AI & Data Innovation


The trusted use of data is the foundation of a vibrant Digital Economy, and trusted data flows have the potential to deliver tremendous benefits to both organisations and consumers. For organisations, it facilitates more effective information exchanges, and enables shared data assets (e.g. between business partners) to support the development of innovative solutions, to customise services and processes for different market segments. For consumers, their willingness to share their data with organisations reflects the amount of confidence they have in an organisation’s ability to use and safeguard data. The intent of the Framework is that with stronger safeguards and clarity on regulatory compliance, consumers will be more ready to share their data and consequently benefit from more personalised goods and services.

Data sharing

To facilitate and support businesses in their development and adoption of Artificial Intelligence (AI) and Data projects to create/uncover new value for themselves, partners and/or customers. Any businesses interested in harnessing value of data, sharing of data, develop AI solutions or adopting AI can refer to the following programmes and guides.


Data Collaborative Programme

Data service intermediaries, i.e. companies that offer platform or services to enable exchanges of data, can participate in the Data Collaborative Programme

Related Programmes:

Startup Station Singapore 

Startups that are innovating with Data and AI may check out Startup Station Singapore, a joint programme by IMDA and Facebook, to provide start-ups with mentorship and guidance for their businesses.  Recruitment of Season 1 has closed and interested startups can look forward to Season 2 at end of 2019.

SME Digital Tech Hub

SMEs interested to harness the value of data and adopt AI to improve efficiency of businesses and generate new business value, can approach SME Digital Tech Hub


Useful Guides:

Trusted Data Sharing Framework

Businesses or individuals who wish to understand data sharing concepts or key considerations when planning data partnerships can refer to the Trusted Data Sharing Framework (4.42MB)

Access the templates and resources reference by Trusted Data Sharing Framework here:

Legal Templates for Data Sharing:

Data Sharing Agreement (51.66KB)

Confidentiality Agreement (41.35KB)

Data Subject Consent (27.61KB)


How Can Your Organisation Dispose of Personal Data (224.12KB)

Guide to Data Valuation for Data Sharing

Businesses can establish common baseline for valuing data to be shared using Guide to Data Valuation for Data Sharing (2.03MB)

Personal Data Protection Act

Businesses planning to share personal data within and between companies, can refer to the Personal Data Protection Act (PDPA) and the Advisory Guidelines published by the Personal Data Protection Commission (PDPC).

AI Governance Framework

AI solution providers and businesses keen to find out more about AI Governance, can refer to the Proposed Model AI Governance Framework.

Other Resources

For broad, common data sharing scenarios, particularly in relation to training AI models, can refer to the three model data use agreements published by Microsoft, and the two agreements optimized for “open” data are posted on GitHub here and here for community input.


Companies can also write in to, or approach an IMDA Data Innovation Programme Office (DIPO) officer for discussion.

regulation and licensing

Data Protection Trustmark Certification

To help businesses increase their competitive advantage and build consumer trust, IMDA has launched the Data Protection Trustmark (DPTM) certification to help organisations demonstrate sound and accountable data protection practices.

Find out more

Last updated on: 06 Nov 2019