he use of artificial intelligence is rapidly rising, and for those in the performance plastics industry, it is no longer a question of whether to use AI, but how and for what purpose. When implemented strategically, AI can be an excellent tool to help streamline processes, reduce busywork and make teams more efficient. This article covers different types of AI, use cases to consider when building an AI strategy for your business, tips for prompt writing and other best practices.

You are likely used to hearing about, and perhaps even using, generative AI platforms such as ChatGPT and Claude. These are common tools used both inside and outside the workplace, but AI platforms and functions go beyond generative AI. Below are several AI types categorized by business purpose to consider when creating an adoption strategy.

Generative AI, including large language models, or LLMs, and content generation tools, is the current hot topic in artificial intelligence. It focuses on creating new content, such as text, code and images. Employees use generative AI to create sales presentation outlines, draft marketing content, summarize and organize documentation, brainstorm, conduct research and much more. Examples include OpenAI’s ChatGPT, Anthropic’s Claude, Google Gemini and Microsoft Copilot.

Predictive AI analyzes data to identify patterns, flag anomalies and predict outcomes, helping businesses with forecasting and decision-making. Uses include sales and demand forecasting, fraud detection, pricing optimization and predictive maintenance. Examples include Amazon Web Services SageMaker, IBM Watson and others.

Assistive AI does not fully automate decision-making but helps employees optimize workflows by organizing information and supporting daily tasks. Tools such as Microsoft Copilot, Salesforce Einstein and others assist with email drafts, CRM support, document summarization and more. These tools often are integrated directly into technologies already in use, such as email, enterprise resource planning systems, CRM platforms, word processors, spreadsheet software and other applications.

Conversational AI uses natural language to interact with users in messaging or voice chat interfaces. Companies use conversational AI for customer support chatbots, phone answering systems, internal help desks and other applications. Conversational AI platforms to consider include Google Cloud Dialogflow, Salesforce Agentforce and Microsoft Copilot Studio.

While each of these AI categories appears in different ways and serves different purposes, many business AI deployments combine multiple categories to create or optimize a single workflow.

• Practice prompt writing. When using generative AI, the output will only be as useful as the input. AI works best when given clear directions and boundaries.

  Provide clear context. What use will the output serve? What is the goal, and what does a successful output look like to you?
  Define the desired format. This minimizes the need for revisions. Do you want the information structured in a two-paragraph summary or a two-page summary? Perhaps you need a comparison chart or a list with 10 bullet points. The more specific you are, the faster AI can get to your desired output.
  Define the audience and tone. Emojis and exclamation points could be appropriate for social media content but may not be suitable for a draft of a technical document. Consider your audience and desired tone when asking AI to create something for you. Should the output be written for a technical or nontechnical audience? Is there a specific industry or job type you are addressing? Do you want a casual tone or something more formal?
  Refine the output. Treat the first response as a draft and use prompting conversationally to iterate until you get the desired output. Ask AI to simplify language, add examples, adjust the tone, add or remove specific details, or shorten or lengthen the word count.

• Use AI intentionally, not just because it is a trend. Successful AI implementation begins with identifying business goals and operational pain points, then finding the right tools to help. Focus on the outcome rather than the technology alone, and measure the success of that implementation to refine and scale your AI strategy.
• Maintain human oversight. Artificial intelligence systems are rapidly evolving and improving, but they are not infallible. Human oversight is necessary to avoid potentially serious consequences. Performance plastics are used in important industrial and technical markets where accurate information is critical. Therefore, AI output should always be reviewed and vetted by qualified employees before distribution. For queries involving research and facts, ask for the AI’s sources and verify them. Another pitfall of overreliance on AI content generation without a human touch is that the results can become generic and lack authenticity. Many companies are using the same tools for the same purposes, so make sure your messaging does not become just another copy.
• Prioritize training. For consistent results, employees must understand how to use available AI tools, as well as when not to use them.
• Always follow your company’s policy for AI use. Not all AI tools are created equal when it comes to data security, and using them without proper vetting or precautions can leave your company vulnerable. Because LLMs generate responses to users’ questions based on learned data, and some of that learned data comes from other users’ inputs, what you type into a service such as ChatGPT may not be kept confidential.
• Establish an AI policy. If you lead a company that does not have an AI policy, prioritize creating one. The policy should include which AI tools or platforms are approved for business use, who is allowed to use them and what information may be entered into these tools.

In business use cases, AI is especially effective at handling repetitive or time-consuming tasks, such as summarizing documentation and data cleansing. These efficiencies allow employees to dedicate more time to strategic work, customer relations and problem-solving.

AI adoption will have a lasting impact on manufacturing and distribution, and companies that develop clear, scalable and goal-oriented strategies will be positioned to operate more efficiently and remain competitive in the future. The most effective AI implementation strategies combine automation technologies with internal expertise, human oversight and strong business processes. This balance will ultimately determine success in the performance plastics industry, where technical knowledge, responsiveness and customer trust are crucial.