Preparing Your Data for Success with AI: An Intro to AI Readiness

Have you ever asked an AI tool a question, only to get an answer that missed the mark? Are you struggling to turn your data into useful insights? It’s not just you—many businesses face challenges with unreliable insights from AI chat tools. Whether it’s misinterpreted queries or irrelevant outputs, these frustrations often stem from one fundamental issue: unprepared data.  

But there’s a way to fix that: AI readiness. With the right preparation, you can turn your data into a powerful source of practical insights that help you make smarter decisions and get better results. 

In part 7 of our AI Insights Livestream series, the Domo team introduced AI Readiness—our suite of tools designed to prepare your data for better AI performance. At its core are customizable data dictionaries, which give AI the right context to understand your data. This ensures precise, consistent results to help you get the most out of generative AI. 

Missed the livestream? Catch the full conversation here.

What is AI readiness? 

To prepare for the challenges of managing data and capturing the full power of AI, it’s essential to understand AI readiness, its capabilities, and its benefits. AI readiness prepares your data to make AI tools work better—laying a solid foundation. It improves the quality of your generative AI outputs and reduces inaccurate results, irrelevant outputs, or AI models misinterpreting user queries—providing a critical advantage for businesses using AI to advance decision-making.  

The guiding principle of AI readiness is to avoid “garbage in, garbage out” by ensuring “quality in, quality out.” Clean, well-structured, and contextually rich data is essential for AI systems to perform as intended. Without proper preparation, even advanced AI models struggle to deliver meaningful results. 

By ensuring AI has the right context, AI readiness helps it understand your data correctly. This leads to better accuracy and consistency in your AI outputs, including AI Chat tools.  

This way, organizations can tap the full potential of AI and create reliable, impactful results. 

Key benefits of AI readiness 

How does it deliver tangible value? Here are some ways AI readiness helps organizations get the most out of their AI systems: 

Improved accuracy

Clear and well-organized data leads to more accurate results, which helps teams make better decisions with confidence.For instance, Google’s DeepMind used AI to analyze retinal scans for diabetic retinopathy. By training the system on clean, high-quality data, it achieved over 90 percent accuracy in diagnoses.  

Better collaboration

AI readiness helps teams work better together. Business users, data scientists, and administrators can all access and share the same data, definitions, and context. This common understanding facilitates faster knowledge sharing and speeds up decision-making.  

Consistent organizational insights

AI readiness helps everyone in a company work with the same understanding of data, minimizing misunderstandings. It ensures that they all use the same foundation no matter who accesses the information, keeping insights accurate and reliable across the organization. This also helps teams identify new opportunities early, fueling growth and innovation.  

Key features of AI Readiness in Domo 

Domo’s AI Readiness tools help you make your data more powerful and more accessible to analyze. It also ensures that your AI models product accurate and actionable insights. 

Here are some of its standout features: 

1. Enabling AI columns 

Reduce unnecessary noise and improve the accuracy of your results by selecting only the essential data by choosing the most relevant columns for analysis. 

Example: In a data set with over 200 columns, you can focus on revenue-related columns to analyze financial performance more effectively. 

2. Adding data set context 

Add a brief description to your data sets, giving the AI a better context so your queries are more accurate and relevant. 

Example: If you’re working with data on heart implant device sales, adding context like “sales data for heart implants over the past year” helps the AI interpret your queries more effectively. 

3. Column-level context and synonyms 

Provide specific details to each column and add synonyms so AI can interpret the data accurately, even with varied ways of expressing the same idea. 

Example: If you’re tracking customer satisfaction, define “1” as “high satisfaction” in customer surveys. Then add synonyms like “content” or “pleased” to help AI recognize different expressions. 

4. Use Beast Modes

Use Domo’s Beast Mode to use predefined calculations, making it easier to get insights from complex data. These calculations simplify tasks like aggregations and categorizations, helping you get accurate results faster and easier. 

Example: Automatically calculate the average checking account balances across a large data set with a Beast Mode instead of doing it manually. This will save time and reduce errors. 

Best practices for getting your data in AI-ready shape 

Getting your data ready for AI is important to make sure your AI tools work effectively and give accurate results. You can ensure better insights and smoother interactions by focusing on clean and well-organized data.  

Here are some simple best practices to follow: 

• Focus on data cleanliness: Clean data is vital for reliable results. To ensure your data is ready for AI, remove missing values, fix errors, and manage outliers. Tools like Domo’s AI Readiness Guide can help. 

• Avoid overloading AI with too much context: Share only the most relevant information with the AI. Giving too much data or unnecessary context can confuse the system and lead to overload and incorrect results. 

• Use Beast Modes: Use Magic ETL to clean and transform your data, and then apply Beast Mode to add your custom calculations. Beast Mode helps you refine and prepare your data for AI applications. Don’t try to put complex calculations inside the AI Dictionary or column contexts, as this could cause inefficiencies.  

• Improve through iteration: Don’t expect everything to be perfect at once. Regularly refine your data and how you interact with AI by improving prompt phrasing and context over time. 

• Use Domo’s AI Dictionary: Use the AI Dictionary to add context to your data, such as custom mappings or calculated fields. This makes your data easier for the AI to understand and process accurately. 

Applications and use cases  

AI Readiness helps businesses get better insights from their data. It tailors AI interactions by adding context, simplifying columns, and using synonyms to avoid confusion. This ensures accurate and meaningful answers across different use cases, including:  

1. HR survey data 

HR teams can use AI Readiness to solve tricky problems like reverse scoring in employee satisfaction surveys. For example, if a lower score means higher satisfaction, the AI dictionary helps the system understand this correctly. Adding synonyms, like linking “happiness” to “job satisfaction,” makes it easier for anyone to search the data, even without technical skills. 

2. Healthcare sales data 

Tracking healthcare sales data can get challenging if the data set lacks context. For example, if you need to track heart implant device sales, the data might not explicitly indicate it is specific to heart implants. As a result, AI might fail to answer questions like, “How many devices were sold by region?” 

You can add context about the data set using the AI Dictionary inside Domo. For example, you could add a note like, “This data set tracks heart implant device sales for the healthcare industry.” With this context, the AI understands the data set’s purpose and delivers accurate insights. 

3. Financial data 

The AI dictionary simplifies how AI interacts with complex data sets for financial teams. Imagine a scenario where a data set contains over 200 columns, many referring to revenue in different ways. Without guidance, the AI may guess which column to use, leading to inaccurate results. 

Financial teams can focus AI on key metrics by selecting only the relevant columns, such as annual contract value (ACV). This ensures the AI provides accurate answers, like calculating total recurring revenue for a specific period.  

Getting started with AI readiness 

Making your data AI-ready is the key to obtaining high-quality, trustworthy answers from your AI systems. With Domo’s powerful AI tools, preparing your data for AI is simpler than you might think. 

If you’re not getting the responses you expect from your AI system, AI Readiness in Domo can help. This feature enhances the accuracy and relevance of your AI results by adding metadata and selecting relevant fields. The additional context ensures better, more precise insights from your AI-generated content. 

Want to learn more about Domo.AI? 

• Watch the replay of AI Insights: Part 7—Unlocking AI Potential Through AI Readiness. 
• Or, you can explore our AI Readiness Guide for a step-by-step checklist to prime your data sets for any AI use case.