Content Excellence: A Non-Technical Approach to AI in Content

Safalta Expert Published by: Sanny Gangwar Updated Fri, 18 Aug 2023 12:58 PM IST

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The quick usage of Artificial Intelligence (AI) methods and innovations has caused a profound impact in the context of content development and distribution in today's rapidly evolving digital ecosystem. According to a recent Gartner report, 50% of all businesses will utilize AI for content generation and dispersion by 2023.

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Table of Contents:
What is Non-Technical AI for Content?
The Benefits of Non-Technical AI for Content
How to Use Non-Technical AI for Content
Case Studies

What is Non-Technical AI for Content?

Non-technical artificial intelligence for content enables the development and management of content without the need for extensive technical expertise. These types of AI can help companies of all sizes create more engaging and impactful content capable of reaching a larger audience.

Some examples of Non-technical AI for content are as follows:

Content generation:
Artificial intelligence generates blog postings, articles, and social media posts. Businesses that need more time or resources to produce their content may find it beneficial.

Chatbots: Computer programs known as chatbots can mimic conversations with real humans. Chatbots can assist in sales closing, customer service, and question-answering.

Text analysis: It is the process of extracting meaning from text.


Text analysis with AI can look for sentiment, subjects, and other patterns. Making better business decisions and increasing the appropriateness of content are both possible with the help of this data.

Content optimization: By optimizing content for search engines and social media, AI helps businesses increase website traffic and reach a wider audience.

Personalization of content: AI can tailor material to each user. Data from past purchases, browsing habits, and social media activity is employed to carry it out. Custom-made content can be more effective at engaging users and driving sales.

The Benefits of Non-Technical AI for Content
According to a Forrester report, companies in India can reduce their content development expenses by up to 30% using non-technical AI.

Increased productivity: Artificial intelligence
(AI) on a technological level can automate tasks like content creation, research, and editing. Human content producers may have more time to devote to strategic tasks like formulating content strategies and producing high-quality content.

Improved quality: By ensuring that content is factually accurate and checking for language and spelling problems, non-technical AI can raise the quality of content.

Increased reach: Non-technical AI can distribute content more widely by optimizing it for search engines and social media platforms.

Reduced costs: Non-technical AI can reduce the costs of content creation and distribution by automating tasks and eliminating the need for human editors.

According to a Google survey, 60% of Indians use tools for AI-powered content production. As stated in a PwC report, the global market for non-technical AI for content anticipates reaching a worth of more than $20 billion by 2023.

Read more: How to Start a Career as an AI Content Writer. 

How to Use Non-Technical AI for Content
67% of Indian businesses utilize AI for content marketing, according to a PwC report. 70% of Indians use social media to consume material, according to a Google survey.

AI-powered content creation
AI enables the creation of tailored content for specific audiences. It is possible by using information from past purchases, internet habits, and social media activity. AI can craft original content, including poems, stories, and scripts.

AI-powered content distribution
AI can distribute content to the right people at the right time. You can achieve this by utilizing information like previous engagement, interests, and location. AI can optimize content for several platforms, like social media, email, and search engines.

AI-powered content measurement
Analyzing indicators like website traffic leads and sales enables the utilization of AI to measure the effectiveness of content marketing campaigns. It can identify trends and patterns in content consumption.

Case Studies
A study by Forrester found that AI-powered content creation can save businesses up to 50% of the time and cost of creating content. The Indian Chamber of Commerce's study revealed that 60% of brands in India utilize AI-powered content creation.

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Google AI
Google AI has developed multiple tools for crafting and enhancing content. For instance, the Text-to-Image API enables the creation of images from text descriptions, while the AutoML Natural Language API facilitates the generation of text content.

IBM Watson
IlluminateAI utilizes IBM Watson's suite of AI tools to accomplish various tasks, including content creation. It can provide customer service and answer questions. For instance, Watson Assistant enables the creation of chatbots capable of delivering customer service and responding to inquiries.

Amazon Lex
The Amazon Lex service enables the creation of chatbots that can understand and respond to natural language. You can apply this to develop chatbots for customer support, sales, or entertainment.

AI is revolutionizing the content industry, offering businesses unprecedented creative possibilities and operational efficiency. Non-technical AI for content curation creates individualized, high-quality content that improves brand recognition and outreach. This novel strategy provides a future competitive advantage. According to a Forrester Research study, initiatives utilizing AI-powered content marketing can increase lead generation by up to 20%.


What is AI for non-technical?

AI, or Artificial Intelligence, is:

  1. Sensible automation is the ability for machines to think and learn, enabling them to carry out activities independently.

  2. Human Mimicry: AI copies how humans think, solve problems, and make decisions.

  3. Adaptive Learning: It gets better on its own over time and experience.


What are the different types of AI approaches?

  1. Symbolic AI: Uses predefined rules and logic for decision-making.

  2. Algorithms: Use machine learning to identify patterns in data and predict outcomes.

  3. Neural Networks: Models inspired by the human brain's structure for complex tasks.

  4. Evolutionary Algorithms: Mimic natural selection for optimization problems.


Can a non-technical person learn AI?


What is machine learning for non-technical?

Without explicit programming, machine learning teaches computers to recognize patterns in data and gradually improves their intelligence.

What are the four types of AI?

Four types of AI include Reactive AI (limited tasks), Limited Memory AI (short-term learning), Theory of Mind AI (understanding emotions), and Self-aware AI (consciousness).

What is the rule-based approach in AI?

The rule-based approach in AI uses predefined logical rules to make decisions or perform tasks without machine learning or data analysis.


What are the approaches to AI thinking humanly?

The cognitive modeling approach.


What types of AI are not machine learning?

Rule-based AI, expert systems, symbolic reasoning, and knowledge-based systems are AI types not reliant on machine learning techniques.

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