Only 2 out of 3 People Are Using Generative AI Effectively
Among business owners and freelancers who say they “use generative AI at work,” a surprising 36.5% are not leveraging it for publishing or updating web pages. This unexpected reality emerged from a survey on AI adoption among SMEs and freelancers conducted by Peraichi.
As we’ve repeatedly pointed out on this platform, the adoption rate of generative AI is steadily rising. However, there remains a significant gap between “using it” and “using it effectively.”
Publishing and updating web pages is a daily task for many small and medium-sized businesses. Yet, the fact that over one-third of companies that have introduced AI are failing to see results in this area is a critical point that business owners cannot afford to overlook.
Why AI Adoption Stalls in Web Publishing and Updates
The Wall Between “Writing” and “Publishing”
Generative AI excels at text generation. Many business owners use it for drafting blog posts or creating catchy copy. However, many companies stumble when it comes to actually publishing or updating the generated content as a web page.
I myself went through numerous trials and errors before building an AI-driven article generation pipeline for my company’s WordPress site. Publishing AI-written text as-is often falls short from an SEO perspective or doesn’t match the brand’s tone and style.
Three Specific Challenges
The challenges revealed by the survey can be broadly categorized into three areas.
The first is that “the editing and publishing processes are disconnected.” Even if AI writes an article, separate work is required to reflect it on the website. This “translation task” becomes a bottleneck.
The second is that “AI output cannot be used as-is.” Human verification—fact-checking, tone adjustments, image selection—is essential. A method for delegating this verification step to AI has not yet been established.
The third is “insufficient integration between tools.” Many companies lack a system to automatically transfer content generated in ChatGPT or Claude to a CMS like WordPress or Peraichi. Most are likely manually copying and pasting.
The Solution: “Pipeline Automation”
Direct AI-CMS Integration is Key
To solve this problem, a system that directly connects AI and the CMS is effective. Specifically, build a pipeline like the one below.
First, generate a draft article with AI (Claude or ChatGPT). Next, automatically convert the content into the CMS format. Finally, go through an approval workflow and publish automatically. Automating this entire process can significantly reduce manual work.
In my experience, combining WordPress’s REST API with Claude Code allowed me to build a system that can publish about 20 articles per month almost automatically. The initial setup took about half a day, but since then, the work time per article has been reduced from about 15 minutes to 3 minutes.
Cost and Implementation Hurdles
The cost of implementing this system is not as high as you might imagine. AI API usage fees range from about $30 to $70 per month. CMS plugin or customization costs, if you hire a developer, can be kept between $350 and $700.
However, if you don’t have in-house technical talent, the implementation hurdle may feel high. In that case, choosing a service like Peraichi that offers a no-code CMS with AI integration plugins is another option.
Three Actions Business Owners Can Take Right Now
Start by Taking Stock of Your Current Situation
The first step is to visualize your company’s web publishing process. Who uses which tools and what steps do they follow to publish articles? Identify where in that process AI can be integrated.
In many cases, the “writing” step of an article should already be AI-powered. The problem lies in the subsequent “editing and publishing” steps. Automating this part is the next step.
Select and Test Tools
Next, choose an AI integration tool compatible with your CMS. For WordPress, plugins like “Jetpack AI” or “AI Power” are options. For Peraichi, using the AI features provided by the company itself is likely the smoothest path.
The key is not to target all articles at once. Start with a test run of one article per week to verify quality and time savings. Then, gradually transition to full-scale operation.
Build a System to Prevent Dependency on Specific Individuals
Finally, create a system where the AI-powered publishing process doesn’t rely on a single person. Automating manual creation and standardizing approval workflows are effective.
In my team, we’ve built a workflow where AI-generated articles are automatically posted to Slack for team members to review and approve. This ensures operations don’t stop even when the responsible person is unavailable.
Conclusion: The Next Phase of AI Adoption is “Integration”
As generative AI adoption progresses, the focus now needs to shift from “using it” to “using it effectively.” Web page publishing and updating are crucial customer touchpoints for many SMEs. Failing to leverage AI in this area puts you at a significant competitive disadvantage.
The survey results clearly highlight the “next wall” in AI adoption. As a business owner, the key is to recognize this wall and take concrete action. It’s essential not just to introduce tools, but to review the entire business process.
Direct AI-CMS integration is by no means a major investment. For a few hundred dollars a month, you can dramatically improve the efficiency of your web publishing operations. Start by understanding your current situation and take that first small step.
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