Data feeds artificial intelligence, and your company’s data will feed the artificial intelligence that you use for automation, content generation, and other tasks. How do you know if your data is ready to train artificial intelligence models, and how will you prepare it for that goal? Read on to learn more about preparing your data for AI’s use, making sure it’s as error- and bias-free as possible, and that your infrastructure is ready, too.
The Importance of Data Quality for AI Initiatives
Since data is the “lifeblood” of artificial intelligence, it’s vital to have the best-quality data for your company’s AI initiatives. First, data needs to be reviewed to make sure it’s consistent, free of duplicates, and as bias-free as possible. Consistency of the data, beyond its training of the models to produce accurate results, also supports team collaboration; the ability to adapt and expand AI as your company’s needs grow (scalability); making auditing and reporting easier for the purpose of regulatory compliance; and overall trust in AI’s role in business decision-making. Duplicate data can cause certain data to be given too much importance, resulting in bias. This duplication could even undermine the ability of the models to learn patterns. And errors in data could produce incorrect results, or hallucinations.
Other Components of Data Readiness
Security of your data is a starting point. Has your company performed a data audit, searching for confidential, personal or private information, so it is safe and secure? In terms of governance, what are your underlying policies for determining how secure your data is for use by employees with AI models? Part of governance is data confidentiality and the access to data, ensuring the data doesn’t fall into the wrong hands. Managing the data is yet another component, and involves having the tools and architecture to handle the volume of data and how fast it is generated.
Consulting with a Technology Advisor
The next step could be a consultation with your technology advisor. One question to consider is your business goals and how the benefits of artificial intelligence can support these goals. You’ll also need to consider your infrastructure and if it has enough bandwidth for the demands of AI. Along with increased bandwidth, latency needs to be decreased. Also, will you keep your data on-premises, go with colocation, or with managed hosting? These options have pros and cons to consider.
Using artificial intelligence, while helping reach business goals, also requires much thought and planning. For help, contact your trusted technology advisor today.
