Data-First Foundation for Tax Pros

Hey — It’s Edna.

Welcome to this week’s edition of The Growth Ledger, where we unpack how to future-proof your tax practice with AI-ready data strategies.

Today we'll dive into:

• Critical data challenges facing modern tax practices

• Order of operations to follow for risk mitigation during adoption

• Actionable steps to future-proof your practice

The IRS Is Using AI. Your Clients’ Data Quality Just Became a Liability.

The IRS’s new AI audit systems are flagging inconsistencies in returns 10x faster than human reviewers. Meanwhile, firms using hybrid human-AI workflows report 40-90% efficiency gains—but only if their data foundations are bulletproof.

Critical Challenges in the AI Era

1. Data Validation Gaps: 63% of errors stem from inconsistent client intake forms 

2. Workflow Fragmentation: Teams lose 15 hours/week reconciling spreadsheets and tax software outputs

3. Hybrid Team Hurdles: Remote staff face 28% longer review cycles without proper tooling 

Don’t put the cart before the horse

Data quality and management must be prioritized before AI deployment. Infrastructure modernization preceding any AI initiatives ("plumbing before faucet cleaning"). This means that you’re best bet is partnering with tax tech that understands your current infrastructure and checking out their roadmap updates. Ethical guidelines and compliance frameworks need to be established early, with cross-functional expertise being your green flag when in the decision making process. Seek out technical and domain experts that work together, or better yet teams that have both. Those who understand and can properly access if your tax pro biz is a technical fit and help manage your data alongside you.

Start prepping this tax season, modernize by the next!

1. Dedicated Tax Data Teams

Leading organizations are establishing dedicated tax data teams that:

• Bridge the gap between tax and technology

• Respond faster to data-related challenges

• Reduce dependency on general IT resources

• Enhance data accessibility and quality

Identify who on your team can lead this team, or invest in training your leadership in this lucrative skill. Do you know who that is? Will it be you?

2. Strategic Implementation

Deloitte's research shows that 70% of AI experiments don't make it to production. To beat these odds:

• Start with clear pain points and "low-hanging fruit"

• Focus on input data quality first (review your onboarding, refine your intake)

• Seek to optimize parts of your workflow, instead of rushing into adoption for tech that reinvents the wheel with shiny promises of end-to-end automation or all-in-one solutions.

3. Get Ready to Measure Impact

We discussed this e modernized tax practices need new metrics for success. Try these on for size and get tools in place to start measuring these metrics:

• Reduction in data preparation time

• Accuracy rates in tax filings

• Speed of response to regulatory changes

• Quality of strategic insights delivered to clients

Success with AI in tax practice isn't just about the technology—it's about the quality and accessibility of your data. As we move forward, the firms that thrive will be those that build strong data foundations while leveraging AI's capabilities for strategic advantage.

Until next time,
Edna