In today’s business landscape, the most pressing question facing organizations is no longer whether to adopt artificial intelligence, but how to do so—and just as critically, how not to. As leaders search for answers to this defining 21st-century challenge, many find themselves stalled, overwhelmed by complexity, hype, and uncertainty. Without the guidance of credible AI leaders such as Malay A. Upadhyay, many organizations might have remained trapped in this paralysis far longer. Instead, under his influence, leaders are learning not only how to answer the AI question—but how to engineer a meaningful turnaround.
As Chief Operating Officer (COO) of SalesChoice, an award-winning AI SaaS and consulting firm, and a Board Advisor & Masterclass Trainer in AI at the United States Artificial Intelligence Institute, Malay occupies a unique dual role. On one front, he drives organizational growth and advises enterprise and public-sector clients across industries. On the other, he trains senior executives worldwide on navigating AI transformation journeys. His work is further informed by early involvement with the European AI Alliance, which contributed to shaping the European Commission’s first AI policy in 2019.
Malay’s contributions have earned him the Global Icon Award from Corporate Connect and recognition as one of the Most Influential Business Leaders to Watch by CEO Time Magazine, as well as one of the Top 10 Pioneering Business Leaders by Mirror Review.
An author and educator, Malay has written and published four books on artificial intelligence—in addition to two fiction titles centered on evolving techno-economic paradigms—and developed three educational courses. He has trained more than 2,000 business leaders across organizations such as CGI India, Compass Group Japan, World Financial Group, the U.S. Navy, Reckitt Europe, Services Australia, and more. Through this work, thousands of leaders have gone on to make better-informed AI decisions using the managerial frameworks he advocates.
AI as a Leadership Discipline
What distinguishes Malay’s career is how seamlessly it bridges enterprise leadership, AI education, and global policy influence. Over years of experience, he has arrived at a perspective that challenges conventional thinking.
“AI is often treated as a technical problem,” he explains, “something to be solved through engineering alone.” Yet only about 20% of an organization’s workforce is involved in developing AI solutions. The remaining 80%—non-technical professionals—play the more decisive role as users, investors, and decision-makers. “That realization is what compelled me to position AI not merely as a technology, but as a leadership discipline.”
This insight was shaped by several pivotal moments. Chief among them was witnessing firsthand how managerial blind spots and knowledge gaps consistently undermined returns on AI investments. Leaders struggled not because the technology was weak, but because there was no structured frameworks for them to drive the managerial side of AI journeys. Nearly all available education focused on the technical minority building AI tools, leaving decision-makers unequipped.
The final turning point came with a broader realization: the future of AI—and “the sustainability of socioeconomic systems in a world shaped by safe and responsible AI”—depended on whether this other 80% understood AI well enough to make informed, ethical decisions. That understanding became the foundation of Malay’s work: creating content that was practical, accessible, and immediately applicable.
Redefining AI Transformation
As a Masterclass Instructor for the Certified AI Transformation Leader Program, Malay challenges executives who initially view AI transformation as a simple technology upgrade. He argues that a mindset shift is the true starting point for becoming AI-ready.
Case studies, he finds, are particularly effective. They reveal where AI initiatives succeed or fail—often independent of the sophistication of the technology itself. In one instance, weak AI governance protocols exposed an organization’s intellectual property and customer data. In another, a company lost millions after being misled by a seemingly “99% accurate” AI model. Conversely, he has also seen an organization recover millions by predicting profits and prioritizing customers without relying on revenue or cost data.
By unpacking such stories, executives move beyond abstract potential and begin to understand what it genuinely takes for AI to solve real business problems.
Correcting Global Misjudgments
Through extensive work with global enterprises and public-sector institutions, Malay has identified a consistent pattern in failed AI initiatives: a misjudgment of organizational readiness.
“AI readiness rests on talent, data, and process readiness,” he explains. Talent readiness, in particular, starts at the top. Leaders often underestimate the level of understanding required to decide whether to use AI, where to apply it, and when it adds value.
Equally important is helping people understand why AI is the right solution to their everyday problems—and what AI requires from them to function effectively. Without early clarity on governance, strategy, usage policies, and business use cases, the probability of success declines sharply.
Balancing Innovation with Ethics
Malay’s work in AI policy and advisory boards reflects a rare ability to integrate innovation velocity with ethical responsibility. To him, the two are inseparable.
Innovation, he argues, is ultimately justified by longterm returns. Without an ethical lens, those returns are rarely sustainable. “This isn’t about balancing opposing forces,” he notes. “It’s about using ethical responsibility as a mechanism to guide, de-risk, and sustain innovation.”
The AI-Transformed Leader
After training thousands of senior leaders worldwide, Malay draws a clear distinction between AI-aware and AI transformed leaders. The difference lies in experience.
