreas Welsch discuss going beyond quick-win use cases for Generative AI. Randy shares perspective on data and AI leadership, spanning more than 35 years of experience in the industry,  and provides valuable advice for listeners looking to move from quick wins to strategic AI programs in business.Key topics:- See the parallels (good and bad) between the Generative AI and Machine Learning hype?- Determine the top kinds of Generative AI use cases for organizations- Learn about the next wave after the quick-win use cases (generation, summarization, coding, …)?- Prepare for the biggest challenges that AI leaders faceListen to the full episode to hear how you can:- Address leaders’ exaggerated AI enthusiasm and pessimism- Get key results from long-running Fortune 1000 data & AI survey - Learn how Generative AI can support healthcare staff with compassionate medical notes- Manage expectations with a realistic and pragmatic mindsetWatch this episode on YouTube:https://youtu.be/wZc8HaSWw-sQuestions 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, Elizabeth M. Adams (Leader of Responsible AI) and Andreas Welsch discuss increasing engagement in Responsible AI programs. Elizabeth shares findings from her doctoral research on responsible AI engagement in Fortune 10 companies and startups. She provides valuable insights for listeners looking to create effective responsible AI programs within their businesses.Key topics:- Evolution of responsible AI in times of Generative AI- Common barriers to creating an effective responsible AI program- Leadership approach to increasing employee engagement and participation in responsible AI programs- Navigating conversations with employees when their jobs are affected by AIListen to the full episode to hear how you can:- Develop a responsible AI vision for the organization- Make the vision concrete through AI ethics statements- Ensure employees are aware of AI ethics policies and how they relate to their work- Provide a path to raise stakeholder claims and build trust that claims are addressedWatch this episode on YouTube:https://youtu.be/o7ygYzN6GBEQuestions 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, Bernard Marr (Futurist & Author) and Andreas Welsch discuss preparing for a future of converging technologies and AI. Bernard shares his insights on the next wave of AI-driven innovation and provides valuable examples for listeners looking to seize opportunities across their business when data, AI, mixed reality, and many more capabilities come together.Key topics:- Learn about the next wave of Generative AI-driven innovation- Hear how modalities, agentic AI, and other technologies converge in the near and distant future- Seize the opportunity for business leaders in traditional industries- Prepare today to set your business up for future success in this environmentListen to the full episode to hear how you can:- See the opportunity of AI for different modalities coming together (e.g. text, audio, video)- Envision the future of your business and what role AI plays in enabling that strategy- Focus on humans and how technology can empower them- Communicate clearly and openly while embracing learning and changeWatch this episode on YouTube:https://youtu.be/30YZejRr2awQuestions 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, Sadie St. Lawrence (Founder of Women in Data & Human-Machine Collaboration Institute) and Andreas Welsch discuss how leaders can empower women to thrive in Data & AI. Sadie shares her story in data and data science and provides valuable tips for listeners looking to increase overall diversity on their teams in an age where AI needs to serve us all.Key topics:- Understand the tech industry’s gender gap- Identify inhibitors for women’s career growth- Learn how leaders can support women in data & AI- Foster collaboration across diverse teams and backgroundsListen to the full episode to hear how you can:- Shape organizational culture and lead by example- Understand how in-group and out-group behavior influences engagement- Speak up even if you are in a minority group- Provide space and opportunities for female team membersWatch this episode on YouTube:https://youtu.be/ffKFsRwEfIkQuestions 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, Anthony Alcaraz (Chief Product Officer) and Andreas Welsch discuss supercharging your Retrieval Augmented Generation (RAG) application with a knowledge graph. Anthony shares his experience expanding Generative AI applications and large language models and provides valuable tips for listeners looking to get even more relevant results from their AI applications.Key topics:- Identify shortcomings of Retrieval Augmented Generation (RAG)- Describe a knowledge graph and its purpose- Learn how to build a knowledge graph- Clarify when to use a knowledge graphListen to the full episode to hear how you can:- Provide context between data sources with a knowledge graph- Gather and prepare qualitative data to build your knowledge graph and AI model on- Treat knowledge graphs as one concept among others in your AI strategy- Start with the business problem and identify the best data sources and methods for solving itWatch this episode on YouTube:https://youtu.be/OSj08YBdQrgQuestions 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