The Difference Between AI vs. LLMs: How Small Businesses Can Leverage Both for Growth
Receiptor AI
Automated Extraction of Receipts and Invoices from Emails. Seamless Categorization into Xero, Quickbooks, and others.
This year, the hype is on Artificial Intelligence (AI) and Large Language Models (LLMs). While these terms are sometimes used interchangeably, they refer to distinct technologies with different applications. In this article, we unravel the the differences between AI and LLMs and provide real-world examples of how small businesses can use both to boost efficiency and productivity.
What is Artificial Intelligence (AI)?
AI refers to the broader field of computer science focused on creating smart machines that perform tasks requiring human intelligence. It includes machine learning, natural language processing (NLP), computer vision, and robotics, offering businesses tools for automation and improved decision-making.
What are Large Language Models (LLMs)?
LLMs are a specific subset of AI focused on language tasks. These models are trained on vast amounts of text data and can understand, generate, and manipulate human language. Examples include ChatGPT, OpenAI’s models, and Google’s BERT. FYI, our favourite bookkeeping app, Receiptor AI uses LLMs to read, extract and process your receipts as well! Although their focus is on language based tasks, LLMs excel at content creation and customer interactions.
Key Differences Between AI and LLMs
AI vs. LLMs: Small Business Examples
AI: Implement a smart chatbot that answers routine queries and routes more complex issues to human agents.
LLM: Generate human-like responses to customer inquiries, ensuring a smooth and personalised experience.
AI: Use predictive analytics to identify customer trends and optimize ad spending.
LLM: Craft engaging product descriptions, email campaigns, and social media posts.
AI: Apply computer vision for quality control during manufacturing or food preparation.
LLM: Automate the creation and updating of employee handbooks and standard operating procedures.
AI: Use machine learning algorithms for fraud detection and financial forecasting.
LLM: Extract and categorize receipts with apps like Receiptor AI, generating simple financial summaries for stakeholders.
AI: Analyze customer data to identify emerging trends and inform product improvements.
LLM: Help create detailed product specifications, user manuals, and support documentation.
Why Small Businesses Should Use Both AI and LLMs
Using AI and LLMs strategically allows small businesses to achieve greater efficiency and provide better customer experiences. AI solutions can automate business processes, analyze data quickly and accurately, and enhance operational workflows. Meanwhile, LLMs can be used to streamline communication tasks, content creation, and customer engagement.
For example, a retail store can use AI for inventory management and predictive analytics, while an LLM can generate personalised product recommendations and follow-up emails. Similarly, a bookkeeping app like Receiptor AI combines machine learning for data categorization with LLMs to generate easy-to-understand financial reports.
How to Get Started with AI and LLMs
Conclusion
While AI and LLMs are interconnected technologies, understanding their differences enables small businesses to leverage them effectively. AI offers a broad range of capabilities that can automate processes and improve decision-making, while LLMs provide powerful tools for communication and content creation.
Small businesses that adopt both technologies strategically will enhance productivity, customer experience, and competitiveness in the market. Whether it’s managing financial tasks, personalizing customer service, or optimizing marketing campaigns, AI and LLMs open up new avenues for growth and success.