To ensure accuracy in its legal AI, LexisNexis unexpectedly hired a large number of lawyers, not just data scientists. These legal experts are crucial for reviewing AI output, identifying errors, and training the models, highlighting the essential role of human domain expertise in specialized AI.

Beyond generative AI for content creation, agentic AI offers immense value by automating tedious, error-prone governance tasks. AI agents can manage compliance, routing, and metadata tagging at scale, turning previously manual and costly work into an automated workflow.

For knowledge workers like authors, up to 50% of their time is spent on tedious "chores" like organizing sources or creating timelines. AI automates this drudgery, freeing up mental bandwidth for higher-value creative tasks like narrative construction and prose.

Effective AI tools are not just about task automation; they encode an expert's strategic perspective. By building a point-of-view-driven research process into an app—prioritizing specific metrics and analyses—you can scale specialized expertise across an entire marketing team, ensuring consistent, high-quality insights.

The most effective use of AI in content is not generating generic articles. Instead, feed it unique primary sources like expert interview transcripts or customer call recordings. Ask it to extract key highlights and structure a detailed outline, pairing human insight with AI's summarization power.

Run HR, finance, and legal using AI agents that operate based on codified rules. This creates an autonomous back office where human intervention is only required for exceptions, not routine patterns. The mantra is: "patterns deserve code, exceptions deserve people."

The company developed an AI that conducts highly technical expert network interviews, automating a high-friction manual process. This enables new, scalable content creation like monthly channel checks across dozens of industries—a task too repetitive for human analysts to perform consistently at scale.

Instead of prompting an AI to generate a full article, which often results in 'slop,' a better approach is to use it as an assembly tool. Feed the AI granular, pre-vetted pieces of unique business intelligence (like sales data or expert insights) to construct a higher-quality output.

Effective AI content strategy uses tools to handle first drafts and outlines, accelerating production and ensuring consistency. This frees up humans to perform the crucial roles of editing, shaping perspective, and injecting unique, lived experiences, which AI cannot replicate. The goal is amplification, not automation.