The Motivation Behind Professor Jim Samuel’s AI ROI Research

Artificial Intelligence may be the buzzword of our decade, but how many businesses can truly say they’re seeing measurable returns from it? That question has fueled countless boardroom debates, and it’s exactly what inspired Professor Jim Samuel’s groundbreaking research into the real ROI of AI.

Professor Jim Samuel is the Executive Director of Informatics Programs at Rutgers University and an academic thought leader in artificial intelligence, data science, and information systems. With extensive research in AI innovation, ethics, and economics, Professor Samuel focuses on understanding how businesses can responsibly and effectively extract value from AI technologies.

He joined our recent webinar, “Beyond the Hype: The Real ROI of Generative AI in the Future of Search,”  to break down different aspects of the research with our very own CEO Udayan Bose.

The Inspiration Behind the Research

When asked about what inspired his latest academic research into AI ROI, Professor Samuel shared that his motivation came from bridging the gap between AI’s excitement and its economic reality.

Although AI has gained immense popularity, he explained that “interest does not translate to correct knowledge.” In fact, early research revealed that roughly 95% of AI initiatives were failing, sometimes after millions of dollars were invested.

The Problem: Success Without Value

The issue wasn’t that the AI systems weren’t working, but rather that they weren’t delivering measurable business outcomes. Coming from a finance background, Samuel wanted to explore why this was happening. Academia often celebrates algorithmic breakthroughs, but in business, value creation is the ultimate measure of success.

Defining the Goal: Economic Accountability in AI

His goal was to uncover what distinguishes companies achieving positive AI ROI from those struggling to see returns. This foundational work has set the stage for a more data-driven understanding of AI success, one that emphasizes not just innovation, but the economic accountability behind it.

Professor Samuel’s ongoing work seeks to define what economic accountability in AI truly means and how organizations can measure it. His framework emphasizes:

• Strategic problem definition before applying AI tools
• Budget allocation for experimentation and iterative testing
• Outcome-focused measurement tied to real business goals
• Risk assessment, ensuring AI systems enhance trust and reliability

As Udayan Bose added during the session, many brands are now realizing that AI alone isn’t the answer.  AI guided by clear intent and experimentation is.

Balancing Innovation with Human Insight

Both Samuel and Bose agreed that while AI is a powerful innovation driver, it also carries ethical, operational, and reputational risks. Professor Samuel likened it to “a sword hanging over AI implementations.” Companies are becoming better at safeguarding outputs and monitoring risks, but he emphasized that human oversight remains essential.

The key, he suggested, is not to fear AI’s unpredictability, but to approach it with structured curiosity, transparency, and a commitment to learning.

A Continuing Journey

Professor Samuel’s research represents the first step in a longer investigation into how organizations can separate AI hype from real, measurable value. As the world moves toward conversational and agentic AI systems, his work provides a timely framework for leaders seeking to invest wisely, ensuring that technological progress aligns with long-term business growth.

Download the Full Research Paper

Get the complete findings from Professor Jim Samuel’s study and uncover the full framework for assessing AI ROI.