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Data and AI ethics principles

Explore how Sage upholds the highest standards in data and AI ethics, ensuring your data's integrity and security. Our commitment is rooted in transparency and trust, safeguarding you and your business with ethical diligence.

Sage data and AI ethics principles

In a constantly changing world, we are committed to integrity, transparency, and trust. Our data principles may adapt to stay aligned with our customers' needs, the evolving business landscape, and regulatory requirements.

Data security and privacy first

Principle 1

First and foremost, you can trust us to keep your data safe and secure, and to comply with data privacy and other applicable laws.

  • We keep this commitment central to everything we do with your data.
  • We apply internationally recognised standards to data security and use independent assessments to test how well we are applying those standards.
  • We are open about our approach to data security and data privacy, describing what we do in simple, clear language, stripping away the jargon.
  • We recognise that security and fair and responsible use is important for business data as well as personal data, so these principles apply to both.

To learn more on how we approach data security and privacy, explore the rest of our Trust and Security hub.

Customer choice

Principle 2

Some of our products, features and experiences are built using your product data or other data or involve sharing your data across our trusted network. When we do this we are transparent about how we use your data and the choices you have.

  • We do not share your identifiable data with third parties unless you give us permission first, either explicitly or by choosing to use a product or feature that requires sharing. We make it clear when sharing is required and share only the minimum data necessary.
  • When using your anonymised product data to build products, features or experiences, or as part of our Using Data for Good work, we do not offer a choice on whether your anonymised data is used.

Customer benefit

Principle 3

We use your product data and other data to develop innovative and powerful new products, features and experiences to help your business and your employees thrive.

  • We believe data has enormous potential to help you and your employees thrive.
  • Where it is allowed under applicable laws, we analyse your product data and/or other data, together with data from other Sage customers, to enhance your experience with Sage, simplify your business processes and solve common problems and to develop and train AI models to create new products, features and experiences.
  • When doing this, we may give carefully selected Sage employees temporary access to your product data as part of a sample, with data from other customers. If this happens it is done with strict controls to ensure security and protect your privacy.

Charging for access to data

Principle 4

We may charge for access to products and features built using your product data.

  • We build products and features that provide insights or predictions derived from your product data, together with data from other customers and other data. We also build products and features that allow you to share your identifiable product data with third parties.
  • We may charge for use of these products and features. If we do charge, we are transparent and open about the charges.

Using data for good

Principle 5

We use your product data to help find and fix common problems facing small and medium sized businesses and wider society.

  • Our purpose is to knock down barriers so everyone can thrive. We analyse your product data together with data from other customers and other data, to help us better understand the barriers and problems SMBs are facing and to identify solutions. We publish these insights or use them to help us be a more effective public voice, speaking up for all SMBs’ interests.
  • We sometimes work together with governments or trusted partners to do this analysis and may share your anonymised product data with them. We assess the security approach of partners before agreeing to share data.

Read more about our approach at our Sustainability and Society hub.

Data quality matters

Principle 6

We make sure data quality is as good as possible so you can trust the insights and recommendations that flow from it.

  • We understand that the value of insights and recommendations that we make from data depends on that data being accurate, relevant, complete and up to date. This includes data that we control in our websites and internal systems, and also data in our products and services that you control as a customer.
  • We have put in place teams and processes internally to look after data quality.
  • We build features into our products, services, websites and internal systems that help detect and remove data errors and improve the quality of your data.
  • When we build products and features that involve data sharing, we include features that help data recipients have more trust in the accuracy of the data they receive and where it came from.

Diversity and bias management

Principle 7

We work to manage bias in our AI models to help make sure that everyone affected by our AI models is treated fairly and without discrimination.

  • We look carefully at the datasets we use to manage the risk of bias in our AI models.
  • We design our AI models with the management and prevention of discrimination and stereotyping in mind.
  • We build AI models using diverse teams from a wide range of cultural, academic and professional backgrounds.
  • Our AI and Data Ethics Council, which will help us make ethical decisions on how we use data, will include members who are specifically focused on diversity and bias management.

Human-centric AI

Principle 8

We will always empower you to make decisions on how AI in our products affects your business.

  • We ensure that you can understand and control how AI in our products affects your business.
  • We build features that allow you to decide how much automation you want to allow or how much you want to review recommendations before they are applied.
  • Where possible, we make it simple for you to understand the recommendations made by AI.
  • You can override recommendations made by AI. When you do this, we use your feedback for improvement, so your trust in the recommendations increases over time.

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