Navigating the GenAI Revolution: 5 Strategies for Safe and Effective Marketing

Udittha is the CMO of Travers.io, a sports AI technology company, with 16 years of experience in marketing technology roles at companies like Adobe, Salesforce, Rakuten, and WPP.

The presentation focuses on strategies for using generative AI in marketing while prioritizing safety, ethics, and compliance.

Key milestones include the movement of software into cloud systems, the rise of mobile internet, the impact of social media, and the development of big data and tools like Customer Data Platforms (CDPs).

Predictive AI classifies, predicts, and takes actions based on data, while generative AI creates new content such as text, images, or videos based on input data.

Risks include data breaches, intellectual property theft, compliance violations, misinformation, and damaging brand reputation.

Companies can implement data security frameworks, create secure user interfaces, conduct regular risk assessments, prioritize ethical AI use, and invest in employee training.

A data security framework involves protecting sensitive information through methods like masking and secure data retrieval, ensuring data is not retained after use.

Ethical AI ensures transparency and trust in how AI is used in marketing, helping to maintain customer trust and avoid legal issues.

Continuous education and training ensure that employees understand how to use generative AI responsibly and effectively, reducing the risk of data leaks and compliance issues.

Hybrid systems combine local and third-party AI models to balance customization and data security, although they require significant management and integration efforts.