AI in R&D for life sciences is transforming drug targeting, patient recruitment, and regulatory compliance. Advancements in AI-enhanced protein structure prediction are revolutionizing the industry. The impact of AI on drug discovery, clinical trials, and regulatory functions is discussed, highlighting the potential for innovation and efficiency in the pharmaceutical field.

In this podcast, Jennifer Bradshaw and Arash Kamiar from NLP Logix discuss the importance of a 'product mindset' when developing AI solutions. They emphasize understanding customer problems, agility, and stakeholder involvement. The conversation explores using the Socratic method for AI implementation and prioritizing workflow solutions over technology development.

Dr. Dan Elton from Mass General Brigham discusses AI in healthcare, covering radiology, compliance, and medical record generation. They explore how foundational models will revolutionize AI in radiology and highlight promising use cases in healthcare such as automating billing codes and transcription processes.

Bhuvanesh Abrol, US Private Equity Consulting Leader at Deloitte, discusses the AI opportunities in private equity investment decisions and deal-making. They explore the power of AI in analyzing unquantifiable data, summarizing financial data, and understanding market trends. The intersection of decision-making in private equity and AI is highlighted, emphasizing the need for relevant data. Challenges in analyzing financial information for private equity firms and the potential benefits and hurdles of implementing AI are also discussed.

Melissa Easy and Vinita Navadgi of IQVIA discuss the advantages of automating consent workflows in healthcare through eConsent processes. They delve into the metrics defining its effectiveness, highlight the role of AI in shaping clinical trials, and explore the potential of using AI tools to personalize consent-related content for better patient outcomes.

Mark Miller, Managing Director of Life Science Advertising, Marketing & Commerce at Deloitte, joins the podcast to discuss leveraging data in AI use cases in pharmaceutical sales and marketing. He emphasizes the importance of connected data and decision algorithms to engage with healthcare professionals effectively. Topics include challenges in the life sciences field, the impact of AI and data on marketing and sales, adapting strategies in life sciences, and applying Gen AI in the pharmaceutical industry.

John D’Angelo, Real Estate Solutions Leader at Deloitte, discusses challenges in real estate industry, including slow adoption of technology and resistance to change. He explores potential of AI in leasing process to streamline creation of complex leases and mitigate risks. Importance of storytelling and local knowledge in real estate emphasized. Conversation also touches on ROI in legal document creation, potential of AI in contract creation, and challenges and trends in real estate innovation.

Ciprian Porutiu, VP of Operations and Strategy at Marsh McLennan, discusses the challenges of scaling systems in the VUCA business landscape. The importance of business agility, transparency, and quick feedback cycles in customer experience development are emphasized. The application of the dynamic of sandwiching in user experience and navigating compliance governance and business agility in a volatile environment are also explored.

Sreekanth Menon, VP and Global Leader of AI/ML Services at Genpact, discusses responsible AI practices and data governance policies. He emphasizes the importance of reliability, security, autonomy, accountability, and traceability in AI models. The podcast explores the use of prompts and structured approaches in generating AI models, and highlights the significance of responsible AI in highly regulated industries like finance and healthcare.

Steve Astorino, Director of the Canada Lab and VP of Development in Data and AI at IBM, discusses the challenges and misconceptions in generative AI, addressing the skills gap in utilizing emerging technologies in enterprises, challenges and governance in enterprise data and models, and the intersection of data governance and AI ethics.