Boosting editorial productivity in the existing workflows

37 out of the 40 news and magazine businesses I spoke to in 2024 said they are prioritizing editorial productivity as the key use case to harness AI. Only 2 out of those 37 have been able to create something that their team was able to use! Why?

Here are some quotes that throw some light

• "Playing with tools like Chat GPT, Claude and Gemini is easy but the use case is usually 'Curiosity' without a real understanding of the tangible value"
• "It's impossible to make our team use these tools as they are not part of the existing workflow. Even if someone champions usage, it's difficult to convince the majority of the team to use it."
• "There are so many options, so many vendors, and so much noise in the market! Whenever we think we have an idea of how to proceed, there is some news about a newer shinier object that distracts the team and disrupts any progress we have made."

In this edition, I will discuss what areas of a typical content workflow can benefit from AI, how to adopt AI tech in those areas, and what to consider before jumping in

Through over 400 AI experiments conducted with editors globally, I have identified key AI tools that significantly improve the efficiency of newsrooms, magazines, and other information businesses.

I found there are 3 areas to boost productivity

• Content Discovery and Drafting
• Content Analysis
• Content Distribution

To be clear, there is no silver bullet here. I outline different "AI Assistants" that can build productivity for a content team in an information business. The best way to find the right assistant would be to evaluate the current processes and find out where the productivity will create maximum value and, more importantly, will be accepted by the team.

What is an AI Assistant?

An AI assistant, often referred to as an AI agent, uses AI technologies such as Generative AI, data analytics, and natural language processing to enhance editorial productivity. These assistants can assist writers and editors by suggesting content ideas, correcting grammar and style, summarizing large texts, providing real-time feedback on writing quality, drafting research materials, and optimizing content for SEO. By automating repetitive tasks and offering intelligent insights, AI assistants help editorial teams focus on creative and strategic aspects, thereby increasing overall efficiency and productivity in content creation and publication.

Content Discovery / Drafting: Streamlining the Creative Process

• Monitor a Topic Assistant: This assistant monitors real-time trends and compiles relevant data, enabling editors to produce timely and engaging content. Taking one step further, this assistant can also create personalized drafts to the publication's style. This reduces the initial drafting time significantly. An example prototype that Bridged created can be seen below

• Redaction Assistant: Compliance with editorial and regulatory guidelines is a major concern. The Redaction Assistant automatically checks for guideline violations and suggests precise corrections. This ensures articles meet standards without extensive manual review, saving both time and effort.

• News Fusion Assistant: When covering complex stories, editors need to synthesize information from various sources. This Assistant combines data from URLs (such as press releases), documents, and other formats to create comprehensive drafts. It maintains consistency in voice and style, facilitating a more efficient content creation process.
• Data to Article Assistant: Producing articles from data such as weather reports, sports results, market reports, etc. can be data-intensive. This Assistant generates articles by analyzing data using AI such as creating weather analysis using historical and forecasted weather data, creating match previews using the latest results, player ratings, and news, etc.
• Sports Preview Agent: Sports editors need to provide up-to-date previews for upcoming matches. This agent compiles the latest results, player ratings, and news, creating drafts that align with the publication's style. It helps in delivering timely and accurate sports content.

If you are looking to explore any of the assistants I have mentioned, above or below, just comment "Explore" and I will send you a cheatsheet on how you can build the assistant or even a prototype!        

Content Distribution: Enhancing Reach and Visibility

• SEO Content Optimization Assistant: To maximize online presence, articles need to be SEO-friendly. This Assistant generates optimized titles, meta descriptions, and relevant keywords. It benchmarks articles against top-ranking competitors, ensuring higher visibility and engagement in search results.

• Summary Generation Assistant: Readers today prefer concise summaries. This Assistant creates engaging summaries from full-length articles, adaptable to various formats like bullet points or social media snippets. It enhances reader engagement by providing quick, digestible content.
• Google Discover Assistant: Optimizing content for Google Discover requires a unique approach. Similar to the SEO Assistant, this tool enhances articles to meet the specific criteria of Google Discover, broadening the reach and attracting more readers.

Content Analysis: Gaining Insights and Ensuring Quality

• Hotspot Finder Assistant: Understanding reader engagement is crucial. This Assistant predicts where readers will spend the most time, allowing editors to focus on these sections. It helps in crafting more compelling and targeted content.

• Plagiarism Checker: PlagiarisNLPm can undermine a publication's credibility. This Assistant checks for any unauthorized copying of content, ensuring that all articles are original and trustworthy.
• Insights Generator: Identifying what works best with your audience can drive higher engagement. This Assistant analyzes various content aspects—tags, authors, tone, style, and length—and correlates them with engagement metrics. Editors can use these insights to refine their content strategy.

Considerations Before Starting

Evaluating Compatibility and Integration: Before implementing AI tools, assess the compatibility of these tools with your existing editorial systems and workflows. Consider how the tools will integrate with your CMS, editorial calendar, and other software to ensure a smooth transition without disrupting current operations. Ensure data privacy and security measures are in place to protect sensitive information.

Building Team Readiness and Buy-In: Successful implementation requires buy-in from the editorial team. Engage editors early in the process, highlighting the benefits of AI tools and addressing any concerns they may have. Provide comprehensive training to help staff become comfortable with the new technology. Encouraging feedback and involving the team in the pilot testing phase can foster a sense of ownership and ease the transition.

Defining Clear Objectives and Metrics: Establish clear, measurable goals for what you want to achieve with AI tools. Define specific objectives, such as improving content quality, increasing production speed, or enhancing reader engagement. Develop metrics to monitor progress and measure the impact of the AI tools on your editorial processes. Regularly review these metrics and be prepared to make adjustments to optimize the use of AI in your workflow.

About Me

I am an experienced entrepreneur who has worked in Media and Tech consulting for many years. Apart from being a full-time parent, I am also leading a project that aims to make AI more accessible to level the playing field between tech vendors and digital publishers in the Media ecosystem. Bridged’s out-of-the-box agents eliminate the need for extensive data processing or dedicated AI resources, making AI adoption accessible and efficient.