The AI Today podcast explores when to use automation versus AI, including examples of automating repetitive tasks and the suitability of AI for complex tasks. It also discusses scenarios where automation falls short, such as image recognition and customer service. Additionally, the podcast highlights the strengths and weaknesses of both approaches and introduces the CPMAI methodology and certification.
Automation is ideal for repetitive tasks and processes that don't require exception handling or AI capabilities.
AI is useful for tasks that cannot be easily coded or scaled with automation and excels in generating large volumes of text based on a few prompts.
Deep dives
Automation: Repetitive tasks and workflows
Automation is ideal for tasks that involve repetition, such as automating emails or reaching out to customers at regular intervals. Workflows that remain the same each time and don't require exception handling can also be automated. In addition, automating data entry into forms or different systems is a practical use case for automation. Processes that are repetitive and predictable, like approving bills or invoices below a certain amount, can also benefit from automation. Furthermore, customer service tasks with consistent answers, like providing store hours or contact information, can be automated without the need for AI capabilities.
AI: Content generation and analysis
AI is particularly useful for tasks that cannot be easily coded or scaled with people or automation. Automatic content generation is one such application, where AI excels in generating large volumes of text based on a few prompts. Analysis of sentiment, mood, or intent is another area where AI's contextual understanding outperforms keyword-based approaches. Machine translation, recognition tasks (e.g., image, object, facial), and autonomous systems like vehicles also require AI. Additionally, AI is valuable for creating hyper-personalized content or recommendations and for tasks such as fraud detection, data outlier identification, or predictive maintenance.
Summary and future steps
Understanding the distinction between automation and AI is essential for successful AI implementation. Automation is most suitable for repetitive tasks that can be programmed, while AI is chosen when rules cannot be easily coded or when continuous learning and decision-making based on data over time are necessary. Recognizing the strengths and weaknesses of each is key to ensuring that AI is applied appropriately in problem-solving. To deepen knowledge on this topic and many others, Cognitica offers CPMAI methodology and certification, including a free introductory course. By joining the CPMAI community, professionals gain access to further resources and industry-specific insights.
We often get asked what projects are appropriate for AI versus other forms of technology. So, we thought it was a great topic for a podcast. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer go over when to do automation versus AI.
Automation is using technology to perform repetitive tasks.