Quantum AI: Is This Humanity’s Most Consequential Innovation?

Originally published in Forbes Book Author Post, April 2026(opens in new tab)

Nearly 50 years ago, in 1979, I sat in a classroom on the beautiful campus of Rollins College in Winter Park, Florida. I was in my final year at Rollins before starting the second part of a five-year dual-degree program at the Georgia Institute of Technology (Georgia Tech) in Atlanta. At Rollins, my three-year focus was physics, and, ultimately, my two-year focus, excluding grad school at Georgia Tech, was Electrical and Computer Engineering. 

The most memorable class at Rollins was P451, Quantum Physics, because it was both challenging and fascinating, revealing mysteries of this advanced science. Each day, my curiosity led me to ask myself what I would ever do with any of this knowledge. The book used for the class was “An Introduction to Quantum Physics” by A. P. French and Edwin F. Taylor. It still sits on the shelf of my home office, and I shake my head each time I look at it. 

Quantum physics, also known as quantum mechanics, is a branch of physics that explains how nature operates at its most fundamental levels, including the behavior of atoms, electrons, and photons. It may not be evident to most of us, however, that quantum physics is the foundation for much of modern technology, including semiconductors used in every electronic devices such as computers, smartphones, and household appliances, as well as in automotive applications, optical devices like lasers, and healthcare products like MRI machines; it is also fundamental to the emergence of quantum computing because these new quantum systems will use the principles of quantum physics to process information beyond the capabilities of today’s classical computers.

My final reflections on this quantum physics class centered on learning about Erwin Schrödinger, an Austrian physicist and one of the founding figures of quantum mechanics, and the magnitude of the Schrödinger equation. Still, I didn’t fully appreciate it until recently, mainly due to the hype surrounding the promise of quantum computing. Much like the well-known Newton’s law, which explains the motion of objects, it describes how the state of a quantum system evolves. The Schrödinger equation is the mathematical foundation that explains the behavior of small particles, predicting their wave-like properties and their evolution over time.1 It applies to quantum computing because it describes how the three foundation pillars work in delivering an exponential increase in computing performance: Qubits which stands for quantum bits, the basic unit of quantum information; Superposition, the ability of a qubit to simultaneously represent multiple states unlike a bit’s 0 or 1 in today’s binary systems; Entanglement, the ability of qubits to become interconnected so that the state of one can influence the state of another, independent of the distance. The opportunity for these systems is to achieve an order-of-magnitude reduction in the time required to solve complex problems. These systems today have demonstrated an advantage for specific tasks, running some tasks one thousand to one million times faster than the best-known classical methods.2 

“For specific problems, quantum computers don’t just incrementally improve the speed; they change the scale of problem-solving altogether.”3 The tasks best suited for quantum computing are those that are highly complex, optimization-heavy, quantum-native, security-sensitive, and data-intensive, in other words, solving problems that become too big, too complex, or too subtle for today’s classical AI systems. Just imagine being able to simulate entire molecules to discover new medicines, simulate neural networks of extreme complexity, or break current encryption while enabling new, unbreakable forms of security. In the world of distribution and logistics, imagine a day in the future where companies could instantly optimize their entire supply chains on a global scale. 

“Like most transformative technologies, the success of quantum computing will depend not only on inventors, physicists, and engineers, but also on entrepreneurs, investors, designers, teachers, and decision-makers who can help shape how the technology is developed, commercialized, and governed.”4 Studies estimate that quantum computing will continue to advance, unlocking an estimated $2 trillion in economic value by 2035.5 Quantum systems are being built by a mixture of large traditional technology companies, numerous early-stage companies and startups, and various research labs. 

