Aditya Saharia

Bio:
Dr. Aditya Saharia is a professor of Information Systems at the Gabelli School of Business, Fordham University. He serves as the Director of the Gabelli School’s Center for Digital Transformation and is the Coordinator of the Fordham CIO Roundtable, a platform that brings together senior IT leaders to discuss emerging challenges and opportunities in digital innovation.

Professor Saharia’s research focuses on the strategic and operational applications of AI systems, information systems strategy, data engineering, and service center management. His recent projects include work on AI-enabled applications, data visualization for healthcare data breaches, alignment of IT and business through data engineering, and the design of incentive-compatible contracts in digital ecosystems. He has also investigated IT integration challenges in mergers and acquisitions.

At Gabelli, Dr. Saharia teaches undergraduate and graduate courses in IT strategy, IT project management, e-commerce, and enterprise integration. His work bridges academic rigor with real-world impact, making him a key contributor to the evolving dialogue on responsible and effective digital transformation.

Abstract:
The rapid advancement of Artificial Intelligence (AI), especially Generative AI, is transforming labor markets, productivity, and patterns of value creation across sectors. This talk critically examines the implications of these developments for the future of work, focusing on job displacement, global inequality, and the ethical responsibilities surrounding AI deployment.

Forecasts about AI’s economic potential vary widely. Goldman Sachs estimates that generative AI could raise global GDP by up to 7% over the next decade. However, economist Daron Acemoglu offers a more cautious view, projecting less than 1% growth in total factor productivity over the same period. These contrasting estimates reflect deeper uncertainty about AI's adoption, sectoral impacts, and the capacity of institutions to adapt.

At the same time, job displacement is emerging as a central challenge. Generative AI is expected to automate substantial portions of knowledge-based work—particularly in content generation, customer support, and administrative roles—while offering fewer gains to lower-digitized sectors and economies.

The global digital divide further complicates the distribution of benefits. AI innovation is dominated by the United States and China, while much of the Global South lacks the digital infrastructure and institutional readiness required to implement these technologies at scale. Without targeted investment, this imbalance could exacerbate existing global inequalities.

Additionally, a recent MIT report reveals that only 5% of firms investing in generative AI report a measurable return on investment. This points to a growing gap between AI’s potential and its realized impact—underscoring the need for more deliberate, inclusive, and responsible AI strategies that prioritize both equity and long-term effectiveness.