How to assess your company's needs

- You might be excited about the possibilities AI can offer for your company. But the AI implementation is not the goal in itself. It's a means to an end, one that should help you meet your strategic objectives. As we discussed earlier, the first and most important step is clearly defining your business objective. Without a clear understanding of what you're trying to accomplish, you will never achieve your goal. Think through the business problems you're trying to solve. Where are you looking to create the most impact for your company, and why is that the most important? Those could be process related. For example, a manufacturing company might want to focus on optimizing its production processes or a consumer internet company might want to reimagine its experience to increase customer loyalty. Start by sending out specific measurable outcomes for your objective. And if successful, what's the change you would like to see? Next you need to evaluate your current capabilities. What are your strengths and gaps in relation to the objective you chose? Understanding your current capabilities can help you determine where to start with AI and what types of projects might have the highest ROI for you. If your company, for example, does not have experience with AI, you might want to invest in training your employees on machine learning and data science first so you can get the most out out of your AI projects. Don't just think of AI as a way to close gaps. There's a good chance that AI can actually help you boost the strength you already have. As a mental model, don't start by asking yourself where can I add AI? Ask yourself, given my objectives and my current state, and by thinking AI first, what can I do to create business value in a differentiated way? The third step is to identify the data needed to meet your objective. As we learned earlier, with AI, data is no longer a competitive advantage as it used to be. I would assume, for example, that many small businesses will have to rely on pre-train models like GPT and zero shot learning. However, you still need to assess what kinds of data you will need and where you can get it from. It could be internal or external, and ideally the data is unique, it's high quality, and it's differentiated to you. I cover this in depth in my previous AI mindset course if you'd like to learn more about it. The fourth step is to select the right types of AI systems and tools. Choosing the right tools and platforms can go a long way in maximizing your success. So evaluating different AI systems against your specific goals will really help you select the right one that fits your needs the best. In the next couple of videos, we'll learn more about how to make those decisions. The final step is to monitor results, refine and assess progress and risks. This way you can make ongoing iterations and refinements to your projects to achieve the best outcome for you. It's also critical that you consider the potential risks that can arise with your AI projects, such as privacy concerns bias in the data, copyright violation or even lack of transparency and take steps to address these issues upfront. In this course, we have a whole section dedicated to it given how important this is. So there you have it. If you're looking to get started, these five guidelines will help you make the most out of AI and unlock the potential for your business. So number one, clearly define your business objective. Number two, evaluate your current capabilities. Number three, identify the data you need. Number four, select the right types of AI systems and tools, and lastly number five, monitor results, refine and assess progress and risks.