I’ve judged journalism awards for years. The categories haven’t changed much: investigative, feature, breaking news, multimedia, editorial writing.

But the work has changed. Dramatically.

More and more of the best journalism I see involves significant AI assistance. Reporters using AI to analyze documents, identify patterns, transcribe interviews, research context. The human journalist remains essential, but the work is increasingly collaborative.

Our awards structures haven’t caught up.

The Current Awkwardness

Right now, AI-assisted journalism exists in an awkward limbo.

Should a reporter who used AI to analyze thousands of documents for an investigative piece enter the traditional investigative category? How does that compare to a reporter who did manual document review?

Should a team that used AI for translation across dozens of sources compete directly with teams working with translators? The outcomes may be comparable, but the methods differ significantly.

When AI contributes to the research, analysis, or production of journalism, how do we evaluate the work?

Currently, most awards programs ignore these questions. Entries don’t require disclosure of AI use. Judges don’t know whether work was AI-assisted or not. The elephant in the room goes unaddressed.

Why This Matters

Some would argue AI assistance doesn’t matter—what counts is the final product.

I don’t think that’s right, for several reasons.

Different achievements. A reporter who personally reviewed 50,000 documents demonstrates different skills than one who used AI to surface the relevant 500. Both can produce excellent journalism, but the nature of the achievement differs.

Fairness to entrants. Journalists who don’t have access to sophisticated AI tools compete against those who do. This creates uneven playing fields that awards should acknowledge.

Transparency for the field. Awards showcase what’s possible and set standards for practice. Not addressing AI obscures an increasingly important aspect of how journalism gets done.

Professional development. Highlighting excellent AI-assisted journalism helps the field learn. Hiding it prevents professional advancement.

What a Category Could Look Like

I’m not proposing we segregate AI-assisted work into some lesser category. Quite the opposite.

An AI-assisted journalism category should recognize excellence in human-AI collaboration. The criteria would include:

Impact. Did the journalism matter? AI assistance is a means, not an end.

Sophistication of collaboration. How effectively did the team use AI capabilities? Did they push the technology’s limits?

Editorial judgment. Did human journalists maintain appropriate control? Was AI used thoughtfully rather than carelessly?

Transparency. Was the AI use disclosed appropriately to audiences?

Innovation. Did the work demonstrate new approaches others can learn from?

The best AI-assisted journalism combines human editorial judgment, source relationships, and analytical thinking with AI’s ability to process information at scale. The category would recognize that combination.

Objections and Responses

I anticipate objections:

“AI is just a tool like any other.” True, but we don’t pretend all tools are equivalent. We recognize data journalism as distinct. We have multimedia categories. Tools shape what’s possible and how work gets evaluated.

“This will stigmatize AI use.” Only if we make the category seem lesser. Positioned correctly—as recognition of innovative excellence—it elevates AI-assisted work rather than segregating it.

“Soon all journalism will be AI-assisted.” Possibly. When that happens, the category may become unnecessary. For now, we’re in a transition period where recognition of the transition is valuable.

“We can’t judge AI use without technical expertise.” Judging already requires diverse expertise. Adding judges who understand AI tools isn’t fundamentally different from including technical experts in data journalism categories.

Implementation Challenges

Creating this category would require thoughtful design:

Disclosure requirements. Entries would need to describe AI use: what tools, for what purposes, with what human oversight.

Judging criteria. Clear standards for evaluating human-AI collaboration would need development.

Category scope. Would AI-assisted work also be eligible for traditional categories? I’d say yes, but with disclosure.

Training for judges. Evaluators would need guidance on assessing AI use appropriately.

Evolution. As technology changes, the category would need regular review.

None of these are insurmountable. Awards programs evolve regularly as the field changes. This is just the next evolution.

The Broader Conversation

My proposal is ultimately about transparency and acknowledgment.

Journalism is changing. AI is increasingly part of how work gets done. Pretending otherwise—in our awards, our bylines, our professional conversations—doesn’t serve anyone.

Recognition of AI-assisted journalism wouldn’t diminish human contribution. The journalists driving these collaborations are doing exceptional work. They deserve recognition that accurately reflects what they’re achieving.

And the field needs models to learn from. Celebrating excellent AI-assisted journalism helps others understand what’s possible.

Looking Forward

I’ve raised this with a few awards administrators. The responses range from interest to skepticism to concerns about practicality.

But I’m convinced we’ll get here eventually. The only question is whether awards programs lead the conversation or follow it.

Some organizations are already thinking about this. I’ve talked with these AI specialists about how other industries are handling recognition of AI-collaborative work. The patterns emerging elsewhere may inform journalism’s approach.

For now, I’m making the case publicly. Let’s have the conversation about how we recognize excellence in an era when excellence increasingly involves collaboration between human journalists and AI tools.

What I’d Want to See

If I were designing an AI-assisted journalism award today, I’d want:

Mandatory process disclosure. Entries must explain what AI tools were used and how.

Human-centered judging. Evaluate the journalism first, the collaboration second.

Innovation emphasis. Reward approaches that push the field forward.

Diverse judging panel. Include technologists alongside journalists.

Learning focus. Winners should share their methods publicly so others can learn.

The goal isn’t to create an AI showcase. It’s to recognize that excellent journalism increasingly involves human-AI collaboration, and that recognition matters.

A Call to Action

To journalism awards programs: consider this proposal seriously. The work you’re evaluating is already AI-assisted; acknowledging that doesn’t change reality, just our response to it.

To journalists doing AI-assisted work: advocate for recognition that accurately reflects your practice. The work you’re pioneering deserves celebration.

To the field broadly: let’s have honest conversations about how AI is changing our work. Awards are one small piece, but they signal what we value.

Working with partners who provide AI implementation help—I’ve seen how sophisticated these collaborations are becoming. They deserve recognition commensurate with their achievement.

The journalism is already excellent. The awards should catch up.

---

I’d love to hear from journalists who’ve done AI-assisted work and awards administrators thinking about these questions. What would meaningful recognition look like?