The New Scorecard: Measuring Trust in the Age of Enterprise AI

CHICAGO, IL – August 06, 2026

The frantic race to integrate artificial intelligence into the core of enterprise operations has created a silent but substantial liability. For every press release heralding AI-driven efficiency, there is a quiet, unmeasured risk growing in the shadows of corporate networks. The chasm between the performance of AI and the permanence of its governance has widened into a critical vulnerability. Now, a move from a new rating firm signals a foundational shift from abstract policy to accountable practice.

AIQA Global, LLC this week announced the formation of an inaugural Advisory Board, a development that, on its surface, is standard corporate procedure. But looking beneath the headline reveals a deliberate and strategic attempt to build the missing infrastructure for the AI era. The firm is not merely gathering experts; it is assembling the architects for a new standard of accountability, centered on its AIQ™ Score—an ambitious effort to quantify and rate the quality of a company’s AI governance.

A Credit Score for AI Governance

For decades, markets have relied on independent, evidence-based ratings to price risk and build trust, from credit ratings for bonds to safety ratings for vehicles. AIQA Global is betting that AI needs the same treatment. The firm’s AIQ™ Score is a 0–200 point assessment, built on 250 distinct factors, designed to provide a standardized, quantitative measure of AI governance maturity.

“Enterprise AI adoption has advanced much faster than enterprise AI governance,” said James E. Malackowski, Co-founder and Chairman of AIQA Global. “Self-attestation is not governance.” This statement cuts to the heart of the problem. In the absence of a common yardstick, companies have relied on internal policy documents—a method that, as one executive noted, is akin to letting students grade their own exams.

The AIQ™ Score aims to replace this self-reporting with a rigorous, auditable framework. The methodology is built across five key dimensions, each weighted based on its contribution to potential risk and failure: Oversight & Accountability (30%), Technical Robustness (25%), Strategic Alignment (20%), Responsible AI & Compliance (15%), and Adaptability & Education (10%). The heavy emphasis on oversight underscores a critical lesson from past technological disruptions: failures of governance, not just code, are what lead to catastrophic outcomes.

This isn’t the founding team’s first foray into quantifying the intangible. Malackowski previously co-founded Ocean Tomo, the firm that pioneered patent quality ratings and created the Ocean Tomo 300® Patent Index. That experience—turning the abstract value of intellectual property into a measurable, market-relevant metric—provides a compelling precedent for what AIQA is attempting with AI governance.

The Architects of Assurance

A standard is only as strong as the minds that shape it and the market that accepts it. AIQA’s selection for its advisory board reflects a deep understanding of this reality. The board is an interdisciplinary coalition, with each member representing a critical pillar of the emerging AI ecosystem.

• Jon Held, Chairman of J.S. Held LLC, brings the perspective of the insurance and corporate risk world. His firm consults for the majority of the Fortune 100 and top global insurers. His involvement signals that the insurance industry, which will ultimately underwrite AI risk, is seeking a reliable yardstick.

• Mike Hrabik, CEO of cybersecurity firm SecureSky, represents the front lines of digital defense. “AIQA's evidence-based standard is the only framework that focuses on verifiable proof of effective AI governance, deployment, and use,” Hrabik stated, highlighting the convergence of cyber risk and AI oversight.

• Michael Mitzenmacher, a distinguished Harvard computer science professor, provides the academic and algorithmic rigor. His interest was piqued by AIQA's transparency. “If companies cannot interrogate and understand their rating, they will not have the means to improve,” he noted, emphasizing that a black-box rating system is no better than a black-box AI.

• Albert D. Napoli, a veteran entrepreneurship professor at USC, brings the perspective of value creation and company building. His role is to ensure the AIQ™ Score is not just a risk-mitigation tool but a driver of competitive advantage and long-term enterprise value.

This assembly is not for show. It is a strategic move to embed the AIQ™ Score into the operational fabric of the institutions that matter most: insurers, regulators, corporate boards, and the technology community itself.

From Policy Documents to Market Imperatives

The timing of this initiative is no accident. The market forces demanding independent AI assurance are reaching a critical mass. Regulatory bodies, from the European Union with its AI Act to individual U.S. states, are shifting from principles to enforcement. The era of voluntary guidelines is ending, and the era of auditable compliance is beginning.

As AIQA’s Head of Product, Chase Malackowski, bluntly put it, recent AI mishaps—from models escaping sandboxes to the arrival of near-singularity claims—would not have been prevented by a simple policy document. “Boards need a score they can check and compare,” he said. This is the new fiduciary reality. A board that cannot measure its AI risk will soon be seen as negligent in managing it.

This shift creates a powerful economic imperative. A high AIQ™ Score could translate into lower insurance premiums, preferential access to capital, and a significant advantage in procurement. Conversely, a low score could become a major red flag for investors, partners, and regulators. AIQA is positioning its score not just as a compliance tool, but as a core component of enterprise valuation and resilience.

Building a Shared Language for Risk

AIQA’s strategy appears to extend beyond a single product. In a related move, James Malackowski was appointed to the advisory board of a generative AI program at Webber International University. This dual approach—creating the standard and simultaneously training the people who will use it—is crucial for building a durable market infrastructure.

Most professionals today learn AI governance on the job, resulting in an inconsistent and fragmented understanding of risk. By engaging with academia, AIQA is helping to create a common vocabulary and analytical framework for the next generation of business leaders, risk managers, and technologists.

Ultimately, the announcement from AIQA Global is more than just news of a new product or an advisory board. It is a signal that the AI industry is beginning to mature. The wild, experimental phase is giving way to a necessary period of stabilization, where trust is not merely claimed but measured, verified, and earned. For businesses seeking to build lasting value in an unpredictable world, this new scorecard may prove to be an indispensable tool for navigating the path ahead.