Sorry for the spoiler, but the simple answer to the question is yes — artificial intelligence can absolutely make you a faster writer. There’s little doubt that AI-driven tools and platforms are able to speed up most aspects of the editorial creation process.
Just think how easy it is nowadays to auto-correct text, to validate facts, or search for synonyms online. It used to take serious time and effort to thumb through dictionaries, encyclopedias, and thesauruses. This information, digitally stored in the cloud, is now delivered at lightning speed through our devices.
So the question isn’t whether AI can save you time in the editorial process — it’s more about how artificial intelligence impacts different stages of the content creation process, and what you do with the time it frees up. And the research on this point is interesting.
Reinvesting the gains
For the most part, content creators appear to be investing time savings back into the editorial process—rather than speeding up and finishing faster, bloggers are spending longer on their blogs than ever before.
The data is clear. Results from Orbit Media’s 2017 survey of bloggers found the average time spent creating a blog post was 3 hours 20 minutes, an increase of approximately 40% since 2014. By a similar measure, the average blog post in the 2017 survey came in at 1142 words, also increasing by around 40% from three years earlier. The heyday of the short post is gone.
So the time savings derived from advances in technology—if only from improvements in semantic search and word processor functionality—are being invested back into the content on a surprisingly consistent basis. But why?
The gravitation toward longer blogs in recent years has certainly something to do with search engines increasingly rewarding extended content. In a city of tall buildings, you need to build your structure higher than the others to stand out.
One further thesis is that blog posts are getting longer because it has simply become easier to compose a lengthy article than it was a decade ago.
Think about it for a moment—importing new material and adding visual media into your word processor is “plug and play” nowadays in most content management systems. And for every new element you add, there’s an opportunity for further comment. Bloggers are continually encouraged by the system to make their pieces longer.
Compounding this, nobody is really telling the writer when to stop. Sure, there might be a word count of sorts. But, unlike print, there is no fixed endpoint for digital articles. Once you start writing, you could theoretically go on forever. Not that we would advise that, of course.
Whatever happened to writer’s block?
Once upon a time, writers would script movies and pen books about not being able to write. French novelist Flaubert used to famously agonize for hours over a single word. Writer’s block was a thing even not so long ago, but we seem to be hearing less about it these days.
Why might that be? For one, the process of getting started on your creative work is increasingly painless. Numerous topic analysis tools are available to help get your content research underway, while advances in natural language processing are enabling machine learning platforms to generate deep research at the click of a button. Editorial AI is like a personal assistant, gently nudging, suggesting, and prodding you along the way.
It’s also easier than ever to work with others on editorial projects. If the typewriter was an island technology, the personal computer and the internet moved everyone a step closer together.
Since the advent of cloud technology, the floodgates have opened. Digital solutions support every aspect of creative collaboration from ideation and scheduling through development and review.
There has been a similar proliferation in the available tools for optimizing, repurposing, scaling, personalizing, and distributing content both within domestic markets and internationally across languages. As part of the ongoing explosion of martech platforms, AI-led tools can schedule social posts for optimal times, uncover traits of top-ranking content, AB-test landing pages, and manage paid search and paid social campaigns. They can offer live recommendations on improving content performance, assist with design and pagination, and automatically recognize images. IBM Watson, for one, is on a mission to hoover up all the unstructured data on the internet and give it form.
What this all means is that it is easier than ever to produce insightful, engaging content supported by AI. At the same time, this has had the parallel effect of making it even more difficult for your content to stand out from the crowd. Experts have talked for several years now about the requirement for 10x content and the almost Herculean levels of effort needed to differentiate your editorial.
Human versus machine
And it is not as though creative jobs are beyond the reach of the machines. Many aspects of the content and copywriter’s job are already subject to some degree of automation.
The Associated Press has long used AI writing technology to produce data-heavy sports and financial reporting, and NLP firms are working hard and fast to offer organizations AI solutions for automated report writing.
Or look at advertising copy. In launching its proprietary AI copywriter, retail giant Alibaba insisted that the introduction of the technology would allow advertising creatives to spend more time on higher-end analysis and tasks. “Copywriters will shift from thinking up copy—one line at a time—to choosing the best out of many machine-generated options, largely improving efficiency,” the company said in a statement.
Nancy A. Shenker, founder and CEO of marketing firm theONswitch, expects AI technology to play a growing role in content development in the coming years. “My estimate is that 50% of all content will be developed by machines, with oversight and editing by humans,” , she told EContent Magazine. “Artificial intelligence will recommend topics based on trends, gather facts—and validate them—and assemble very tight posts and suggested graphics based on those combinations.” Flesh and blood creatives will add “soul and humor as needed,” according to Shenker.
Can machines get creative?
The march of AI is inevitable. 2017 research from McKinsey found that across the global workforce approximately 50% of “current work activities are technically automatable by adapting currently demonstrated technologies.”
As always, the critical question is how we harness advances in technology to our collective betterment or ill.
For now, the reality is that humans are not getting sidelined in the creative process. Some might say we are even entering a golden age of AI-assisted creative.
While AI is great at aggregating data, identifying patterns, and generating recommendations, it is not so good yet at coming up with original, well-edited, and emotionally engaging material that helps your content stand out.
The oversight of strategy in content development—why we create what we are create and how the content maps to broader commercial objectives—remains a fundamentally human domain, at least for the time being.
Similarly, the ability to induce an emotional response from a piece of content, or to decide whether something is fit or not to publish, continue to rely on human judgement.
Throw into your content some proprietary research, take a standpoint on your topic, and inject some voice and style, and you’re doing things that machines still find difficult.
The interplay between human and machine is fluid, fast-moving, and fascinating. An architect who uses 4-D CAD visualization is still 100% an architect and a carpenter who deploys AI to determine the best way to sequence a home-building project based on local weather conditions is still 100% a carpenter. They are just using better tools than were previously available.
And so it goes with writers and other creative professionals. Write faster, write harder, write better.