Finance, Technology & Investments — Foreword

Former Director of the Joint Artificial Intelligence Center | Advisory Board, American Society for AI (ASFAI) | Founding Partner, Global Frontier Advisors

Stepping up the foundational ladder of AI: 'Making it Real' in a New Economy, a new Prosperity and a new Investment framework; Finance, Infrastructure, Abundance and the human/machine partnership for broad prosperity.

AI's impact on our social constructs, our ethical boundaries and our educational standards are emerging and growing in maturity and power. It is a wonder to watch as our baseline understanding of the appropriate relationships between machines and humans continues to grow. Finance, Technology, and Investments serve as core application environments that deserve our immediate attention. If we have built (and continue to grow) the necessary protections for our society, we must also pay attention to the foundations of our security and prosperity as well.

We need to ensure that we are protecting and carefully extending our technological reach into the underpinnings of our economic structures, our perceptions of wealth creation, and integrating the value of AI into every strata of our economic activity. It is in these areas (Finance, Infrastructure, and Investments) that we have the opportunity to accelerate broad prosperity, ensure protections, drive technological enablement and grow the core of human abundance. Here we find the opportunity for the lifting of not just the few, but the many. There is nothing more exciting than mapping out the broad prosperity and human satisfaction that our relationship with our machines can enable.

It is the integrative nature of these technologies that serve as the ideal bedrock for moving into broader economies, technologies and financial activities. We have already seen broad applications in mobile payments, open markets, and globalization of trade enabled by safe, protected technologies. Importantly, we have also seen the impact of poorly imagined or poorly constructed failed efforts. Remediating the things that do not work in this new era is as important as imaging the workings of the new. Today, artificial intelligence, ubiquitous connectivity, and the Internet of Things are rapidly gaining ground on these foundational technology areas. The same data that moves through payment rails, credit systems, and capital markets now flows from sensors and devices embedded in critical infrastructure, logistics networks, and everyday environments. Finance is now bound to the digital and physical systems it funds, secures, and guides.

Humanity always comes first. It is not wrong for us to focus on people, children, relationships and those things that underpin our selves, our relationships, and our empathy. But the most exciting steps we will take may be those that begin to broaden our human convenience, economic well-being and safety into our foundational existence. We have to build the broad economic and technical underpinnings of the new abundance, entirely guided by human values. This Finance, Technology & Investments component of AI for Humanity lives at that intersection. The chapters here ask simple questions with complicated consequences. What happens when AI-driven finance operates inside IoT-rich, cyber-physical systems, and who is responsible for what follows? How do we imagine and engineer broad prosperity by thinking globally about the fiscal environment, the physical resource environment, and our trust in human-machine systems?

For leaders, this is not theory. AI-enabled risk models already ingest high-frequency telemetry from IoT networks. Portfolio and trading decisions increasingly respond to real-time signals from supply chains, energy grids, and transportation systems. National power is being reshaped around data infrastructure, compute, and intelligent networks. This progress rests in a foundation of human trust and vision for future prosperity for all, especially those who do not enjoy it today. We are wise to understand the foundational risk aversion of most humans and their general unwillingness to let go of the shore when they cannot see beyond the horizon. In a technological chapter, the core elements of our humanity remain our strongest influence. We may wish it were not so, but we must engineer solutions that bring us all along.

There is also a more foundational question that sits beneath these obligations. As artificial intelligence becomes embedded in financial systems, infrastructure, and national capability, questions of authority and accountability become unavoidable. LtGen Eric Wesley's contribution highlights a critical tension. Corporations play an essential role in innovation and stewardship of advanced technologies, but they do not carry democratic legitimacy. Decisions about how AI is applied in matters of national security and public safety must ultimately remain with democratically accountable governments. In a world where private innovation increasingly shapes public capability, preserving this distinction is essential to maintaining both trust and stability.

That reality creates several obligations.

First is trustworthiness. As Amyn Jan's work on AI assurance shows, institutions need more than a checklist. They need ongoing frameworks that continuously validate transparency, robustness, ethics, and accountability in human-machine systems. In an IoT-enabled financial stack, where sensing, decision, and action can occur in milliseconds, assurance is an operational discipline, not a report on a shelf.

Second is resilience. Saxon Knight's call for "secure by design" is direct and correct. In an AI-accelerated, hyperconnected environment, security cannot be an afterthought. When financial decisions depend on IoT-driven operational data, a weakness in one network can create systemic risk in another. Cyber resilience becomes essential to maintaining trust in both the financial system and the infrastructure that supports daily life.

Third is inclusion and long-term value. Several chapters in this part probe how generative AI can move beyond short-term hype. They look at sustainable business models, the need for AI literacy at the executive level, and ways AI-enabled finance can support broad-based human development instead of deepening concentration and fragility. In an IoT world, where data is collected from streets, factories, and homes, questions about who benefits, who is exposed, and whose values are embedded in algorithms cannot be ignored.

The core message of this part is straightforward: AI in finance is no longer just about efficiency gains or marginal improvements in returns. It is about how intelligence embedded in capital markets and IoT-enabled infrastructure can either harden existing vulnerabilities or strengthen systems for the long term. That connects directly to the rest of AI for Humanity: ethics, education, and policy are not side issues. They are prerequisites for deploying AI in finance and cyber-physical environments in a way that serves people first. In doing so, we must remain clear about where responsibility ultimately resides, ensuring that decisions affecting public safety and national security remain anchored in accountable public authority.

For leaders working at the intersection of finance, AI, and IoT, the invitation is clear. Treat intelligence at the edge as both an opportunity and a responsibility. The choices made now about how we design, fund, and govern these systems will shape economic resilience, security, and fairness for years to come.