The Art of Finding the Perfect (Generative) AI Use Case for Your Business

The world of Generative AI is evolving at a rapid pace, and businesses are starting to recognize the potential that it holds for driving innovation and automation. However, with so many Generative AI solutions available, it can be challenging to know where to begin. Having a tool in this case a large language model (LLM) doesn’t guarantee success. Moreover, many organizations struggle at the POC level. When the hype is at its peak, it is easy to get #FOMO and start something fun with LLMs, but figuring out where to apply generative AI to bring business-value is crucial. A few years back, Gartner predicted up to 85% of AI projects would “not deliver”. With recent hype around Generative AI, this estimation can go beyond the 90%.

The key to success in implementing Generative AI lies in finding the perfect use case for your business. But how do you identify the right use case? Here's a an approach to help you uncover the ideal Generative AI use case for your business.

1.?????Finding business-blind spot through “problem first” approach

The best place to start is with a "problem first" approach. Talk to experts who are working and responsible for different processes in your company. These experts might not know the latest technology, but they know the process. They might be using a 100-sheet macro-enabled super-customized excel file. They might not see the problem in the process (blind spot), but they are the ones closest to it. While learning the process, you can (hopefully) see the potential benefit to the business by overcoming the challenges associated with current processes. The problem could come in many shapes and sizes and often hidden, but asking the right questions can help you get a sense of it.

• Churn is the problem and customers feedback if not encouraging. Support team is delivering on complaints about that is not increasing sales or customer experience.
• Marketing campaigns are not getting enough attentions of customers and response rate of no impressive
• Supply chain is delivering the products and performance on established KPIs looks reasonable but that seems not enough.
• Market has a lot of uncertainties and existing portfolio needs to be adjusted to make it future proof, but any change seems a risky bet.
• …..

2.?????Understanding the short/long term business goals

Having a clear idea (with enough details) on the company’s goals and roadmap to achieve those targets is the next critical information. Understanding the micro and macro level message company wants to give to its customers (and investors) shapes the action to achieve the desired outcome.

3.?????Setting measurable success criteria

Setting measurable success criteria is an essential step in identifying the right Generative AI solution for your business. It involves defining specific, measurable, achievable, relevant, and time-bound (SMART) goals that will help you evaluate the success of your Generative AI implementation.

• Chatbot for customer service: Suppose your company wants to implement a chatbot to handle customer service inquiries. In that case, your measurable success criteria could be to increase customer satisfaction ratings by 10% within six months of implementation. You could also measure the chatbot's accuracy by tracking the percentage of inquiries that the chatbot answers correctly.
• Personalized marketing campaigns: If your company wants to use Generative AI to create personalized marketing campaigns, your measurable success criteria could be to increase the click-through rate of email campaigns by 15% within three months of implementation. You could also track the conversion rate of personalized campaigns compared to non-personalized campaigns.
• Predictive maintenance: Suppose your company wants to use Generative AI to predict when maintenance is required for your equipment. In that case, your measurable success criteria could be to reduce equipment downtime by 20% within six months of implementation. You could also track the number of times the equipment requires maintenance compared to the number of times predicted by the Generative AI model.

4.?????Analyze your data

Analyze your business data to identify patterns, trends, and insights that can help you solve the problem. This will also help you identify the type of Generative AI solution that would be best suited to your needs. It involves collecting and analyzing data from various sources to identify patterns, trends, and insights that can help you solve the problem at hand.

• Chatbot for customer service: To implement a chatbot for customer service, you need to analyze data from previous customer interactions. This could include customer inquiries, responses, and feedback. By analyzing this data, you can identify the most common inquiries, the most effective responses, and the areas where customer service can be improved. This analysis will help you identify the type of Generative AI solution that would be best suited to your needs.
• Personalized marketing campaigns: If your company wants to use Generative AI to create personalized marketing campaigns, you need to analyze data from previous customer interactions, such as purchase history, browsing behavior, and social media activity. By analyzing this data, you can identify patterns and insights that can help you create personalized campaigns that are tailored to each customer's interests and preferences.
• Predictive maintenance: To use Generative AI to predict when maintenance is required for your equipment, you need to collect data from various sensors and monitoring systems. This data could include temperature, pressure, vibration, and other factors that could indicate when maintenance is required. By analyzing this data, you can identify patterns and trends that can help you predict when maintenance is required and avoid costly equipment downtime.

5.?????Research, Plan your implementation and Monitor

Get a good understanding of the various Generative AI solutions available in the market and determine which one aligns best with your goals and business requirements. Once you have identified the right Generative AI solution, plan the implementation process carefully. This includes defining timelines, identifying resources, and setting up a testing framework to ensure that the solution is working as expected. Once you have identified the right Generative AI solution, plan the implementation process carefully. This includes defining timelines, identifying resources, and setting up a testing framework to ensure that the solution is working as expected. After implementation, monitor the solution's performance and evaluate its impact on your business. This will help you refine the solution and identify areas for improvement.

Finding the perfect Generative AI use case for your business requires a systematic approach and a clear understanding of your business problem and goals. By following these steps, you can identify the right process in your company and right Generative AI solution and unlock the potential of Generative AI to drive innovation and automation in your business.

PS: Opinion expressed in this article belongs to me as an individual and do not represent opinion of any organization, I am part of.