Global AI challenge to transform investigative journalism

• Goal is to create tools that support watchdog journalism without replacing reporters

• Contest opens May 15 and ends July 15

• Top teams to receive cash prizes

EVANSTON, Ill. -- Investigative journalists often obtain thousands, if not millions of pages of documents and take on the challenge of finding the truth buried inside. That could take months, or even years, of work to accomplish. Artificial intelligence can help, but many AI tools still have shortcomings.
Now, a new contest led by the Generative AI + Journalism Initiative at Northwestern University is working to unlock the potential of coding agents to increase the processing power of AI. The goal is to help investigative journalists work faster, more efficiently and smarter. The contest launches Friday, May 15 and ends July 15.

The Agentic AI Investigative Journalism Challenge is a global competition inviting journalists, data scientists, developers and technologists to build AI "agent skills," or bundles of instructions and code, to help make investigative reporting faster, cheaper and more transparent.

"We don't want to replace investigative journalists," said Nick Diakopoulos, professor in communication studies and computer science. Diakopoulos leads the Computational Journalism Lab in Northwestern's School of Communication. "The idea is to unlock the potential of these agents to support investigative journalists - to suggest leads, patterns and connections that are apparent in the documents."

The Challenge

Using Claude AI to find newsworthy insights in a provided dataset comprised of U.S. House and Senate lobbying disclosures and congressional press releases from 2022 through March 2026, competing teams will enter their process as a replicable workflow.

Teams will submit:

• Agent skills - the reusable workflow they built, including any new skills developed

• Findings report - a written summary of the newsworthy discoveries produced by running the skill(s) on the data plus any outside material brought in to enhance the investigation

• Interaction traces - full logs of the model sessions, including inputs, tool calls, outputs, and the moments when human judgment intervened

• README.md - a brief map of the submission, including skills, which findings they support, where the relevant traces are located, any outside data used, any conflicts of interest and whether findings suggest possible legal violations that should be flagged to the evaluation panel
  

"We want to spark a movement around building these kinds of agent workflows," said Nick Hagar, postdoc in Northwestern's Generative AI + Journalism Initiative and creator of the contest. "Reporters need a new toolkit to speed up critical investigative reporting processes. With this contest, we hope to demonstrate the viability of AI agent workflows and foster sharing among like-minded journalists."

The top team will win $5,000, second place $2,500 and third place $1,000. All three teams will be invited to present at the 2026 Computation + Journalism Symposium.

"Even though we are giving folks a specific data set to work with, part of the judging criteria is how repeatable the skill is in terms of being applicable to new data sets or other kinds of investigations journalists might want to pursue," Diakopoulos said.

More information and submission forms are available online.

The challenge emerges from an effort to develop responsible practices for generative AI in news production, which launched in April 2024 with a $1 million grant from the John S. and James L. Knight Foundation through its Press Forward program. The project is a collaboration between Northwestern's School of Communication and the Medill School of Journalism, Media & Integrated Marketing Communications.