AI and content production has become a divisive issue, with many either lauding or demonising AI. But creating content with AI goes far beyond just slinging blog ideas into ChatGPT: use machine learning and AI tools to leverage computing power in your content and editorial strategy. Get beyond the AI hype by implementing AI in key moments in your content and editorial workflow.
We have been working with publishers to develop some AI frameworks and tools to help with publishing processes, and here are some ideas on how AI can be strategically used in content production. Work smarter with AI to improve efficiency, automation, and creativity!
Read our guide to using AI in your editorial strategy here.
Different forms of AI
We recently broke down AI in our blog, and while there are a lot of interchangeable terms and ciphers in the industry, these are probably the main forms of AI for publishers to keep in mind:
- Natural Language Processing (NLP): understanding and generating natural (human) language
- Machine Learning (ML): analysing big data and patterns, the basis for other useful AI systems such as recommendation systems (used for content personalisation)
- Generative AI Models: this is what people often mean when they talk about “AI”: systems such as ChatGPT primarily used for text generation.
Snippets, summaries, and reports
Have you already seen AI-generated summaries used by Amazon, Google, or publishers such as TripAdvisor? Seems like everybody is clamouring to maximise AI’s ability to condense and summarise information, and we can certainly see why. For busy users, an AI-generated summary is a great way to get a handle on complex content quickly.
You can use it to:
- Explain texts
- Break down concepts
- Generate sales copy
- Circulate internal information
- Enrich your catalogue
- Summarise reviews.
🪄Tip: ask users to feedback on your AI-generated copy to gauge its effectiveness.
Multilingual just got easier
One of the most exciting ways to leverage AI is to offer dynamic multilingual experiences.
We are seeing real-time translations and captions improve and become increasingly standard in our tech systems and platforms. Case in point: Google Meet recently added 52 more languages (including Swedish!) to its translated captions.
This is just another example of how big companies are using automated translation to facilitate international business. And you can do the same by plugging into their ecosystems or using your own translation plugins.
Note: Automated translation should go through editorial checks and processes.
Creative ideation, blogging & process iteration
Use tools like ChatGPT to do some of the heavy lifting for your content strategy: generative AI can be a brilliant content marketing asset. It is especially good at breaking down B2B concepts and providing concise and well-formatted posts and responses. Generative AI tools are also useful for tutorial and process-driven content.
- Use generative AI to help you with your blogging strategy. AI can help you create blog drafts and suggested post outlines.
- AI tools are very useful for content idea generation, similar to keyword research tools.
- Generative AI is also surprisingly useful in internal communications scenarios where you must break down processes.
- It is also useful for support teams who need to break down workflows and processes in clear and concise language.
- Use generative AI to get more ideas for your FAQ pages and ensure your support literature is comprehensive enough.
Improve content quality
We have been using spell-check and grammar tools in word processing for a long time, but the new NLP models we have access to today are taking things up a notch. By embedding smart AI tools into your content production process, you can help improve quality and readability.
- AI grammar and readability tools are great for creating more concise and readable copy and can be used alongside normal editorial processes.
- Leverage aggregated content and curated content to create thought-leaderships roundups, newsletters etc.
- Filtering and sorting data using AI can help you create data-informed content faster.
- Email writing tools can help with high-volume inboxes and canned responses.
Personalised content
One of the most exciting ways in which AI can impact your content strategy is its ability to personalise content. Personalisation is a great way to add value to users, though be mindful of local data collection and privacy laws.
- AI-driven content recommendations can help your users with content discovery and help improve your engagement rates.
- Content curation is a major asset in the knowledge economy, so leverage data models to offer targeted, curated content.
- User engagement can be driven by personalisation and predictive analytics. Foresee your users’ needs before they know them themselves.
Metadata, marketing, and accessibility
Metadata is key for publishers and AI tools are awesome at creating metadata at scale, e.g. image alt texts. (TimeAI plug – our family of AI products we have developed with publishers that do just that). Metadata is a major accessibility enabler, and all publishers should be taking their accessibility responsibilities seriously.
AI can also help with key marketing activities such as SEO optimisation, A/B testing etc. Smart marketing means using smart tools.
Challenges of AI
Using AI is a relatively new concept for many businesses, so best practices are still being formed and negotiated. But if you are using AI to create content, consider the following issues:
- Copyright (we wrote an entire blog on this)
- Bias: are the models you use biased? (Invariably, AI will be influenced by what is put into it. So be judicious)
- Disclosure and transparency: tell users how you use AI
- Privacy: be careful on what you collect and leverage for marketing
- Quality control: don’t rely on generative AI to do the heavy lifting when it comes to compliance etc.
- False ease: AI generated content is almost too good to be true, but being generic is not a good content strategy
- If you rely too much on AI for content creation you may lack context, nuance, and creativity, so be wary of editorial-free AI writing!
AI can be used in content production in interesting ways. Text generation is just one example: AI can also be used to collate data, curate content, automate metadata creation etc. Check out our AI for publishers services here.
Keen to learn more about AI? Check out our blog on how AI is revolutionising publishing or peruse our TimeAI products for ideas on how publishers can benefit from AI.
