Argument 1: The Necessity of Cross-Functional Teams to Drive Innovation
Connelly’s first and perhaps most emphasized argument is that the traditional, siloed structure of media organizations is the primary barrier to solving complex problems and that the solution lies in the implementation of cross-functional teams. She argues that innovation cannot be the sole responsibility of a specific “newsroom,” “business team,” or “product team.” Instead, the most effective way to tackle disruptors—whether they be new audience segments, platform shifts like video, or technologies like AI—is to dismantle these distinctions and create unified “innovation pods” or “task forces.”
The rationale behind this argument is rooted in the complexity of modern media challenges. Connelly suggests that when a problem is isolated to a single department, the solution is often limited by the specific skillset and biases of that department. However, when a team is composed of individuals from product, subscription, and editorial backgrounds, their diverse skills and perspectives combine to create solutions that are not only more innovative but also more holistic. She explicitly states that these mixed teams, “pulled away from their core functionalities,” are able to generate better outcomes than any solo team could achieve.
A significant portion of this argument focuses on the psychology of the newsroom, which Connelly identifies as the “toughest part of business to change.” She argues that newsrooms are naturally resistant to corporate structures or business-led initiatives. To overcome this, she proposes a reframing strategy: reminding journalists that they are already cross-functional by nature. By drawing parallels between a new cross-functional initiative and standard journalistic practices—such as a print reporter collaborating with an audio journalist, or two different desks (e.g., politics and business) collaborating on a story about corporate corruption—leaders can lower the psychological barrier to entry. Connelly contends that normalizing “dual reporting structures” and “ad hoc teams” transforms the frightening prospect of business reorganization into a familiar, mission-driven workflow.
She supports this argument with the case study of the “Style Sessions” at the Washington Post. This initiative, which involved partnering with a local museum to interview high-profile figures like Christopher Nolan, was not merely an editorial event. It required the subscription team to be at the table from the very beginning to decide on invite lists and revenue models (free vs. charged). The result of this cross-functional collaboration was the most diverse young audience the Post had ever convened, proving that when business goals (subscriptions) and editorial goals (high-quality interviews) are aligned through cross-functional teamwork, the outcome exceeds what either could achieve alone.
Argument 2: Establishing “The Why” to Align Technology with Journalistic Mission
Connelly’s second core argument is that implementing new technology or strategies must start with a clear articulation of “the why,” specifically grounded in journalistic values rather than purely business imperatives. She posits that simply telling a newsroom that “AI is the problem” or “we need younger audiences” is insufficient to motivate behavioral change. Instead, leaders must articulate why journalists are uniquely positioned to solve these problems and how doing so serves their core mission of holding power to account and delivering facts.
This argument addresses the cultural friction that often arises when newsrooms are asked to adopt new technologies. Connelly suggests that if the directive is framed solely as a business necessity or a “keep up with the trends” mandate, it will be met with skepticism. However, if leadership frames the adoption of a new technology (like AI) as a tool that enhances the journalist’s ability to care for facts and serve audiences, it taps into the intrinsic motivation of the staff. She argues for a narrative that says, “We as journalists are prepared to tackle AI because we care about facts.” This empowers the team, making them feel that their specific skills—verification, storytelling, inquiry—are assets in the new landscape, rather than liabilities.
Connelly emphasizes that this alignment cannot be an afterthought; it must be established at the inception of any project. The “why” serves as the North Star that guides the project through difficulties. It transforms the adoption of technology from a passive requirement into an active pursuit of better journalism. She argues that when journalists understand that a new platform or tool improves their ability to “report the facts” or “hold power to account,” they engage with it “with a purpose.”
This argument is illustrated through the example of the Washington Post’s launch on Twitch in 2018. Connelly notes that the decision to launch wasn’t just about using a new platform; it was tied to a specific journalistic moment—Mark Zuckerberg testifying on Capitol Hill. The team realized that this was a “news moment” that required a specific type of live, interactive engagement that Twitch offered. By connecting the platform (Twitch) to the journalistic need (covering a major political/tech hearing live), the technology became a vehicle for the mission, validating the argument that technology must serve the story, not the other way around.
Argument 3: Tactical Operationalization and the Bottom-Up Adoption of AI
The final core argument aggregates Connelly’s specific tactical recommendations for managing innovation, with a particular focus on how these tactics apply to the current disruption of Artificial Intelligence. She argues that high-level strategy and cross-functional teams are useless without a rigorous operational framework consisting of three pillars: business-aligned metrics, radical transparency, and executive sponsorship. Furthermore, she argues that for AI specifically, adoption must be bottom-up (user-led) rather than top-down (CEO-led), and that AI should be viewed as a “question engine” rather than just an answer generator.
Regarding the operational pillars, Connelly insists that innovative work must be measured against the “oldest, most entrenched” business goals of the organization. It is not enough to have “innovation metrics”; the new work must “ladder up” to core business objectives to prove its value to the wider organization. Secondly, she argues against the “skunkworks” model where innovation teams work in secret. She advocates for “regular public share office hours” to ensure the culture shifts slowly day by day, allowing the broader organization to participate in the journey. Thirdly, she emphasizes the need for “executive sponsorship.” Innovation teams cannot do the work and fight for the budget and navigate internal politics simultaneously. A designated executive must handle the bureaucratic friction, freeing the team to focus on the work itself.
Connelly applies a specific lens to AI, arguing that it represents the “final problem.” She references a Bloomberg article to support her claim that while CEOs can mandate AI usage, true adoption only happens when “super users” within the organization share how the tool actually helps them in their daily work. This bottom-up approach mirrors her earlier point about cross-functional collaboration—it relies on peer-to-peer influence rather than administrative fiat.
She further elaborates on AI through the concept of the “question engine,” referencing Shuei Feng from the Shorenstein Center. Connelly argues that AI is changing how audiences engage with information, shifting from passive consumption of answers to an active process of asking questions. This implies that news organizations need to rethink their product not just as a delivery mechanism for articles, but as a utility that helps audiences interrogate the world. This supports her case study of “Ask the Post,” which began as a partnership between the product team and the climate desk. By starting small with a specific editorial need (climate change queries) and a specific desk, they were able to build a tool that eventually scaled, proving that successful AI strategy is iterative, collaborative, and deeply integrated with editorial needs.