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Business and technology leaders are under increasing pressure to prove that they're capturing and using data in conformance with relevant regulations and internal processes. And the expanding use ofartificial intelligence (AI) has only increased that pressure. So whether it's "just" guidelines or actual legislation (which is forthcoming in the EU, for example), companies must be ready to provide clear evidence that their models are ethical and free of bias. And beyond regulation, many organizations just want to be able to prove to their customers that their data is trustworthy and hasn't been tampered with to build trust. 

Here are three of the most common data integrity challenges organizations struggle with -- see if any of these sound familiar to you: 

• Proving data provenance.There are many situations where companies have to demonstrate where they obtained data and identify who gave permission for them to have that data. This can apply to data used internally for analytics purposes or information that's made publicly available. 

• Ascertaining data integrity.Is this the original data, or has it been tampered with? If there are changes to the data, are they legitimate? These perennial and frequent questions can cause major challenges, and the ability to answer with certainty is essential to an efficient and trusted data operation. 

• Providing an audit trail of data use and process compliance.Many companies already have processes in place to document their adherence to data privacy requirements. Still, a smaller number have processes to ensure that they apply ethical principles in developing their AI models. That won't be enough for many organisations, with impending AI regulation in the EU and the requirements for proving compliance becoming more stringent overall. 

If these are areas that your organization struggles with, there is good news -- blockchain (distributed ledger technology) can help preserve data integrity and prove the trustworthiness of data-centric processes.  

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To learn more, register to attend Forrester's upcoming Data Strategy & Insights event on November 18-19 here. 

This post was written by Vice President, Principal Analyst Martha Bennett and it originally appeared here.

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