AI can be a powerful fraud detection tool by comparing a company's public statements against alternative data. For example, it can analyze satellite imagery of shipping traffic or factory activity and flag discrepancies with management's guidance.

AI adoption in drug companies isn't about moonshot discovery via a single prompt. Its immediate, high-impact use is in automating and error-proofing massive regulatory documents for the FDA, where a single misplaced comma can cause costly, multi-billion dollar delays.

Beyond individual productivity gains, AI's strategic enterprise value is its ability to re-engineer core operations. This automation creates significant efficiency savings, unlocking capital that can be reinvested into strategic technology spending without negatively impacting financial returns.

Businesses are unlikely to use powerful AI simply to shave a few percentage points off their software spend. The real, high-impact ROI comes from applying AI to improve core business operations, making the actual business more effective and efficient.

The most tangible ROI for AI in healthcare today isn't in complex diagnostics, but in operational efficiency. AI scribes that free up doctors, intelligent call centers that triage patients correctly, and automated claim management are solving major bottlenecks and fighting burnout right now.

While many focus on AI for consumer apps or underwriting, its most significant immediate application has been by fraudsters. AI is driving an 18-20% annual growth in financial fraud by automating scams at an unprecedented scale, making it the most urgent AI-related challenge for the industry.

Pharmaceutical giants are adopting AI not for moonshot "cure cancer" prompts, but to streamline critical, error-prone processes like compiling 10,000-page FDA documents. This mundane application prevents costly delays and accelerates time-to-market for multi-billion dollar drugs.

While public attention focuses on glamorous AI applications like image generation, the most transformative and valuable contributions of AI are happening in less visible areas. Optimizing logistics, streamlining back-office operations, and improving industrial processes are where AI is quietly delivering significant ROI.

While AI for designing novel molecules gets the hype, its practical, near-term impact is in streamlining operational tasks like summarizing medical charts, preparing SEC filings, and analyzing contracts, which are a better fit for current LLM capabilities.