AI & Future of Business Technology

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.