This race is healthy competition that fuels innovation, which will eventually impact every industry. The four industry sectors most often cited as the most significant early beneficiaries of quantum computing are finance, pharmaceuticals and life sciences, mobility (including automotive, aerospace, and logistics), and sustainability and energy. For finance, the use cases will include portfolio optimization, risk analysis, fraud detection, derivative pricing, and Monte Carlo simulations. In the pharmaceuticals and life sciences sector, the use cases will include drug discovery, protein folding, molecular simulations, and genomics. For mobility, the use cases include traffic-flow optimization, autonomous-vehicle routing, fuel-efficiency design, and supply-chain optimization. In the sustainability and energy area, use cases include battery materials, renewable energy optimization, carbon capture, and smart grid design. In each of these sectors, the case for quantum computing is that they are highly complex simulation and optimization problems that require performance faster than classical systems, at reduced cost and with improved efficiency.6 

The pace of innovation will continue to accelerate, fueled by AI. We are on a path where AI will help accelerate what may be the most consequential innovation of all time: Quantum AI. As we advance into the third era of computing, which I refer to as the cognitive cycle, systems will increasingly be defined by how they learn, reason, and interact naturally, rather than by the previous innovation cycle, where systems were primarily characterized by their programming. Quantum AI is the combination of the computational power of quantum computing with the learning and pattern recognition capabilities of AI. The integration of quantum computing and AI will bring more “life” to these systems, transforming them into a form of intelligence that is rapidly on pace to exceed human intelligence.7 Our curiosity should lead us to some profound questions: “Why?” “How?” and “What if?” that we must increasingly face, hopefully sooner rather than later. 

Due to the ever-evolving learning capacity of these systems, why wouldn’t they, over time, develop self-awareness, operate more independently, and strive to establish self-preservation mechanisms? How would we continue to operate as partners, companions, co-pilots, etc. with a non-biological entity in a world where control is potentially redefined, whose intelligence exceeds the level of human intelligence? What if there is a significant difference in the interpretation of human motivations like behavior, which is what we believe, emotions, which are what we feel, and empathy, which is how we connect? I know some of this sounds like Sci-Fi or a vast stretch of the imagination, which may be more likely. Still, the central point is that we must always ask the right questions to ensure our primary focus is on responsible outcomes and to avoid unintended consequences.

We must continue to be mindful of the rules of partnership, where humans do what humans do best, and AI continues to enhance us, making us more productive in what we do. AI excels at the information-processing aspects of human intelligence, particularly reasoning, problem-solving, and memory. Humans still dominate in emotional processing, mainly through curiosity, judgment, and relationship skills. For example, I will argue that, in meaningful relationship management, whether personal or business, “the human-in-the-loop” is always more effective because a relationship is not just computational. We have discovered that, on a relative scale, continuous innovation brings more opportunities to help humanity and improve the world, but it also introduces threats. For example, I refer to the second cycle of innovation as the Internet cycle, which began in the 1990s and gave users access to vast amounts of media and content, enabling online interaction. One of the innovations that emerged along the way was social media. The opportunity was how it connects people, creating opportunities for sharing and awareness, and empowering voices. The threats are that it can spread misinformation and become a distraction due to overuse, and that it raises privacy concerns and drives polarization, ultimately influencing behavior. Like any innovation, they require balance and responsible use.

These questions about where we may be headed with Quantum AI are designed to pique your curiosity, and I’m sure, like in the past, we will maintain our track record in delivering meaningful change and impact. Due to this potential major shift resulting from the fusion of quantum computing and AI, we may need to refer to it as the fourth era of computing: the Quantum cycle. 

1. David J. Griffiths and Darrell F. Schroeter, Introduction to Quantum Mechanics, 3rd ed. (Cambridge: Cambridge University Press, 2018), 23–25.
2. McKinsey & Company, Quantum Technology Monitor 2024 (New York: McKinsey & Company, 2024), accessed October 12, 2025, https://www.mckinsey.com/capabilities/quantum
3. Pantheon Space Academy, Quantum Computing Explained for Beginners (no place: Pantheon Space Academy, 2023), 26.
4. Quantum Index Report 2025, Quantum Index Report 2025 (New York: Quantum Insights Press, 2025), 14.
5. McKinsey & Company. Steady Progress in Approaching the Quantum Advantage: Quantum Technology Monitor, April 2024. April 2024. https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/steady-progress-in-approaching-the-quantum-advantage(opens in new tab)
6. Matteo Biondi et al., “Quantum computing use cases are getting real — what you need to know,” McKinsey (Dec. 14, 2021), 1–2, https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/quantum-computing-use-cases-are-getting-real-what-you-need-to-know(opens in new tab)
7. James Barrat, Our Final Invention: Artificial Intelligence and the End of the Human Era (New York: Thomas Dunne Books, 2013)