Beyond futuristic applications, AI is currently providing tangible value in medicine, commerce, and banking by tackling core operational challenges like identifying fraudulent claims, optimizing shipping routes, and preventing money laundering, thereby boosting efficiency and reducing financial risk.

Contrary to the view that useful AI agents are a decade away, Andrew Ng asserts that agentic workflows are already solving complex business problems. He cites examples from his portfolio in tariff compliance and legal document processing that would be impossible without current agentic AI systems.

Industries historically slow to adopt software are now rapidly embracing AI. Unlike rigid workflow tools, AI excels at parsing dense text and augmenting the nuanced, unstructured work common in these fields. This allows new AI vendors to gain traction without needing to rip-and-replace legacy systems of record like EHRs.

Within the last year, legal AI tools have evolved from unimpressive novelties to systems capable of performing tasks like due diligence—worth hundreds of thousands of dollars—in minutes. This dramatic capability leap signals that the legal industry's business model faces imminent disruption as clients demand the efficiency gains.

To solve the manual, week-long process of distributing 4,000 unique PDF parking passes, the team built a custom AI application in 90 minutes. It handles PDF separation, data appending, and logical distribution, highlighting the ROI of building hyper-specific internal tools.

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.

AI tools can instantly parse, reformat, and summarize dense documents like congressional bills, which would otherwise require significant manual cleanup. This capability transforms workflows for analysts and researchers, reallocating time from tedious data preparation to high-value strategic analysis.

AI's role has matured from assisting with trivial tasks like homework to autonomously managing complex, multi-step financial and scientific processes end-to-end at major companies like Coinbase, Salesforce, and Novo Nordisk, signaling a fundamental shift in its capability.

The goal for AI isn't just to match human accuracy, but to exceed it. In tasks like insurance claims QA, a human reviewing a 300-page document against 100+ rules is prone to error. An AI can apply every rule consistently, every time, leading to higher quality and reliability.