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Technology powered by #ArtificialIntelligence and machine learning are revolutionizing the world of work. With data as their foundation, there is a growing focus on trust, transparency and governance. Employers need to manage and protect their data, while ensuring it is used ethically.

ADP’s Jason Albert shares the top trends impacting data, data governance and ethical use of AI in 2026.

For more 2026 HR Trends, visit ADP.com/SPARK

Video Transcription:

Jason Albert, ADP Global Chief Privacy Officer

We have lots of existing governance structures to address compliance. But it's important to think about not only what can we do, but what should we do.

Workforce data management is going to become increasingly important to companies. They have the ability to bring data from different silos and different systems together. And it's important when they do so that they manage that to make sure that the data is of high quality, that they've addressed data privacy and data security as well, and that they manage this to provide opportunities for their workers and insights as they manage their workforce.

Everything from new training opportunities and new career paths to helping with performance evaluation and recruiting. Data management is going to help enable all of this. But to enable these opportunities you have to have good governance to make sure that the right data is being used to provide the right and accurate insights.

1. The first thing employers have to do to build a responsible data governance structure is to understand what data assets they have. They need to have an inventory of the different systems in which data is housed.
2. Then they need to understand how various tools, AI systems or otherwise act on that data.
3. And then they need an approval process for when new tools or systems or capabilities are introduced into their environment.
4. They need to be able to check those to make sure that the right data is being pulled, that it's of the appropriate quality, that they take account of privacy and don't share more data with systems than they need.
5. They take account of security and make sure that the AI systems are only accessing what they need to access to in order to provide their functionality.

This needs to be overseen by a broad and diverse team to make sure that all perspectives are brought to bear on how to best manage and govern data assets in a world of AI