How to Generate AI Business Ideas
AI has become a game-changer for both large enterprises and smaller teams alike. It holds the potential to boost sales, cut costs, and drive innovation by creating new products and services. However, many business owners, executives, and product managers are left wondering: where do I even begin harnessing the power of AI? How can I identify the areas where AI can help me achieve my business goals?
In this article, I will present you with a framework comprising four fundamental principles that will provide valuable insights on leveraging AI for existing process automation. This is one of the applications with the highest return on investment.
Interestingly, teaching an AI system to perform a task is strikingly similar to training a new employee. Think about it: when onboarding a new team member, you typically pair them with a trainer who shares knowledge about the task, explains how to execute it effectively, and provides numerous examples for reference. Sometimes, the training involves walking the new employee through detailed instructions. At the same time, in other instances, they learn primarily by observing their more experienced colleagues in action. This fundamental training paradigm is the foundation for the principles we will discuss next.
First Principle: Training an AI automation system typically requires a substantial number of successfully completed task examples. This principle carries two critical implications.
The first implication is that individuals currently performing the job must be capable of articulating their thought process, even if it’s somewhat intricate and fluid. The beauty of utilizing AI lies in its ability to handle exceptions and variations that would be arduous, expensive, and error-prone to address through traditional software development.
The second implication is that those performing the task must exhibit confidence and, notably, consistency when confronted with the same situation repeatedly. Consider an example: imagine a customer service telephone operator randomly assigning customer calls to the accounting or service departments, even when all calls pertain to billing inquiries. Introducing an AI system in this scenario would pose challenges since the statistical model would struggle to identify a consistent pattern in the operator’s behavior.
Second Principle: The availability of training data is crucial when introducing an AI automation system. Data availability often presents a significant hurdle for many AI initiatives. Therefore, it is vital to carefully plan and address data-related challenges before embarking on an AI project. In upcoming articles, we will delve into data collection in detail. For now, it is essential to recognize that the required data may already exist within your company or need to be obtained externally from data vendors. Understanding and securing the necessary data sources is a critical step in ensuring the success of your AI implementation.
Third Principle: When considering task automation, especially with AI systems, focusing on tasks that can benefit from the economies of speed and scale enabled by technology is crucial. Ideal candidates for automation are repetitive tasks that require frequent completion. This principle holds particular significance for AI solutions due to the need for training data, as discussed earlier. AI systems excel in streamlining such tasks, unlocking the potential for significant improvements in speed, scalability, and overall productivity.
Fourth Principle: Tasks suitable for AI automation should allow for a certain degree of error tolerance. Although this statement may initially raise concerns, it’s essential to consider the current error rate of human experts. They are likely to make mistakes occasionally, and an AI solution can achieve comparable, if not better, performance. One option is to use AI to assist rather than entirely replace human workers. This approach, known as human-AI collaboration, often yields the best results, especially when introducing AI projects or processes for the first time.
So there you go! You now have a framework to start evaluating AI business ideas. By embracing these principles, you can have a more realistic and pragmatic perspective on AI implementation, automate your processes with remarkable precision and efficiency and unlock the benefits of automation while maintaining a balanced and effective workforce. Thank you for reading! Let me know in the comments your thoughts and questions.
If you enjoyed this article, please give it a round of applause by hitting the clap button generously! Your support and engagement are greatly appreciated!
To stay updated on future AI insights and discussions in the business realm, follow the “AI with Lina” publication on Medium. For video content, follow me on YouTube. You can also connect with me directly on LinkedIn.
