Government agencies could significantly improve data relevance by implementing 'user governance' boards. Comprised of outside experts and business leaders, these boards can guide agencies on what data is most valuable to collect and analyze, moving beyond static surveys to capture real-time economic shifts.

Reducing the IRS budget incentivizes aggressive tax evasion by the wealthy because the probability of being audited is extremely low. This 'tax gap' of uncollected revenue is a more significant de facto tax cut than legislated ones, costing the government hundreds of billions.

Underfunding the IRS is not a neutral act but a policy choice that disproportionately benefits the rich. Auditing complex, high-value returns requires significant resources. A weakened IRS cannot effectively pursue wealthy tax evaders, creating a massive "tax gap" that functions as a stealth tax cut for the top earners.

Traditional data tools were built for specific, siloed tasks with a pre-defined purpose. They are ill-suited for AI agents, which require broad, contextual understanding across an entire organization's data. To power AI effectively, companies need a new data foundation that can unify disparate sources and provide holistic context.

The biggest tax cut isn't a legislative change but rather neutering the IRS's budget. The agency lacks the resources to audit the complex finances of the wealthy, incentivizing aggressive tax strategies and leaving hundreds of billions in legally owed taxes uncollected each year.

While AI will improve IRS efficiency in collecting taxes from typical wage earners, it struggles with the bespoke, complex tax shelters used by the ultra-wealthy. This creates a perverse outcome where enforcement becomes tougher on the masses while the wealthiest continue to exploit loopholes.

Unlike instrumented data from internal systems, data collected from external sources (e.g., government forms) presents a major challenge. Data leaders cannot fix quality issues at the source, forcing them to invest heavily in downstream cleaning, enhancement, and interpretation to account for errors and ambiguity.

Instead of focusing on changing the tax code, the most significant tax benefit for the ultra-wealthy has come from systematically cutting the IRS budget. This prevents the agency from auditing complex returns, effectively making the wealthy 'protected by the law, but not bound by it,' and creating a massive enforcement gap.

The primary obstacle for Fortune 500 companies adopting AI isn't a lack of good models, but their disorganized data. Decades of fragmented systems mean agents can't reliably find the right information, creating a massive, decade-long data cleanup and consolidation opportunity for services firms.