Artificial Intelligence Fact Sheet

Artificial intelligence may be at a tipping point. With the launch of artificial intelligence company OpenAI’s ChatGPT at the end of 2022, more people are talking about and using AI than ever before. ChatGPT had one million users just five days after it opened to the public. Let’s take a closer look at the current facts related to artificial intelligence. 

What Is Generative AI? And, What Other Types of AI Are There?

ChatGPT is an example of generative AI. That means you can use it to create new content. With generative AI, users can create content, including code, writing, or imagery. 

But organizations are developing and using AI in many ways, beyond novel content generation. AI uses computer systems to do tasks that typically only humans have been able to do. According to IBM: 

Artificial intelligence leverages computers and machines to mimic the problem-solving and decision-making capabilities of the human mind. 

AI can be trained to do specific tasks or, as with ChatGPT, can be built to think and act as a human would using a type of AI called machine learning. Machine learning is a booming field. Other powerful machine-learning programs include:

• DALL-E, which creates images and art based on a description and also comes from OpenAI.
• Deepmind, which is a subsidiary of Alphabet.
• Make-A-Video, which is from Meta. 

Content Science lists 17 different AI tools in its latest Content Technology Landscape infographic. These tools can help you write, edit, and create video and imagery. 

So what does all of this mean for content professionals? Explore the following facts to find out. 

The State of AI

VC fund and accelerator Antler recently mapped the generative AI field and list nearly 200 different tools. And, that’s just generative AI. McKinsey finds that “the average number of AI capabilities that organizations use, such as natural-language generation and computer vision, has doubled—from 1.9 in 2018 to 3.8 in 2022.” 

More companies are adopting AI. “AI adoption continued at a stable pace in 2022, with more than a third of companies (35%) reporting the use of AI in their business, a four-point increase from 2021.” — IBM

Majority of companies say they have started automation initiatives. Seventy-three percent of executives say their organizations have embarked on a path to intelligent automation, up 58% from 2019. Those organizations range from piloting, with 1 to 10 automations (37%), to scaling, with 51 or more automations (13%). — Deloitte

Much more to come from ChatGPT. Microsoft has committed billions to OpenAI. “Microsoft’s partnership enables it to capitalize on OpenAI’s technology. Microsoft’s supercomputers are helping to power the startup’s energy-hungry AI systems, while the Redmond, Washington-based tech giant will be able to further integrate OpenAI technology into Microsoft products.” — Associated Press

How Content Marketers Use AI

The release of ChatGPT has unleashed enormous potential for using AI in the content industry. But even before ChatGPT came on the scene, content professionals were increasing the use of AI in their operations. 

Number of organizations using AI for content is increasing. Twenty-two percent of organizations are using AI or machine learning in some capacity related to content. This is up from 15% in our 2017 study. — Content Science, Content Operations Study

Marketers lean on AI for customer data. Marketing and sales professionals are most likely to be using AI for customer service analytics and customer segmentation. — McKinsey

AI and the Content Job Market 

Although the launch of ChatGPT unleashed a wave of predictions about the end of certain kinds of jobs, AI is far from ready to replace us all. In fact, AI will open up more opportunities for people to do their jobs faster and more efficiently. 

Is the era of the “prompt engineer” coming? “To use generative AI effectively, you still need human involvement at both the beginning and the end of the process,” write two AI experts in Harvard Business Review. — Harvard Business Review

To start with, a human must enter a prompt into a generative model in order to have it create content. Generally speaking, creative prompts yield creative outputs. “Prompt engineer” is likely to become an established profession, at least until the next generation of even smarter AI emerges. …Then, once a model generates content, it will need to be evaluated and edited carefully by a human.

AI may take you to 80% complete when it comes to content creation. “Artificial intelligence is living up to its potential for content. These tools can accelerate creating content at a high level of quality. I think of it as these tools take you to 80% complete, leaving you with about 20% to do…usually final polishing or refinement. — Content Science Review, 4 Content Technology Trends to Watch

Generative AI will bring new opportunities. “While some creatives may be replaced by Gen-AI systems, others may find new opportunities to work with these systems or to create content that is enabled by Gen-AI. In many cases, it may actually enhance the work of creatives by enabling them to create more personalized or unique content, or to generate new ideas and concepts that may not have been possible without the use of AI.” — Mapping the Generative AI Landscsape, Antler 

How to know when you’re ready for AI. “Your content maturity level can help you figure out when and how to start your AI experiments. Knowing your level means you have identified weaknesses in your content ops, which can give you a roadmap for improvement, whether you decide to pursue AI or not.” — The content marketer’s guide to AI and content maturity

Content professionals see AI writing tech as a partner. “Content marketing specialists use AI writing assistants to make sure their writing is engaging and written in a consistent brand voice across platforms, including websites, blogs, and social media. In addition to editing, some AI writing tools help with SEO strategy. We foresee AI-powered technology continuing to help people at work and in their daily lives. We believe AI should help people, not replace them.” — Content Science Review, What an AI Writing Assistant Can Do for You: A Q&A With Writer’s Director of Content

Bottom Line

The AI technology space is exploding. Companies and organizations worldwide, including tech giant Microsoft, are spending billions to turn artificial intelligence technology into practical tools and services. 

Of course, many AI tools and services are already here. Google’s RankBrain uses machine learning to determine the most relevant results to search queries, intelligent chatbots handle steadily more customer service queries, and Amazon’s Alexa uses complex natural language processing (NLP) technology to understand what you’re saying. Using AI, content professionals can better understand their audience, improve user experience, increase productivity, and select more effective content strategies.

And, as the sophistication and ability of artificial intelligence grows, so too does that of content intelligence. Together, these two fields can produce higher content ROI through areas such as content creation and hyperpersonalized content. 

Putting your head in the sand will not make this reality disappear or pause, so it’s imperative business leaders prepare for this new wave of change. Proper content engineering is a crucial aspect of preparing for the impact artificial intelligence will have on every organization, and Content Science CEO Colleen Jones points to nine content engineering activities teams can start or ramp up:

1. Modeling content structures, schemas, and semantics
2. Architecting content using taxonomies and other metadata magic
3. Designing content delivery
4. CEM lifecycle planning (including when to archive!) and implementation specifications
5. Marketing automation workflow planning
6. Designing content management workflows, reporting, and user support services
7. Content reuse planning, adaptive content strategy, and content personalization architecture
8. Audience- and session-based analytics personalization rules and scoring, validating content targeting against user task success
9. Multisite content syndication and content API definitions

Laying this foundation now will help your organization prepare for the AI future.