OpenAI commits $5 million to expand Lenfest’s AI newsroom fellowship
OpenAI and The Lenfest Institute for Journalism have announced the next phase of the Lenfest AI Collaborative and Fellowship Program, backed by a new $5 million OpenAI commitment. The support also includes up to $5 million in software credits and engineering assistance, doubling OpenAI’s previous contribution to the initiative.
Launched in 2024 with AI engineering fellows at 11 major US news organizations, the program places full-time technologists inside operating news businesses. The Lenfest Institute said the next phase will invite a new cohort and broaden the range of participating news organizations.
From fellowship pilot to expanded program
The fellowship was designed to help local news organizations identify their own operational and editorial challenges, then develop practical AI solutions alongside newsroom leaders, reporters, product teams, revenue staff and executives. Fellows are locally hired and work within the organizations they support rather than operating as external consultants.
The first two years showed that adoption depended on trust, collaboration and a clear view of organizational needs, alongside technical capability. Jim Friedlich, executive director and CEO of The Lenfest Institute, said the fellows helped organizations establish practical tools, policy standards, guardrails and internal communication while keeping human news judgment at the centre.
The model also aligns with work such as OpenAI and Brazilian journalism partnerships, where journalism organizations are examining how AI services can support news operations while retaining editorial independence. In the Lenfest program, several fellows are expected to remain as full-time employees at participating organizations.
Tools built around newsroom workflows
Participating organizations have applied AI across audience engagement, news-product development, investigative research, advertising, reader revenue and operational work. At The Philadelphia Inquirer, the fellowship supported Dewey, which helps journalists search decades of archived reporting, and Scrape, a monitoring tool that changed a reporting task of roughly 15 hours per week into a daily digest of potential story leads from the newspaper’s region.
Chicago Public Media used AI-assisted translation workflows to publish time-sensitive Spanish-language coverage in a fraction of the time previously required. The organization also used the work to transcribe audio archives containing decades of Chicago news and culture. Other projects addressed advertising prospecting, donor modelling, audience personalisation, subscription growth, public-meeting monitoring and the transition from print to digital production.
Shared infrastructure is the next objective
Fellows have shared code, product ideas, technical approaches and implementation lessons across the cohort. The Baltimore Banner, for example, drew on work developed by The Philadelphia Inquirer’s team when building its own news-discovery tools. The Lenfest Institute now plans to turn strong projects into reusable tools, frameworks, plugins, guides, playbooks and technical resources.
For news organizations, the practical implication is to begin with a well-defined workflow problem, test with the staff who will use the result and establish transparent editorial policies before broad deployment. The expanded program is intended to make those repeatable methods and shared technical resources available to a wider local-news field.