Forbes contributor Gary Drenik explores this critical question—and features our approach to solving it.

We're honored to be highlighted in Gary's latest Forbes piece examining the stark reality facing enterprises: despite billions invested in AI, most projects never deliver value.

The key insight?

It's not about the algorithms—it's about the data.

As our CEO Morgan Slade shared with Forbes:

"The critical breakthrough isn't building ever-bigger models. It's when subject matter experts combine historical context with forward-looking, representative data so the models reflect reality."

Key takeaways from the article:

• MIT research shows up to 95% of AI projects fail

• Data federation beats traditional ETL for AI readiness

• Poor data quality costs businesses $12.9M annually (Gartner)

• Our CPI forecasting system—featured in the article—consistently beats Wall Street consensus by 23 days

What this means for institutional investors

In today's environment—with government data disrupted by shutdowns—having resilient, alternative data infrastructure isn't optional. It's survival.

Our Unifier platform addresses exactly what Gary identifies as the core challenge: making distributed data AI-ready without the costly, risky process of moving and duplicating it.

Through zero-copy architecture and natural language interfaces, we're helping hedge funds and investment banks join the successful 5%.

Beyond the article, we're seeing this play out in real-time

• Our real-time order flow analysis provides 45-135 day advantages over regulatory filings

• Our CPI predictions remain uninterrupted despite government shutdowns

• Portfolio managers can now query complex datasets in plain English

The lesson is clear: AI success requires treating data infrastructure as the foundation, not an afterthought.

Ready to join the 5% of successful AI implementations?

Contact our team: sales@exponential-tech.ai