Frameworks and Tools
Chain of AI Accountability Framework
AI governance is a shared responsibility.
Both buyers and sellers have obligations to manage AI responsibly from inception to decommissioning. For buyers, however, PROCUREMENT is a critical point in the chain of AI accountability where technical AND ethical debt are transferred from the seller to the buyer...and new transfers occur during EVERY update, upgrade, and modification cycle.
Is your procurement strategy prepared to address the new IT lifecycle?
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Why We Use Frameworks
Our proprietary approach outperforms "DIY AI" advisory approaches any day of the week.
Grounded
Our frameworks are grounded in decades of deep empirical research, curated by experts, to ensure our concepts are sound and interconnected.
Predicable
Our frameworks are rigorously evaluated, tested, and validated by scholars and experienced professionals to ensure successful results for each unique situation.
Scalable
Our frameworks allow us to ingest complex business scenarios at scale and product meaningful results quickly with repeatable patterns of success.
Our Frameworks
The secret recipes behind our experience team.
Four Corners of
Applied AI Governance
Our Four Corners framework unifies people readiness, organizational readiness, value capture, and active oversight to transition AI from an experimental risk into a responsible, high-performance business asset.
By integrating these four pillars, executives can capture higher returns on AI investments and neutralize performance issues before they impact the bottom line, ensuring innovation is both aggressively profitable and structurally protected.
Risk Management Framework
for Procuring AI Solutions
The RMF PAIS is a systematic, six-step protocol that integrates traditional risk management discipline into the procurement lifecycle to identify and neutralize the unique, opaque risks of "black box" AI.
By establishing a rigorous risk-aware requirements development and embedding enforceable risk controls directly into contracts, executives can aggressively capture AI’s efficiency gains while structurally safeguarding their organization against legal liability, algorithmic bias, and reputational harm.
AI Chain of Accountability
The AI Chain of Accountability shifts the "AI Paradox" from a monolithic approach to a dynamic distribution of shared governance responsibilities between buyers and sellers.
It maps governance authority across 16 commercial lifecycle milestones—expanding beyond the traditional software development lifecycle to include critical buyer-side operations—to ensure buyers clearly understand when, where, and how to apply risk mitigation controls across the full chain of AI accountability.
Procurement Workplace
AI Literacy Assessment
Our proprietary diagnostic tool evaluates individual knowledge, skills, and abilities along four strategic pillars (AI Awareness, Practical Application, Critical Evaluation, and Ethical Responsibility) using familiar procurement terminology, scenarios, and use cases to reinforce the importance of AI literacy in their job function.
Not only does this approach enable us to identify practical and meaningful educational pathways to transition your workforce from passive AI users to expert AI collaborators, but our design helps the employee understand that AI literacy is an increasingly important and essential job function.
Procurement Risk Profile
Score Card
Our Risk Profile Tool is an executive-grade, internal consensus-building diagnostic instrument that quantifies the complexity of your prospective AI purchase against the potential impacts on any vulnerable populations to derive a risk profile of the procurement before any solicitation writing occurs.
By mandating this consensus-based pre-procurement assessment, you replace subjective guesswork in requirements development with well-defined, strategic guardrails that help neutralize vendor bias and structurally safeguard your legal duty of care in high-risk scenarios .
Supplier Organization
AI Governance Maturity Assessment
Our research-grounded rubric is a high-stakes strategic tool that enables quantitative vendor rankings to assess critical maturity gaps across 12 dimensions like AI leadership accountability, AI policy rigor, and operational AI ethics.
By utilizing this rubric to objectively score and rank competing bidders, organizations can identify high-risk providers from more stable, trustworthy partners—ensuring every AI investment is aligned on AI governance and defensible from day one.