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Generative AI and Business Technology

Leading with AI: The Power of AI

On May 7, the Digital Data Design Institute at Harvard hosted Leading with AI: Exploring Business and Technology Frontiers. The conference featured a presentation on the power of AI from Ewa Duerr, Head of Product Management for Google Cloud Artificial Intelligence. Based on Google’s extensive research and development in the AI space, Duerr outlined trends […]

Leading with AI: Co-Intelligence

On May 7, the Digital Data Design Institute at Harvard hosted Leading with AI: Exploring Business and Technology Frontiers. A key speaker at the conference was Ethan Mollick, an Associate Professor at the Wharton School of the University of Pennsylvania. Mollick spoke about AI’s disruptive impact on work and business, its rapid advancements, and how […]

Leading with AI: AI Regulation

On May 7, the Digital Data Design Institute at Harvard hosted Leading with AI: Exploring Business and Technology Frontiers. During the conference, a panel moderated by Mitchell B. Weiss, Richard L. Menschel Professor of Management Practice at Harvard Business School, panelists Anita Lynch, Board Member at Nasdaq U.S. Exchanges, Jonathan Zittrain, George Bemis Professor of […]

Insight: Common Generative AI Misconceptions and How to Demystify Them

Owing to the accelerated advancement in the field of generative AI technologies, it’s important to address misconceptions about what generative AI tools can and cannot do in order to maximize the benefits and minimize potential harms. In this “Ask me Anything” session, Amanda demystifies some of the most commonly held misconceptions about generative AI via discussions of real-world use cases. While responding to specific questions, Amanda highlights areas in which generative AI seems to thrive, while she also identifies notable shortcomings of the technology by drawing from her diverse and extensive experience as a digital transformation expert and a sought-after advisor to leading organizations in artificial intelligence and machine learning technologies.

Insight: Integrating Generative AI Within Organizational Systems Comes With Challenges. Here Is Why Businesses Should Still Invest In This Space, Now More Than Ever

Following the abrupt uptick of generative AI innovation in the past couple of years, organizations have ramped up research and development efforts to meaningfully explore the value of integrating generative AI into organizational systems, with a particular interest in achieving operational hyper-efficiency. This effort requires a deep understanding of the steps towards operationalizing generative AI—from development to adoption to deployment—involving benefits and risks that must be carefully considered to augment performance and financial gains. 

Scaling AI Applications in Digital Health

Insights from the January 31st, 2024 session on Gen AI use cases in the Digital Health sector In the third session of the Generative AI in Healthcare series, speakers Nikhil Bhojwani (Recon Strategy) and Satish Tadikonda (HBS) provided a thought-provoking overview of the current digital health landscape, followed by an engaging panel discussion led by […]

The Eco-Digital Era: The dual transition to a sustainable and digital economy

The Digital Value Lab at Digital Data Design Institute, in collaboration with Capgemini Research Institute, unveils a joint research initiative poised at the intersection of innovation and value creation in the burgeoning eco-digital economy. This comprehensive research paper navigates through the transformative impact of generative AI, digital twins, edge computing, immersive technologies, quantum computing, and […]

Scaling Generative AI in the Enterprise – A Fireside Conversation with Bratin Saha

Since the launch of ChatGPT, GenAI has taken center stage, prompting business leaders to explore its potential for creating value. In a recent stimulating discussion featuring Bratin Saha, Iavor Bojinov, and Edward McFowland III, the conversation delved deep into the radical potential of GenAI and its seismic impact on businesses.

From Data to AI: Maximizing Organizational Value Through Effective Operating Models

The following insights are derived from a recent Assembly talk featuring Samir Sharma, the CEO of datazuum.  

In this talk, Samir emphasizes the importance of connecting data strategy with business objectives via a detailed discussion of operating models, which are structured frameworks or organizational approaches that govern how an organization manages and utilizes its data analytics and related processes. Samir draws from his expertise in organizational psychology to highlight the challenges organizations face in embedding data and analytics into their core practices and considers the critical role of talent, systems, processes, and upskilling in building a successful operating model.

See table for a summary of the five types of operating models Samir discussed in this talk along with the advantages and challenges that come with adopting each model in a business setting.

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