Artificial Intelligence (AI) is rapidly becoming a ubiquitous presence in our lives, offering tremendous potential value. However, as customers, it is crucial to understand the technology we are investing in. When considering buying an AI solution, it’s essential to ask the right questions and evaluate the product thoroughly. In this guide, we will outline seven key questions that new customers should consider before purchasing an AI-based solution.
Question 1: Does the solution effectively address a specific business problem?
It is crucial to assess whether the solution can genuinely solve a business problem and whether the developers truly understand that problem. For instance, chatbots can significantly enhance individual productivity, but can they scale effectively to accommodate a large number of users, such as 100 or 1,000 people? Understanding the scalability of an AI solution is essential for delivering continuous value to your business and streamlining your operations.
Question 2: What are the security measures in place?
Data security is of utmost importance when it comes to AI solutions. As AI relies on analyzing massive amounts of data, it is essential to have robust security measures in place. The security stack should meet or exceed your organization’s standards. It is vital to protect and manage data, control access to it, and secure it properly. As regulators focus on the ethical use of AI, ensuring that your solution aligns with these values is crucial for compliance.
Key Takeaway
When evaluating an AI solution, consider whether it effectively solves a specific business problem and assess the security measures in place to protect your data.
Question 3: Can the product improve over time?
Machine Learning (ML) models can become outdated and start producing incorrect results. It is essential to evaluate whether the AI solution can adapt and improve over time. For example, if a model has been trained on data only up until November 2021, it may not be able to understand events that occur after that date. Understanding how the vendor keeps their models up to date and handles model drift is crucial for ensuring accurate and valuable results.
Question 4: What is the expertise of the technical team?
The technical team behind the AI product plays a pivotal role in its success. It is vital to assess the expertise and experience of the team responsible for developing and maintaining the solution. Understanding the team’s qualifications, domain knowledge, and track record can provide valuable insights into the product’s quality and future development.
Question 5: Does the solution integrate well with your existing technology stack?
An AI solution should seamlessly integrate with your existing technology stack to maximize its potential value. Assessing whether the solution can effectively integrate with your current infrastructure, software, and workflows is crucial. Compatibility and interoperability are key factors to consider when evaluating an AI solution.
Question 6: What is the cost and return on investment?
Understanding the cost structure and estimating the return on investment (ROI) of an AI solution is essential. Evaluate the pricing model and consider the long-term benefits the solution can bring to your business. It is important to analyze the potential savings, productivity improvements, and revenue growth that the AI solution can generate.
Question 7: How is customer support and training provided?
Customer support and training are crucial aspects when implementing an AI solution. Evaluate the level of support offered by the vendor, including their responsiveness, availability, and expertise in providing technical assistance. Additionally, consider the training resources provided to ensure your team can effectively utilize and maximize the value of the AI solution.
By asking these seven crucial questions, potential customers can make well-informed decisions when buying an AI solution. It is essential to thoroughly evaluate the solution in terms of its ability to solve specific business problems, data security measures, scalability, technical expertise, integration capabilities, cost and ROI, and customer support. By doing so, customers can ensure they choose the right AI solution that aligns with their business needs and goals.
