What do enterprises on the leading edge of the AI-deployment curve do that sets them apart?
For one thing, these companies are far more likely than less AI-mature organizations to leverage AI risk management to strengthen their risk-management activities. This application is relevant to AI in tax compliance, where organizations must make informed decisions while continuously managing compliance risk.
What AI Leaders Do More Frequently
That takeaway comes from PwC’s AI-performance study of more than 1,200 global companies. The consulting firm’s analysis shows that approximately 20% of those organizations capture roughly 75% of AI-driven revenue and efficiency gains: “One overlooked contributor to their success: using AI for risk management,” according to PwC. “These top performers are 2.3 times as likely as others to report that AI has helped reduce their exposure to risk.”
The article indicates that AI-driven risk management improvements center on anomaly detection, evidence collection and report generation, heightened accuracy (related to regulatory submissions), and scenario modeling (analyses that model policy or geopolitical changes).
Areas of AI Alignment
In its guidance on how organizations can better leverage AI to strengthen risk management, PwC emphasizes two actions that resonate with Vertex’s approach to AI. The first is to treat human-in-the-loop (HITL) oversight as a fundamental component of the AI solution. The second is to “think end-to-end” by integrating AI across complete collections, or lifecycles, of processes. This differs markedly from using AI to automate discrete workflows. Vertex Vice President of Technology Strategy, Chris Zangrilli, makes a similar point in a post that describes Vertex’s Tax AI Platform: “Rather than adding [AI] as a bolt-on capability to an existing product, we’re building AI into the fabric of everything we do, through a unified platform approach designed specifically for the complexities of tax. Our aim is to build AI that tax teams can trust in environments where accuracy, explainability and accountability matter.”
In fact, much of PwC’s guidance on deploying AI to improve risk management is conceptually in step with Chris’s discussion of how we’re exposing AI capabilities across the Vertex portfolio. Here are three points of alignment:
- Architecture: By coupling our AI Platform with our Cloud Platform, Vertex is building a broad, unified intelligence layer that reflects end-to-end thinking.
- Detection: Our agentic tax workflows detect anomalies and identify issues that may require attention before they become filing or compliance risks.
- Governance: PwC’s recommendation to “build trust at the beginning” echoes Vertex’s assertion that trust cannot be an afterthought. “Governance is designed into the platform from the beginning to support explainability, auditability and regulatory requirements from day one,” Chris notes.
What This Means for Tax Authorities and Teams
Tax authorities are also adopting AI in ways that mirror the priorities of leading enterprise tax functions. The Intra-European Organisation of Tax Administrations (IOTA) has highlighted how administrations are using machine learning, anomaly detection, fraud prevention, and taxpayer-risk assessment to improve accuracy and efficiency. The Organisation for Economic Co-operation and Development's (OECD) Tax Administration 3.0 vision points in a similar direction, embedding tax processes more directly into business systems and reducing compliance burdens through better data and digital connectivity. For businesses, the message is clear: tax AI must support not only efficiency, but also explainability, audit readiness, and governance. Success increasingly depends on making tax decisions that can be understood, validated, and defended long after the transaction takes place.
Enterprises with mature AI capabilities generate more efficiency gains and revenue improvements while more frequently using AI to bolster risk-management activities. Companies with forward-looking finance and tax teams now have an opportunity to integrate AI throughout the continuous compliance lifecycle, helping strengthen both decision-making and compliance outcomes.