It’s time for tax to consider AI

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In a recent EY survey of 1,000 global tax and finance executives, 85% of respondents indicated that they do not expect Generative Artificial Intelligence (GenAI) tools to help boost effectiveness and efficiencies within their tax functions during the next three years.  

I was surprised to see that statistic, and so were the EY experts who analyzed that and other survey responses – most of which focused on tax transformation. The EY report encourages tax leaders to review their “strategy around working with other functions on a comprehensive technology strategy that can integrate with new advances that are coming, especially generative AI.” Not to nitpick, but GenAI represents just one form of AI – and this category of AI is more than just ChatGPT. So, there’s at least a chance that some respondents were thinking only about GenAI applications and not more broadly. 

Either way, they may want to reconsider, especially given that some finance groups already are testing and deploying forms of AI, including GenAI. 

“Leading finance groups already are putting GenAI tools through their paces to improve cash flow management, FP&A, liquidity risk management, fraud detection, workflow efficiency, scenario planning and more,” writes Protiviti Founding Managing Director Jim DeLoach in Forbes. “While recent strides in advanced analytics and machine learning have sharpened financial forecasts and equipped finance groups with greater predictive proficiency, GenAI adds an entirely new layer—a narrative that explains the why behind financial analyses—to these existing capabilities.” 

DeLoach also reports that GenAI can be used to create summaries of FP&A outputs for procurement teams that can use these updates to “make faster, more precise adjustments to fluctuations in customer demand, raw material prices and other variables.” Additionally, AI-generated summaries of customer payment patterns can help finance groups make quicker adjustments to cash flow management approaches, DeLoach adds.  

Vertex is also committed to leveraging AI technologies – in a highly thoughtful manner – to improve our own offerings. Through the use of co-pilots (which users may dial-up or down in assistance) embedded into our solutions, customers can gain insights, recommendations, research and even approvals they can choose whether or not they want to take action against. Combining AI capabilities with human tax expertise can both assist with and optimize workflows. 

As EY points out, it makes sense for tax groups to evaluate how AI tools can help their performance in the coming years. Doing so, EY concludes, starts with developing a “sound data and technology strategy.” And it makes sense for the tax teams who develop those roadmaps to inform themselves regarding AI applications while monitoring how these tools evolve.  

For more insights on current and future tax transformation priorities, check out this post from my colleague Larry Mellon, Tax Director in Vertex’s Chief Tax Office. 

Blog Author

Sal Visca, Chief Technology Officer

Sal Visca

Chief Technology Officer

See All Resources by Sal

As Chief Technology Officer, Sal leads the company’s technology strategy, software engineering and innovation roadmap to accelerate growth. 

He joined Vertex in 2021 after 30 years of technology and executive management expertise transforming and operating large-scale cloud software businesses. 

Sal spent his early career at IBM as a software engineer, architect and then in executive roles developing the company’s e-commerce and middleware products. He has also held Chief Technology Officer roles at Elastic Path Software, Business Objects and SAP. 

He holds a bachelor’s degree with honors in computer science from Western University.

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