Artificial intelligence (AI) is eating the world, one boring, routine task at a time.
From navigation apps using AI to crunch a bunch of data at a super-fast speed to determine the best and fastest route from A to B, or automatic spam filters and categorizations that make email more manageable, AI is truly ubiquitous.
It was only a matter of time before AI applications in the content management space arose. And when it comes to content ops, the combination of content management and artificial intelligence is a great tool for giving workers back the time they need to perform more complex tasks that still require a human brain.
The state of play – how content management and AI are already impacting Content Ops
AI excels at ‘understanding’ vast pools of data and automating routine tasks. This is typically orientated towards objectives of improving consumer experiences, saving the time and money invested in routine processes, and even exposing patterns that can uncover new revenue opportunities.
These are typically seen in a content operations workflow in four areas:
1. Smart Content Analysis
AI can analyze a piece of content to identify its sentiment and overall tone, very quickly. This is important for helping content managers determine whether a piece of content is right for their audience or if it needs tweaking before it will truly engage the intended consumer. IBM Watson, for example, uses AI to automate content categorization, text labeling, sentiment analysis, keyword extraction, and more.
2. Automatic Image Tagging
A picture still tells a thousand words. Images enhance content increase engagement. Unfortunately, there is almost nothing less engaging for workers than manually tagging image after image for search and SEO purposes. But it is still a supremely important task. And that is what makes it a great job for AI.
AI-powered automated image recognition is now smart enough to tag images in a matter of seconds—letting content workers get back to deeper work instead of routine classification.
3. Scalable Personalisation and Predictions
AI also brings scalability to another important but nearly impossible task for human staff: tracking and making use of individual user behavior.
AI can automate the process of watching what each user on a website or app is doing simultaneously. Then, it can compile this data to look for patterns that will help it predict, based on past behavior, what each user might want next.
This information can dramatically improve personalization efforts, from serving dynamic content to making product recommendations and more. And improving personalization has never been more important. In the words of the management consulting firm McKinsey, “Personalization will be the prime driver of marketing success within five years.” In fact, they found that leaders in personalization were already able to increase revenue by 5 to 15 percent and improve efficiency on marketing spend by 10 to 30 percent. Achieving that kind of improvement automatically is a massive competitive advantage.
4. Time-Saving Content Creation Assistance
Controversially, AI can also be a big help when it comes to creating content.
Whilst artificial intelligence still is not great at coming up with original ideas or creating nuanced pieces of content, it is catching up fast. A well-trained AI tool should be able to contribute to straightforward writing projects such as news articles, factual reports, translations, transcriptions, and editing for accuracy.
At present, in the content creation workflow, AI is basically a tool for improving the ROI on content marketing, which can often be resource-intensive. Simply put, AI can do the legwork when it comes to research and data while human writers can take this material and do the deep work required to create high-value, relevant content for each target customer.
The shape of things to come
Based on these areas in which content management and artificial intelligence are already coming together to improve content operations, AI may improve marketing even more in the future.
Interactions Between AI Tools
AI interactions already abound in the consumer space. A voice-activated smart speaker to controlling house lights or audio is an everyday example. Similar interactions are in store for the future of AI-powered tools in the content operations space. It is only a matter of time before AI-enabled content management systems (CMSs) and other content platforms and tools will be able to interact with each other in smart, automatic ways to provide faster functionality and better experiences for consumers and marketers alike.
On-the-Spot SEO Improvements
Taking the idea of sentiment analysis one step further, soon AI-enabled CMSs may be able to identify opportunities for SEO improvements in real-time. This capability would empower marketing professionals to create more effective content in less time, which will outperform competitors and rank better in search engines.
Content Gap Identification
Whilst AI may not create great content on its own, it can spot a lack of it – especially if it has access to huge pools of data on customer behavior preferences. This can then alert a business to where its content may be lacking (or where competitors’ content may be lacking).
Both situations are a huge opportunity to fill those “gaps” and capture more traffic. AI is becoming smart enough to flag gaps and make recommendations so businesses can create fresh content that adds value and generates new leads.
Customer Service Automations
Customer service is another expensive yet necessary element of business. Chatbots have already come to the for as a way of reducing both the time and money needed to deliver customer service excellence.
While many of today’s chatbots can address very simple questions with answers pulled from a knowledge base, the future will see a large percentage of queries – if not the majority – that do not have to be routed back to human agents. After all, it is the instantaneous and round-the-clock support that consumers are truly looking for when interacting with brand chatbots.
Bridging the gap – going headless
At the heart of this evolution from where AI and content management is today to where it could be tomorrow, is the need to integrate content management systems with an array of new technologies driven by AI.
In practical terms that means developing headless architectures that will enable content operations teams to explore and exploit everything from automated content analysis to smart content creation. Adopting this strategy will leave a business ready to capitalize on the next wave of AI-based innovation with minimal disruption, driving return on investment.
Varia Makagonova, director of marketing, Contentstack