NBS Knowledge Lab Webinar: Data Privacy, AI, and Consumer Behaviour: Navigating the Complex Landscape

Key Takeaways for Businesses 

1. Consumer willingness to share data is influenced by perceived value, convenience and trust. 

2. Transparency, simplification and clear communication about data usage can give companies a competitive edge. 

3. Privacy management is becoming increasingly complex as AI enables inference beyond explicit consent. 

The Evolving Dynamics of Data Sharing 

Dr Verina highlighted the difficulty consumers face in distinguishing between privacy-conscious apps and riskier alternatives. “Bad players drive out the good players because there’s no clear way for privacy-centric companies to signal their value,” she said, stressing the need for top-down regulations or industry standards to simplify consumer choices and prevent a “market for lemons.” 

Prof Ramanathan added that business models play a central role in privacy outcomes. Companies like Apple, whose revenue is not tied to user engagement, can prioritise privacy features such as screen time limits. In contrast, platforms like Facebook or TikTok profit from maximising time spent on their apps, making ethical data practices more challenging. He noted that trust and transparency are key drivers for consumers when sharing data, alongside a tangible value exchange. 

Ms Josephine emphasised the behavioural drivers behind data sharing, noting that AI and instant gratification have heightened willingness to give personal information. She cited examples such as IoT devices and DNA testing services, where convenience and curiosity motivate consumers to share data voluntarily, sometimes with unforeseen risks. “The risks are more significant than we often realise, especially when data falls into unintended hands,” she said. 

Understanding the Privacy Paradox 

Mr Vidyarth and Dr Verina explored the “Privacy Paradox,” where consumers’ stated preferences for privacy often diverge from their actual behaviour. While users may claim to value privacy, they frequently share personal data when motivated by convenience or perceived benefits. Dr Verina argued that the perceived utility of sharing data is rarely quantified, suggesting that clearer communication about value - such as saving time or gaining control - could improve informed decision-making. 

Prof Ramanathan summarised the challenge: “When the service is free, you are the product. Consumers often take frictionless experiences for granted, without realising the hidden cost is their data.” 

Future Trends: AI, Transparency and Cybersecurity 

Panellists agreed that as AI continues to advance, the definition of private data will expand. Prof Ramanathan noted that AI can infer personal information from behavioural patterns, creating new privacy challenges. Ms Josephine stressed the importance of cybersecurity, citing persistent risks of data leaks and identity theft. 

Mr Vidyarth highlighted the competitive advantage for companies that simplify privacy and empower consumers to control their data. He also noted that AI could be leveraged to enhance security, detect privacy concerns and create new business opportunities. Dr Verina emphasised transparency, calling for clearer regulatory guidance on data usage and inference, including potential economic implications. 

Balancing Privacy with Visibility 

The webinar also addressed how individuals can maintain privacy while building professional visibility. Ms Josephine argued that privacy is contextual, individuals can achieve brand visibility without oversharing by carefully defining personal boundaries. Mr Vidyarth added that consumers should be able to remove their data from platforms, with services offering monitoring and reporting as potential solutions. 

Dr Verina concluded with a reminder about the cognitive sophistication required to maintain privacy: “Private nowadays means friction. If something feels smooth and convenient, there’s likely a hidden privacy cost.” 

Looking Ahead