AI bootcamps, workshops, and hackathons – there's a lot of behind-the-scenes work on AI adoption happening right now with publishers I've been talking to across North America and Europe.
From an inside view, I've seen proactive publishers prioritizing AI education for all in the newsroom. They are equipping their teams with basic generative AI literacy and how to apply it ethically. These crash courses are helping break down silos and spark creative collaboration on potential use cases.
Building organizational AI fluency is a crucial step. We are going to be living and reporting in a world driven by AI. With generative AI being so accessible, we owe it to our audiences to not only experiment with it for potential products but, more broadly, as informed citizens.
Last fall, I spoke with Aliya Itzkowitz and Sam Gould of FT Strategies as they prepared for an intensive AI Design Sprint Day which gathered nearly 20 publishers to collectively brainstorm and strategize AI opportunities and use cases in their newsrooms.
Now that it has concluded, I wanted to hear how they helped publishers move towards AI experimentation and implementation.
In part one of this two-part episode, we delve into the AI sprint's dynamics and the use cases publishers identified, exploring their AI adoption progress.
Aliya is a manager at FT Strategies, where she has consulted over 30 publishers globally on the critical shifts facing publishers today, including rethinking revenue models and understanding how to leverage AI. Before the FT, she worked at Dataminr, bringing AI technology to newsrooms, and at Bloomberg as a journalist. Aliya has a BA from Harvard University and an MBA from the University of Oxford.
Sam is a data scientist at FT Strategies, where he helps clients solve strategic business challenges using data. He has helped organizations across different sectors define their AI strategies and build data systems. Sam designed the FT Strategies AI Design Sprint methodology working in partnership with the Google News Initiative.
From this conversation, here are my top 3 takeaways on AI strategy for publishers:
1️⃣ Start experimenting with generative AI: The chat nature of generative AI makes it accessible to see what's possible and allows publishers to rapidly build prototypes attuned to their business needs and data. Early hands-on testing enables discovering high-potential AI applications and understanding the limitations of AI.
2️⃣ Prioritize educating staff comprehensively on AI: Before implementation, teams must receive training on AI's technical, strategic, and ethical dimensions. A well-informed team can better identify relevant AI opportunities and implement solutions effectively.
3️⃣ Champion ethical AI use and information quality: Emphasize ethics as AI permeates operations - evaluating algorithmic biases, addressing information quality issues like hallucinations, and determining appropriate vs inappropriate uses of AI.
Join us in the next episode for an insightful discussion on the emerging prospects of multimodal AI and the role of AI agents for publishers