“AI-aware leaders understand the importance of AI and want change. AI-transformed leaders have already translated that understanding into tangible business outcomes.”
It is this experience that enables the latter to scale AI adoption successfully, having navigated both its benefits and its limitations in real organizational contexts. This philosophy also explains why Malay emphasizes managerial frameworks—many that he created—over technical prescriptions.
Today, roughly 80% of AI initiatives fail to deliver healthy ROI—a figure that rises to 95% in a 2025 BCG report. “Is this because organizations lack good developers or tools? No.” Failures stem from leadership mindset and governance choices, not technical shortcomings. That reality underscores why learning how to lead AI journeys matters at least as much as learning the tools themselves.
Rethinking Ownership and Accountability
As AI reshapes customer experience, operations, and strategy simultaneously, Malay believes leaders must rethink ownership and accountability. Both are shaped by both organizational structures and the jurisdictions companies operate in.
The regulatory environment is currently in flux as lawmakers attempt to balance competitive realities with perceived risks. So, for C-suite leaders, staying informed is the first step toward compliant governance and risk mitigation.
While many organizations have introduced a Chief AI Officer to centralize accountability, Malay views this as transitional. As AI becomes ubiquitous, ownership will increasingly reside across functional leadership—much as computing did over time. “It would be unthinkable today to have a Chief Computer Officer, wouldn’t it?” Structural change, he argues, is inevitable, as AI does not operate in silos, even though organizations often still do. “There will be a broader reimagining of organizational structures. Organizational design responds to managerial needs, which in turn are shaped by foundational technologies, as they have since the era of Henry Ford.”
Guiding Leaders Overcome Resistance
In classrooms and advisory settings, Malay frequently encounters resistance rooted not in fear of technology, but in fear of irrelevance.
The World Economic Forum’s Future of Jobs report in 2020 estimated that AI would displace 85 million jobs—a figure revised to 97 million in 2025. “What receives far less attention is the counterpoint,” Malay points out, “Job creation estimates rose from 92 million to 170 million over the same period.”
“Fear of displacement is understandable,” Malay acknowledges, “but it is often amplified by sensational narratives.” Education, he insists, is the antidote.
When leaders learn how AI actually works—by building automations and understanding its limits—the fear diminishes. Clarity replaces anxiety, and confidence follows, as they learn what steps they can take to remain relevant in the AI era.
Preparing for Disruption—and Beyond
Looking ahead, Malay expects the AI industry and broader economy to undergo a correction consistent with historical techno-economic cycles. Growth will be uneven, marked by disruption before stabilization.
In these moments, leaders who can stabilize their organizations and extract outsized value from constrained resources will define the next era. Leaders must understand AI capabilities deeply enough to prioritize the right use cases, estimate true costs (direct and indirect), and evaluate outcomes using appropriate measures—system robustness, scalability, sustainability, model performance, and business impact. These capabilities will define credible leadership in the AI era.
Sustainable Training
AI conversations often focus on future potential. Based on what he sees today, Malay believes the most important decision leaders can make is to train their workforce on AI.
Sustainable training must focus on simple, relatable, and practical knowledge that embeds itself into organizational muscle memory—rather than overly technical content that is difficult to apply.
Without this foundation, organizations cannot implement AI incrementally or learn fast enough to generate healthy returns. Early on, long-term leaders should focus less on which AI investments to make and more on teaching leaders how to decide which AI investments are worth making.
Shaping the Next-Gen AI-Transformation Leaders
As someone shaping the next generation of AI transformation leaders, Malay believes educators and institutes like USAII carry a crucial responsibility in influencing how AI power is distributed globally. Institutions play a pivotal role in shaping AI transformation leaders and enabling AI-driven organizations. The content they offer—and the audiences they reach—has a profound impact on how responsibly and equitably AI knowledge is distributed worldwide.
These institutions help learners demystify AI, mitigate fear, prepare for risks, and build managerial frameworks that endure beyond any specific tool. This responsibility must be exercised in an unbiased and ethical manner, because what leaders learn here shapes how AI will be built and governed in the future.
“This belief is what led me to launch ClassesAI.com—to give learners access to AI education that aligns with their time, budget, skills, and learning preferences.”
The Ultimate Goal
Finally, looking toward the future, Malay’s primary aim remains what it has always been: to make AI understandable and accessible to non-technical professionals, enabling them to move beyond fear and take control of how AI shapes their organizations and society.
The ultimate goal is to help leaders influence AI’s evolution in ways that are responsible, ethical, and sustainable. “If future leaders feel better prepared to lead, adapt, and thrive in the AI era—in their careers, their organizations, and their society—because of the foundations we built together, I would consider that goal fulfilled,” he concludes.
