Falkovia provides AI governance diligence for venture capital and private equity firms. We surface the human architecture risk that standard technical diligence never examines, pre-acquisition, and build the governance infrastructure that protects value creation post-close. Confidential, fixed-scope engagements scoped to deal timelines.
Venture capital and private equity firms evaluate AI investments across technology, market fit, and team. What they rarely evaluate is the human governance architecture that determines whether AI creates value or creates liability inside a portfolio company. This is not a compliance concern. It is a value creation variable.
The data from the last 24 months is unambiguous: AI does not fail because of code. It fails because the human systems surrounding it were never designed. Decision rights, accountability structures, workforce readiness, and governance architecture are the variables that determine whether AI investment produces value or produces liability.
For an investment firm, this means the AI value creation assumptions embedded in a deal model are functionally dependent on a variable, human governance architecture, that standard technical diligence does not examine.
$4.63M
avg. shadow AI breach cost
State AI laws are live and expanding. Colorado, Texas, and New York create specific liability for organizations without documented human oversight of AI-influenced decisions. Most portfolio companies cannot produce the documentation a regulator would require.
70-85%
of AI initiatives underperform
Not because technology breaks, but because trust was assumed, authority was unclear, and the workforce resisted in ways that looked like compliance but functioned as sabotage. The value creation thesis never materialized.
17%
higher cost vs. standard breach
Portfolio companies that cannot demonstrate AI governance maturity face additional scrutiny, longer diligence cycles, and valuation discounts at exit. Governance that exists is a defensible asset. Governance that does not exist is a discovered liability.
Know the liability before you price it.
Build the asset before you need to defend it.
1,208 AI bills were introduced across 50 states in 2025, with 145 enacted into law. Colorado's AI Act takes effect June 30, 2026. Texas TRAIGA is live. The EU AI Act classifies multiple sectors as high-risk. For portfolio companies deploying AI in any regulated context, compliance is no longer a future roadmap item.
Organizations with formal AI governance councils reach ROI in 7.5 months compared to 13.5 months without. Successful AI projects allocate 47% of budget to foundations (data, governance, change management) versus 18% in failed projects. Governance is not a cost center. It is the mechanism that converts AI investment into returns.
59% of employees use unapproved AI tools. Among executives, 93%. The average shadow AI breach costs $4.63M, 17% above standard. 86% of organizations are blind to their own AI data flows. This exposure exists inside your portfolio companies today, whether or not it appears in diligence materials.
Do you know which portfolio companies are using AI, how, and under what governance? Can you map AI adoption across your portfolio and identify where governance architecture is absent?
In each portfolio company, who holds authority over AI decisions: approval, restriction, override, and prohibition? Is that documented, or assumed?
Does your standard technical diligence examine human governance architecture (decision authority, oversight structures, accountability mapping), or only the technology stack?
Could your portfolio companies produce AI governance documentation if a regulator asked tomorrow? Would that documentation demonstrate the institutional oversight that state and federal regulators are now requiring?
Is AI creating value in your portfolio, or creating undocumented liability that will surface at exit? Can your portfolio companies demonstrate governance maturity to a future acquirer?
Accountable for portfolio-level risk and responsible for ensuring AI adoption across portfolio companies does not create regulatory, reputational, or valuation exposure that reaches the investment committee.
Responsible for operational value creation and accountable for ensuring AI-driven efficiency gains do not introduce governance gaps that undermine the value creation thesis.
Conducting technical and operational diligence on acquisition targets and responsible for identifying AI governance risk before the deal closes.
Leading organizations where AI adoption is accelerating and accountable for governance architecture that protects the company from regulatory, legal, and operational exposure.
Exercising oversight of investment decisions and responsible for understanding whether AI governance risk has been adequately examined and addressed.
The technical stack is 10%. The human architecture is 90%. Most never examine it.
Engagements are confidential, fixed-scope, and scoped to deal timelines. Start with a confidential conversation about your portfolio.
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