Why AI for In-House Tax Teams?

In-house tax professionals juggle multiple responsibilities that expand outside of standard tax and is closer to corporate advisory with a tax lens.

Generative AI (GenAI) and advanced Large Language Models (LLMs) can reduce time spent on repetitive tasks, minimise errors, and free up internal tax team resources to focus on high-level strategy and advisory work to bring value add to the function and overall business model.

Proven AI-Driven Use Cases

Synthesising Internal Tax Policies

AI solutions can easily ingest existing policy documents, SOPs, and corporate guidelines quickly and embed the information into its database through techniques retrieval augmented generation (RAG) techniques. Using RAG, it can then provide real-time answers to policy-related questions, ensuring alignment with both corporate standards and Australian tax legislation to headstart any policy discussions.

Using AI can also allow for policy harmonization as internal policies often overlap or even conflict when drafted by separate divisions without going through thorough risk processes. By embedding a policy database, GenAI tools can ustilise its logic learnt within its LLM framework to provide practical insight and assist in policy generation.

AI & Tax-Led Solutions

AI can continually monitor financial transactions, expense reports, and other data streams by interfacing with internal data systems (ERP, HR, etc.) and compare them with the ATO’s latest compliance guidelines or company internal risk thresholds. Overlaying this with an AI agent can allow tax professionals to obtain real-time data to conduct tax analysis or identify risks within internal tax controls for better decision making.

Another example where AI’s can assist is in scenario modelling. Given the breadth of information contained within the RAG model and the LLMs ability to read and synthesis this information instantaneously, Gen AI solutions can run efficient “what-if” simulations for corporate restructures or new ventures or day-to-day administrative problems under various legislative scenarios.

Streamlining Collaboration

Creating an AI-driven chatbots or email assistants within internal systems can be a simple task with new LLM technology. The creation of these new chatbots can allow internal teams to self-service simple routine tax queries from other departments whilst directing complex issues to human experts.

Furthermore the transition to cloud base data filing solutions by many organisations has undoubtably strengthened the power of RAG to embed firm wide data into its knowledge base to allow for more accurate Gen AI outputs based on company information. Note that because most LLMs are not specifically trained on company data, there is a risk of hallucination as most LLMs would instead utilised its ‘learnt’ knowledge and logic which is applied to company data.

Example Workflows

Conclusion

AI offers in-house tax professionals a robust toolkit for synthesising corporate policies, automating compliance checks, and creating forward-thinking tax-led solutions. By combining domain expertise with next-generation AI capabilities like RAG and AI agents, tax teams can move from reactive compliance work to proactive strategic advisement. The key is to start with well-defined use cases, ensure robust security, and maintain a culture of continuous learning and improvement.