Nearly all corporate artificial intelligence pilot projects fail to deliver measurable business value, according to new research — a finding that comes as Louisiana companies accelerate AI hiring faster than the data workforce needed to support it.

A national analysis by data consultancy DoubleTrack found that 95% of generative AI pilot projects fail to produce measurable profits, a rate that researchers attribute largely to weak data infrastructure rather than shortcomings in AI technology itself.

Despite that failure rate, Louisiana employers are hiring AI specialists far faster than data infrastructure workers. The study found Louisiana companies posted 151% more AI and machine-learning jobs than data infrastructure roles, ranking the state among the most imbalanced AI labor markets in the country.

According to the analysis, Louisiana employers advertised 548 AI-related positions compared with 218 data infrastructure jobs, meaning companies are hiring more than two AI specialists for every data engineer or platform specialist; the reverse of what experts recommend.

According to the study, industry consensus suggests that organizations should hire at least two data infrastructure professionals for every AI specialist to ensure that data is reliable, integrated, and usable. Without that foundation, AI systems often stall or are abandoned.

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The consequences are already visible nationwide. Research cited in the report shows 42% of companies scrapped most of their AI initiatives in 2025, more than double the abandonment rate from the year before.

The findings carry particular significance for Louisiana as the state courts data centers, advanced manufacturing and digital infrastructure projects, including large-scale developments proposed in Caddo and Bossier parishes. While such projects promise billions in capital investment, they depend on robust data pipelines, power reliability and utility coordination — areas that require deep data infrastructure expertise.

Data centers, in particular, employ relatively few permanent workers but rely heavily on specialized data engineers to manage system redundancy, cybersecurity, data flow and integration with cloud and AI platforms. A shortage of those workers could limit the long-term impact of the projects Louisiana is working to attract.

The report also raises questions for workforce development and higher education. Louisiana universities have expanded AI-related coursework in recent years, but researchers say data engineering, database management and system integration skills are just as critical — and often in shorter supply.

Only 6% of enterprise AI leaders nationwide believe their data systems are ready to support AI projects, and 71% of AI teams spend more than a quarter of their time on basic data preparation and system integration rather than advanced analytics or model development, according to research cited in the study.

Those infrastructure gaps can have ripple effects beyond technology firms. Utilities, energy producers, health systems and logistics companies — all major pillars of Louisiana’s economy — increasingly rely on AI tools that require clean, connected data to function reliably.

DoubleTrack recommends companies adopt a 2-to-1 hiring ratio, with two data infrastructure hires for every AI specialist, to reduce failure rates.

“The businesses most at risk aren’t the ones moving slowly on AI,” said Andy Boettcher, the firm’s chief innovation officer. “They’re the ones who hired aggressively for AI roles without investing in data quality and infrastructure.”

As Louisiana pushes to position itself as a hub for data-driven industries, researchers say closing the gap between AI ambition and data readiness may determine whether those investments succeed — or quietly join the 95% that do not.