AI in Business: How to implement/start with AI in business

AI has transformed from a futuristic concept to a down-to-earth business tool. With the advancement of large language models like ChatGPT(OpenAI), Gemini(Google), and LLAMA(Meta), the use of AI has become quite appealing these days in business, especially when scaling a business 2-3x. But navigating the world of AI can feel overwhelming. Don't be discouraged! This is a strategic journey; you can break it down into achievable steps. Here's a roadmap to get you started:

1. Identify Your Needs:

●????? Repetitive tasks? AI can automate them. Take an example: You have a doc file, and you want to retrieve a table in an Excel file; go to ChatGPT(with a paid subscription), put the file, and extract the data from it. The work becomes money-efficient if you can code or have someone to code for you. Use open source models like LLAMA, Mistral, etc.; write a bit of code for Retrieval Augmented Generation(RAG) with appropriate parameters set to the model. Now, You can do the task without paying ChatGPT.

●????? Data overload? AI can analyze it for valuable insights. Take an example: You have business data over some period of time, feed the data to these Large Language Models, or do some fine-tuning on the base model(transformer architecture); you will get a pretty standard report without the help of a human expert’s intervention.

●????? Struggling with personalization? AI can tailor experiences. For example, you want to suggest personalized products to your customer base, prepare a data set, and make a recommendation model, thus increasing your sales and customer loyalty.

2. Start Small & Scalable:

●????? Don't chase a silver bullet. Focus on a specific, achievable goal (e.g., automating customer service inquiries). Make a ChatBot integrated with ChatGPT or any open-source Large Language Model(LLAMA2-Chat), and now the customers are happy with the response from the customer service facility.

●????? Create appropriate ads. The advancement of GenAI is quite promising in writing appropriate texts(ChatGPT, LLAMA, Gemini) and creating images or videos(Stable defusion, DALLE, LLAMA, Gemini(last two are free)) that are both attractive and customer-appealing.

3. Build Your AI Team (or Partner Up):

●????? You don't necessarily need in-house AI gurus. Partner with AI consultancies or leverage cloud-based AI solutions with expert support.

●????? But having an expert on board makes it better: cost-efficient + unlimited personalization.

●????? If you have a very small-scale business, you can learn it independently. Learn about prompting from the web and integrate on your own. If you can not code, no issues; just have one subscribed OpenAI account and create prompts according to your needs.

4. Prioritize Data Quality:

●????? AI is only as good as the data it's trained on. Clean, organized data is vital for accurate and reliable AI models.

●????? Collect data from the customers(on their search on your website and products), take feedback on your services or products, and use AI strategies to improve the quality and thus increase sales.

5. Embrace Experimentation:

●????? AI isn't a one-time fix. Be prepared to test, refine, and iterate on your AI implementation as you learn and gather data.

●????? One by one, you will learn and advance your model, adding new features and services to your customers, and thus, you scale.

Bonus Tip: Communication is Key!

●????? Clearly communicate the goals and limitations of AI to your team. AI is here to augment, not replace, human expertise; use it as a draft and implement it with human expertise. Focus on reducing human labor with automation and be updated with cutting-edge technology and implementation.

This is a basic road map you can follow to scale your business with AI.

Ready to take the plunge? Share your thoughts! What specific areas are you considering for AI implementation in your business?

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