Generative AI in tax: 5 essential insights for leaders

1. GenAI can — and will — help almost every aspect of your tax function

GenAI comes already trained on large amounts of documents and data, including financial statements, tax regulations and regulatory decisions. This pre-training can help you deploy and scale GenAI far more quickly than conventional AI. But it’s not enough for the accuracy and security that tax requires. Instead, you’ll need to license a private version of one of these pre-trained GenAI models. With rigorous data governance, with safeguards, you can embed your own data into this private model. Enhanced with your financial data, GenAI can then provide highly accurate answers to prompts or requests that your tax professionals give it.

Your tax professionals can, for example, use a GenAI chat-based interface — powered by this mix of commonly available and secure, proprietary data — to access knowledge (such as the latest regulatory decisions), classify and standardize documents, analyze documents or data (such as historical audit outcomes inside your company) or generate reports. Let’s say you need to generate Pillar II disclosures for the first time. GenAI can study examples of reports, then input your data, follow instructions customized to your specific needs and produce a high-quality first draft.

2. GenAI is powerful but not perfect

As is true for all technology, it’s important to understand GenAI’s strengths and weaknesses. These AI models can be very good — accurate, fast and relevant —  at tasks related to understanding, summarizing and generating text and data. Even so, GenAI is best seen not as a pure automation tool, but as a way to help your team grow capacity and work better. For all GenAI, it’s important to build in checks and balances: oversight that will include your tax professionals reviewing and improving at least some of GenAI’s outputs. For sensitive or complex issues, GenAI will mostly provide first drafts or inputs (such as data analysis) that your professionals can then use to make their own work more detailed and accurate.

It may also be wise in some cases to combine GenAI with conventional AI or “old-fashioned” automation. Consider indirect tax transactional sales mapping. Your company may have many products and types of spend, with inconsistent descriptions. It could take your people a lot of time to classify and categorize them all. Machine learning can potentially do some of this work — but it often requires such large training sets, its use isn’t practical. GenAI can solve that problem by reducing this need for historical training data. Machine learning can then do the job, sparing your people this tedious work. A combined GenAI-machine learning solution is often also more dynamic. It can better adapt to new business scenarios and needs.

3. GenAI won’t replace your employees. It will change their jobs.

As GenAI proliferates, your tax professionals will still be in demand. The way GenAI works best in the tax function is when the approach is “human-led, tech-powered.” People make the key decisions and perform the important work, but GenAI is helping them like the world’s best assistant: finding and crunching financial data, reading and summarizing documents (such as regulatory decisions), even writing some simple software when needed. But to work well with GenAI, most tax professionals will need additional skills. For example, they’ll need to learn “prompt engineering” — carefully crafting input questions to get accurate, relevant answers. Your team should also learn when they should and shouldn’t use GenAI, how to validate outputs and how to embed your data into your private GenAI model — securely and responsibly.

GenAI may lead to deeper changes too. Since it can help you do more work more quickly, that leaves more time to focus on strategic issues with the business — requiring more business knowledge by your staff. Tax technology teams may find they’re doing less programming (GenAI can write code) but more data science. Still, if you provide a good plan for GenAI, it may excite your team. In PwC’s Global Workforce Hopes and Fears Survey 2023 over half of the 54,000 employees surveyed (in all functions) expected AI to impact their career positively over the next five years.

4. GenAI has to be responsible AI

At PwC, we work in a tightly regulated industry. Our clients entrust us with sensitive data. And our recruitment and retention depends on our ethics — including our ethical use of technology. That’s why we have developed a responsible AI framework that can govern GenAI and manage the risks from strategy through execution. 

One potential (and avoidable) risk comes from using public GenAI models. These models may not always give you full control over how your company’s data and intellectual property is used and protected. But you can often negotiate a license for access to a private version, then run it within a secure environment, which your data never leaves. This level of data security (a must for us at PwC) requires both rigorous governance and careful negotiations with GenAI vendors. At PwC, if a GenAI vendor offers a new capability that requires our data entering their systems, we don’t adopt it. If necessary, we develop our own version. Our clients usually choose a similar approach — and sometimes run their initial GenAI pilots within our secure systems.

5. Scale and ROI can come quickly

Tax can achieve major, rapid ROI from GenAI in two ways. The first comes from GenAI’s remarkable scalability. For example, a GenAI model that extracts facts and trends from tax notices can also — with a little refinement — spot issues in due diligence, validate large data sets, or analyze and forecast tax controversy trends. We built an AI factory at PwC to deliver this scale and ROI. It features pods with both business and technology experience, supported by toolkits with reusable software code and prompts. These pods help find opportunities, in tax or other areas, then scale each use case across other tasks, functions and lines of business.

The second source of ROI is unique to tax professionals: Implementing GenAI, whether in the tax function or elsewhere, can in some cases generate dollar-for-dollar R&D credits (which translate to cash savings) for the business. But tax professionals need to be involved from the start — even for deploying GenAI in other parts of the organization — to identify and realize these pay-fors. They could offset significant portions of GenAI-related costs.

How tax can get started with GenAI

There’s a tested playbook for GenAI that can work for all functions, including tax. It starts with security and trust, then covers strategy, initial use cases, an AI factory for scalability and workforce transformation. For tax in particular, a few additional considerations can help you get the most from GenAI.

• Get a seat at the table  — early. If tax professionals are involved early on, working with leadership, the business and technology teams, they can help the whole organization achieve value from GenAI — through R&D credits, planning for tax implications and opportunities and more.
• Consider big picture goals. If you define your goals  — such as better planning, stronger data governance or faster answers for the business — you may find many ways in which GenAI can help.
• Educate your teams. If you bring in your people early to understand GenAI and your goals for it, you’ll not only prepare them to use it. You’ll also hear good ideas for additional use cases.
• Start low risk. Given the sensitivity of tax data and the need to avoid costly mistakes, your first pilots should involve nonsensitive data and not be especially complex.
• Let GenAI catalyze other initiatives. GenAI can deliver so much value, it can often help other priorities — such as digital or workforce transformations.

You haven’t fallen behind — yet

GenAI can do so much for your tax professionals that it’s bound to transform the function. But though the technology is moving quickly, it’s still early. Our July webinar (Tax Readiness: Changing the game for tax with generative AI) was one of our most popular ever — but well over half of participants said that they had either “not yet started” with GenAI or were “in the early stages.”

So, wherever you are with GenAI today, you haven’t fallen behind. You have a chance to grow efficiency and capacity while preparing your team for the future and safeguarding data. But it would be wise not to wait too long. GenAI is an effective complement for tax — and that’s becoming common knowledge.