Steps for creating an ai-focused data strategy
Posted: Wed May 28, 2025 4:59 am
following this process will set you on the road to realizing the potential of ai through data:
start with business objectives and use cases: it’s like your home remodeling — you think about how you can make your home more functional and efficient, not necessarily what hammer or power drill you would use for the remodeling. Identify the specific use cases you are trying to solve and see how ai can help meet those requirements. What are your top business objectives that can benefit from ai, such as process automation, segment creation, creating product descriptions and case summaries? Look for processes that can be streamlined to be efficient. Think big and start small.
Ask: who would benefit from this? Is it your customers, partners, employees? Would it increase revenue? Would it improve customer experience? Also, how would you measure success?
Identify, collect, and aggregate data: understand data sources and how the data flows within your organization. Identify what data is needed to fulfill the above use cases. Take into consideration all the various data sources where you might have customer data residing, such as data warehouses, data lakes, operational data stores, and even spreadsheets. Also, data america phone number list could be structured or unstructured, ranging from sales transactions to call recordings to social media comments. To achieve good ai outputs, ensure your data is complete, accurate, reliable, relevant, and timely.
Ensure regulatory compliance: based on a recent survey, 79% of it leaders believe generative ai will introduce new security risks to company and customer data. Prioritize data privacy and security as you craft your data strategy. Use best practices, such as data encryption, multi-factor authentication and identity and access management to ensure safeguard data security. Checks and balances from both humans and technology are a way to protect your customers, your company, and your ethical standards.
Establish data governance: implement robust data governance practices to ensure data integrity, security, and accessibility. Strong data governance frameworks lay the foundation for ai initiatives.
With deeper data insights and the power of ai, your business can deliver improved customer experiences: enabling product recommendations, services, and personalization that resonates — while helping you gain efficiencies in operations and revenue along the way.
start with business objectives and use cases: it’s like your home remodeling — you think about how you can make your home more functional and efficient, not necessarily what hammer or power drill you would use for the remodeling. Identify the specific use cases you are trying to solve and see how ai can help meet those requirements. What are your top business objectives that can benefit from ai, such as process automation, segment creation, creating product descriptions and case summaries? Look for processes that can be streamlined to be efficient. Think big and start small.
Ask: who would benefit from this? Is it your customers, partners, employees? Would it increase revenue? Would it improve customer experience? Also, how would you measure success?
Identify, collect, and aggregate data: understand data sources and how the data flows within your organization. Identify what data is needed to fulfill the above use cases. Take into consideration all the various data sources where you might have customer data residing, such as data warehouses, data lakes, operational data stores, and even spreadsheets. Also, data america phone number list could be structured or unstructured, ranging from sales transactions to call recordings to social media comments. To achieve good ai outputs, ensure your data is complete, accurate, reliable, relevant, and timely.
Ensure regulatory compliance: based on a recent survey, 79% of it leaders believe generative ai will introduce new security risks to company and customer data. Prioritize data privacy and security as you craft your data strategy. Use best practices, such as data encryption, multi-factor authentication and identity and access management to ensure safeguard data security. Checks and balances from both humans and technology are a way to protect your customers, your company, and your ethical standards.
Establish data governance: implement robust data governance practices to ensure data integrity, security, and accessibility. Strong data governance frameworks lay the foundation for ai initiatives.
With deeper data insights and the power of ai, your business can deliver improved customer experiences: enabling product recommendations, services, and personalization that resonates — while helping you gain efficiencies in operations and revenue along the way.