Article

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. 

The Digital Data Design Institute at Harvard’s Startup Foundry launched in 2023 to support and activate academic-led entrepreneurship at Harvard. Like all good entrepreneurs, it began with experiments, testing various formats, processes, and programs, piloting with early customers and tweaking to meet market needs while producing an MVP. As the first program of its kind […]

The digital and sustainability paths, previously considered to be parallel, are now highly intersecting and reinforcing each other, pointing towards a symbiotic relationship between technological advancement and environmental values. Showcasing this relationship, digital technologies are expected to contribute more than one-fifth, and up to one-third, of the GHG emissions reduction required by the Paris Agreement by 2030, illustrating their importance to sustainability transformation. As such, it’s important to understand the main drivers of this shift because of the implications this shift has on the global business landscape, including the demand for businesses to prioritize integrating digital innovation with sustainable practices. With the eco-digital economy including benefits that extend well beyond improvement in core business activities, it’s imperative for leaders to have a vision for digital transformation at their organizations going forward with a focus on harnessing the opportunities created by the emerging eco-digital economy including digital strategy, cybersecurity, sustainability, and more. 

Understanding AI product management has become more crucial than ever, particularly in light of recent advancements in the spaces of AI and Machine Learning technologies punctuated by the proliferation of generative AI models. Considering the speed with which AI is becoming pervasive, having a strong grasp of AI concepts and frameworks is critical especially for aspiring AI product managers without significant technical (e.g., coding) background. This opens up exciting opportunities for non-technical product managers whilst making the field of AI product management more accessible, which is a precursor for innovating and building groundbreaking products that address complex, real-world challenges through leveraging cutting-edge technology. Product managers may have to unlearn things they learned in the past. It requires a new mindset.

Launched in November 2023, the Digital Data Design Institute at Harvard’s Startup Foundry supports Harvard’s academic-led innovation in AI and digital business, offering the necessary business and technical guidance to turn research projects into thriving ventures. Among the inaugural cohort for the Foundry was TeamBirth. Initially a program under the Delivery Decisions Initiative at Ariadne […]

Work, the workforce, and the workplace is subjected to constant disruption primarily as a result of advancements in technology. Weather it is the impact of robotization to manual work or the disruption of knowledge-based work as a result of software-enabled innovation, career values are being redefined to accommodate for the evolving nature of work. This begs many questions, most importantly, the short and long-term implications of such advancements in technology to the concept of work as we ‘used’ to know it and by extension the values we associate with our careers. Using a novel data of resumes from 16 million individuals in the United States, this research study shades light on the existential question of technological disruption to the labor market and impact on career values.

Large language models (LLMs) released for public use incorporate guardrails to ensure their output is safe, often referred to as “model alignment.” The study presented by Chirag Agarwal Private: Chirag Agarwal , Suraj Srinivasan Suraj Srinivasan , Himabindu Lakkaraju, Aounon Kumar, and Aaron Jiaxun Li, along with University of Maryland colleague Soheil Feizi, investigates a […]

How will the release of generative AI tools affect freelance jobs that require different skills or software? Research from Ozge Demirci Ozge Demirci , along with colleagues Jonas Hannane from the German Institute for Economic Research and Xinrong Zhu from Imperial College Business School, examines the impact of generative AI technologies like ChatGPT and image-generating […]

Can market research be done effectively with a synthetic market? This research from Ayelet Israeli Ayelet Israeli , along with Microsoft colleagues James Brand and Donald Ngwe, presents a comprehensive study on the application of Large Language Models (LLMs) like GPT-3.5 in market research. It explores the extent to which these models can simulate consumer […]

There is a growing belief that scalable and low-cost AI assistance can improve firmdecision-making and economic performance. However, running a business involvesa myriad of open-ended problems, making it hard to generalize from recent studiesshowing that generative AI improves performance on well-defined writing tasks. Research from Rem Koning Rem Koning and Rowan Clarke, along with colleagues […]