I had the great pleasure of speaking at the Best of Content Marketing Conference in Vienna. Although the topic is still content marketing, I was focused on the implications of AI: what are the ramifications of AI’s on content marketing?

What is AI?

Before I went on to talk about its impact, I provided a definition to make sure that the audience and I were on the same page. AI, in the context of the presentation, is defined as “intelligence exhibited by machines.” I love that definition, short, sweet and on-point. Then, I continued to peel the onion by further defining the meaning of intelligence. What is intelligence, anyway? I am not the first person to ask that question.

In 1950, Alan Turing posed a question in the opening paragraph of his paper, Computing Machinery and Intelligence:

“I propose to consider the question, ‘Can machines think?’ Because ‘thinking’ is difficult to define…”

The levels of machine intelligence can be measured by their ability to think. Machines can “think” contextually to complete a difficult task, e.g. AlphaGo’s responses to a Go Master’s moves. Or a machine can “understand” how to respond to our questions logically and swiftly (sometimes), e.g. Siri, Alexa, and Google Home. Or a machine can drive a car and react to different driving conditions.

AI was able to make huge strides due to the massive amount of data that we’ve generated in the past several years. A fun fact: 2.5 quintillion bytes of data is created every day by 3.7 billion people on this planet.

It turns out the data we generate every day is gold. We can use a large amount of data to help machines find human-behavior patterns and train them to think and behave in a certain way. With a large amount of data and optimized algorithms for machine learning, AIs can begin to ‘think’ contextually. A great example of machine learning is for an AI to quickly differentiate the images of dogs vs. muffins. This task may be simple and easy for normal human beings, but it requires millions of samples of data to train machines to identify the right subject.

Machine Learning Images

3 Different Levels of AI

AI, in general, is classified into 3 levels:

Three Levels of AI

Narrow or weak AI:

  • Do a single task competently
  • Modify behavior when the situation changes

General AI:

  • Perform any intellectual task that humans can.
  • Capable of cognitive functions humans may have –
    in essence no different than a real human mind.
  • Understand its environment as humans would

Super AI:

  • Much smarter than the best human brains in practically every field, including artistic and scientific creativity, general wisdom and social skills

Looking at these categories, obviously, none of the current AI-based machines are at the General AI level yet. Most AI-based machines or robots still focus on completing specific tasks. If we put the 3 levels of AI in a continuum, we barely scratch the surface of AI. However, pundits predict if we ever advance to General AI, we will likely accelerate to Super AI in no time.

Machines vs. Humans: Is Content Marketing Doomed

AI in Marketing

At this time, no physical machines or robots are built to take over a human marketer’s job.

AI in current marketing comes in the form of software Bots, Marketing Assistants or Sales Agents.

AI as content marketing assistants

Heliograf

A great example is the Washington Post’s home-grown AI-based publication tool, Heliograf. Here is how it works: Editors create narrative templates for the stories, including keywords and phrases which account for different potential outcomes. Then, they hook Heliograph to credible sources of structured data. Heliograph will match the data from the template with relevant data, then merge them and publish them to different platforms.

Machines vs. Humans: Is Content Marketing Doomed

Wibbitz

USA Today is another publisher that also experiments with AI to create content. Wibbitz, an AI-driven production software, creates short videos by condensing news articles into a script with image or video footage, and even adds a synthesized newscaster voice.

Qlik

Another common example of using AI for content creation is in the field of Natural Language Generation using Narrative Science to translate structured data into texts. Image if you can plug a structured graph or data into a software program. The AI-based tool can “read” and “analyze” the data and create narratives in short, long and bullet-point formats. The automated narrative helps you find insights into your data quickly.

AI as sales agents

Conversica 

This is probably one of the best demos to showcase AI-based inside sales agents.


In this demo, the program tracks a prospect over a period of one year. The bot agent was able to create a contextual-based automated e-mail to the prospect, understand the response and follow through several times until the lead is ready to talk to a real sales person. A great example of using AI to keep track of prospects and nurture leads.

Drift

Driftbot is an AI-based chatbot for your websites. Rather than having your prospects fill out a contact form, this software helps you qualify leads through a series of simple questions, guide the customer journey on your site, and make it quick and easy for them to talk to you. Thus, it increases conversions.

Is Content Marketing Doomed?

The tools I mentioned are just a few examples of the hundreds of applications which address different stages of the sales and marketing funnels. So, are content marketing jobs on the cusp of being eliminated?

According to the Washington Post, the goal of AI-based stories is to target many small audiences with a huge number of automated stories about niche or local topics. It’s not about replacing their star reporters, but rather using AI generated stories help them cultivate niche audiences.

All the tools I mentioned help improve efficiency and increase productivity. In the near future, AI-based marketing tools will focus on specific tasks of sales and marketing to make marketers’ lives easier. Like other technologies, it still needs humans to set up the processes, conduct quality checks, and connect different tools and technologies together. Humans still need to take over implementations at some points. No AI or bots can do it all from end-to-end YET.

Machines vs. Humans: Is Content Marketing Doomed

As AI’s utility continues to grow, we, as marketers, should also continue to learn and develop new skillsets to take advantage of new marketing fields emerge, such as AR/VR production, Voice Recognition and more

The machines continue to learn, and so should we; if we are concerned about our own jobs.

I had a great time in Vienna. It was a lot of fun talking about the future of marketing with fellow marketers from Germany, Austria, Norway, Switzerland and Slovenia. In my upcoming new book, Effective Sales Enablement, I discussed extensively about technology’s role in sales and marketing. Check out the chapter outline in this post.

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