Build trust through AI to power tax compliance – PwC

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Here are five of the most important considerations for developing trusted AI in your tax function.

Creating a culture of trust. Trust begins with governance and culture. On the one hand, it’s about establishing clear guidelines and responsible AI standards, ensuring everyone understands the risks and knows where the red lines are. On the other, it’s a question of fostering a culture of responsibility and trust around AI — which needs to be driven from the top.

Trusting your data. Poor quality data leads to poor AI outcomes — and a potentially catastrophic loss of trust. A robust, secure, organised, comprehensive and trusted data strategy is therefore critical. And it needs to be seen not as a technical compliance-oriented task, but rather as an opportunity to build a foundation for future value creation. This is a topic we explored in our recent data strategy article. 

Trusting AI’s outputs. The risks of inaccurate AI ‘hallucinations’ are well documented. The best way to manage this is through a ‘human-led, tech-powered’ approach. It means building in checks and balances to allow experienced professionals to guide AI inputs, review outputs, make the key decisions and perform the important work. Examples include using ‘prompt engineering’ to improve the information supplied to AI models. 

Trusting in people. People, ultimately, are at the heart of any AI transformation. But they need the right skills to use AI in a trusted way. Indeed, our own AI-powered transformation at PwC underscores the importance of upskilling and change management. And we’re not alone: our 2024 Global CEO Survey found 69% of business leaders think AI will require most of their workforce to develop new skills. In fact, the evidence for a skills-led transformation is mounting. PwC’s AI Jobs Barometer found that the occupations that are most ‘AI-exposed’ will see as much as a 25 percent change in the skills required, increasing the pressure on workers to upskill to stay relevant. 

Building trust for stakeholders. Although transparency doesn’t in itself replace the need for trust, tax and compliance leaders can go a long way to building trust with internal and external stakeholders by being transparent about how AI systems operate, making their decision-making processes understandable, demonstrating how data is safeguarded, and so on.