Today, every business is looking for ways to harness AI to gain a competitive edge. From supporting decision-making and improving budget planning with predictive insights, to enhancing customer care, deepening business analyses, and generating personalized content, the use cases are broad and growing.
AI algorithms can accelerate monotonous tasks, optimize processes, remove barriers to user interaction, improve predictive accuracy, and provide real-time analysis. These capabilities help businesses make data-driven decisions more efficiently. AI can also manage complex datasets, integrate data from multiple sources, and continuously learn and improve from new data. This makes it a powerful tool for extracting valuable insights and driving innovation. Gen AI introduces a new, straightforward interface that allows users to “chat with their data” and access information in a natural, human-like way.
AI is also useful for data analytics, because it can process vast amounts of both structured and unstructured data quickly and accurately. In doing so, it reveals patterns and insights that might be overlooked by human analysts.
When building an AI-based system, the first and most critical step is to identify the use case. Are you aiming to automate customer service, support decision-making with predictive analytics, enhance personalized marketing activities, optimize supply chains, detect fraud, or pursue another objective? The chosen use case will influence almost every strategic and development decision that follows.
Once the use case is clear, the next step is selecting the right AI model. Companies today face a wide array of options, which can make the choice daunting. Should you adopt an existing commercial model such as a large proprietary LLM like ChatGPT? Should you build on an open-source or freely available model? Or should you develop a custom hybrid system tailored to your needs?
The key question then becomes: how can a company ensure that its model is trustworthy, fit for its purpose, sustainable, and capable of evolving alongside the business?
In this five-part series, we will explore the main factors that distinguish the different options for building an AI model for business, and how organizations can identify the path that best suits their goals.
