What Happened To AI Taking Over The World? 

Is the AI hype diminishing? 

At the start of the Artificial Intelligence (AI) boom, humanity both celebrated and feared what might happen with rapidly expanding technologies. Goldman Sachs even predicted that 300 million jobs would be lost or degraded due to AI. It’s a hot and controversial question; can artificial intelligence take over the world? 

Fast forward to now and we’re seeing that these attitudes are still reflected in the data. But the data shows conflicted feelings towards AI. For example, 30% of workers worldwide fear that AI might replace their jobs within the next three years. And yet 81% of office workers report that AI improves their overall work performance. It seems like we’re loving what it can do now, but we’re still nervous about where this technology will head in the future. 

A report by Gartner said that most generative AI technologies are either reaching their highest expectations or still in need of improvement. The report said that most of these technologies will be fully useful in two to five years. Where there are many promising prototypes of generative AI products, using them in the real world hasn’t always been very successful. A recent study by the American think tank RAND showed that 80% of AI projects fail, which is more than double the rate for non-AI projects, or those using AI-washing in their marketing.

As a result the AI hype is diminishing slightly, but it’s made room for asking more useful questions: How do we use AI effectively, within our workplaces? What does it look like with the tools we currently have today and our current business goals? 

Using AI effectively means reducing risk

PwC’s Trust Survey asked 500 executives about the risks they prioritize in their company. The results suggested that many business leaders don’t fully grasp the challenges posed by generative AI, such as offensive or misleading content, deep fakes, inaccurate information, exposure of stakeholders’ identity, and illegal reproduction of copyrighted material.

There’s one thing all these risks have in common; and it’s that they manifest themselves in content supply chains where there isn’t content governance. First and foremost, using AI effectively means balancing the innovation it brings with internal regulation to keep things transparent and compliant with your brand standards and industry regulations. 

So let’s explore the ways in which you can strategically add AI into your enterprise content supply chain. From boosting writer productivity to keeping LLM-generated content in line with your content standards – we’ll firstly look at all the ways you can use AI as a collaborative co-writer to boost the quality of your work, without introducing communication risks. 

Use AI as a co-writing companion 

Research suggests that collaborating with AI in content marketing leads to a 68% higher ROI. But AI still requires human help. By incorporating human judgment and expertise, you maintain your agency and control over AI output. Don’t be tempted to delegate everything to AI! 

Why? Because AI generates answers that can be plausible and satisfying – but incorrect. If quizzed as to why it gave that output, AI can also justify the wrong answer, which can make it tricky to spot these erroneous generated concepts. Provide critical oversight with your own critical thinking skills and keep you from being overly compliant to a tool you don’t yet fully understand, until you do. 

Instead, use AI as a co-writer that you collaborate with, with you as the expert in your field. The goal is to leverage the strengths of both human creativity and AI’s more analytic capabilities. Here are some suggestions for what that might look like in your content workflows:

Content development stage	Example of AI-contribution	Example of human contribution
Streamlining research and gathering data	When creating an in-depth report on market analysis for renewable energy, use an AI research assistant like IBM Watson Discovery to gather the latest industry data, statistics, and trends.	Verify facts and cross-reference with other sources that you’ve found manually and deem credible sources of information.  Use this data to synthesize insights that demonstrate your company’s unique thought leadership style, and only present the facts that are relevant to your business strategy.
Developing story and messaging	When developing a case study on AI integration in supply chain management, you might use AI to generate a storyline.  For example, use OpenAIs GPT to prompt for a suggestion faced by a fictional company, followed by a description of the AI implementation process, and concluding with measurable outcomes.	Use your best judgment to select the most compelling structure and refine it to align with your brand’s voice and specific use case examples.  Or you might use this example to generate a customer survey, to interview your customers with a greater understanding of what you might ask to better understand their challenges.
Maintaining style consistency	While drafting a whitepaper on emerging trends in financial services, check your content with a solution like Acrolinx.  The AI can recommend more precise, clear language, and make sure your tone is appropriate for your audience. It also aligns your writing to your brand’s standards and speeds up editing and review.	While Acrolinx is the expert of your style guide, you’re still the subject matter expert.  Human writers bring a deeper understanding of the context of your enterprise, product, and the nuanced ways you communicate to different target audiences, so it’s important you stay in the loop.

Acrolinx – balancing creativity with governance

Acrolinx can be used as a co-writing companion for writers by providing real-time writing assistance, generating ideas, enhancing creativity, and improving efficiency. All while safeguarding your content against communication risks with AI guardrails for your content standards. That way, there’s no way AI is taking over the world of your enterprise content!

Leadership should implement Acrolinx as part of their strategy to implement AI in their workflows because it helps to enhance content quality, maintain brand consistency, and increase productivity with fewer resources. Using Acrolinx can also lead to better collaboration between writers and AI, resulting in greater compliance with regulatory standards and improved content performance.

How does it work? Generative AI from Acrolinx uses your content guidelines to make sure generated content meets your enterprise’s standards. Acrolinx checks both human and AI-generated content against your corporate writing standards. 

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With over 87% of content issues covered with one-click replacements, Acrolinx makes sure corrections meet enterprise standards. Generated content uses your established rules to generate content replacements. Writers are now fixing complex clarity issues in seconds as opposed to several minutes.

AI Assistant

Generate new ideas, expand on existing topics, summarize complex content, and more. The Acrolinx AI Assistant generates content for your writers, checks that content for quality, adjusts the generated content before presenting it to the writer, and scores that content based on your writing standards. 

Writers are guided to create high-quality content with additional automation options to check large repositories for quality issues. And quality gates that block poor quality content from accidentally being published.