KPM Blog

Understanding Data Privacy and Personalisation in AI Marketing

As artificial intelligence (AI) takes the world by storm, companies are embracing AI marketing in their droves. In fact, 61% of marketers have used AI in their marketing activities, and 88% believe their organisation will need to increase its use of automation and AI to meet expectations and remain competitive. (Source: Martech)

But while AI might enable marketers to make tailored product recommendations and personalised content – something that today’s customers have come to expect from their most beloved brands – there are several ethical considerations when embracing all that AI has to offer.

From privacy violations to protecting consumer data, modern marketers have much to think about.

AI Marketing and Data Privacy

The reason AI is gaining popularity with marketing teams the world over is its ability to process vast amounts of data and translate it into an understanding of consumer data in record time. This has led to 31% of marketers reporting that personalised, automated omnichannel campaigns were the most beneficial area for AI marketing. (Source: Instapage)

In its simplest terms, AI empowers marketing teams to be altogether more targeted in their outreach. But in analysing such large amounts of personal data – from purchase history to social media activity – AI marketing leaves itself open to everything from potential data breaches to discrimination bias.

  • Privacy Breaches: The vast amount of personal data collected for AI marketing purposes can be vulnerable to breaches, leading to unauthorised access and potential misuse of sensitive information.
  • Discrimination and Bias: If AI algorithms are trained on biased data, they could play into existing societal biases.
  • Lack of Transparency: AI models can be highly complex, making it difficult to understand how personal data is used and decisions are made. This raises understandable concerns about accountability and transparency.
  • Manipulation and Exploitation: Personal data can be exploited to manipulate consumer behaviour, influence opinions, or deceive people through targeted advertising or misinformation campaigns.

With ever-increasing concerns about the way that AI tech is collecting, sharing, and using personal data, companies need to ensure personalisation is transparent and respectful, without being intrusive.

Ethical Considerations for AI Marketing

From ethical AI to regular audits, these are just some of the areas that you need to consider when building AI into your marketing campaigns:

  • Robust Data Protection: When using AI for marketing, stringent data protection controls must be in place to safeguard personal data – ensuring transparency, consent, and user control over data collection and use.
  • Ethical AI Development: Marketing teams must carefully assess their processes and include ethics and anti-bias reviews as part of the AI development cycle.
  • Empowering Individuals: Consumers should have clear options to control and understand how their data is being used.
  • Continuous Evaluation: Regular audits and assessments of AI systems can help you to identify and rectify potential biases, safeguard privacy, and improve system transparency.

But you also need to make sure you’re remaining on the right side of the law!

Legal Considerations for AI Marketing

As a marketing pro, you have the power to build solid relationships with your audience; relationships that turn potential customers into loyal consumers – but that also means you must tread carefully with customer trust.

To make sure you’re using AI responsibly – and legally – this is what you need to keep in mind:

1 Compliance with Data Protection Laws

Anyone responsible for using personal data must make sure the information is:

  • Used fairly, lawfully and transparently
  • Used for specified, explicit purposes
  • Used in a way that’s adequate, relevant and limited to only what’s necessary
  • Accurate and, where necessary, kept up to date
  • Kept for no longer than is necessary
  • Handled in a way that ensures appropriate security, including protection against unlawful or unauthorised processing, access, loss, destruction or damage

2 Data Minimisation

When integrating AI into your marketing efforts, keep data minimisation front of mind; in other words, avoid collecting excessive or unnecessary personal data. Outlining objectives for the application and use of AI is crucial for compliance.

3 Lawful Basis for Data Processing

Establish a lawful basis for processing personal data within AI systems. The most common bases are consent, contract performance, compliance with legal obligations, and legitimate interests.

  • Consent may be appropriate when you have a direct relationship with the person whose data you want to process, but you must ensure that consent is freely given.
  • Contract performance can be used as a lawful basis if processing using AI is ‘objectively necessary’ to carry out a contractual service.
  • Processing personal data may be necessary if you’re required to audit your AI systems to make sure they’re legally compliant.
  • Legitimate interests may be the most flexible lawful basis for processing, but it’s not always appropriate – for example, if the way you intend to use data is unexpected or could cause unnecessary harm.

4 Data Accuracy and Transparency

AI algorithms learn and make decisions based on the data they receive, so it’s crucial to ensure the accuracy of the data used to train AI models. You should also be transparent with people about how their data is being used.

5 Individual Rights

The GDPR grants people the right to access their data, correct inaccuracies, request deletion, and object to processing. You must have mechanisms in place to address these rights when using AI in your marketing.

6 Data Security Measures

AI systems often process large volumes of sensitive data, making them potential targets for cyberattacks. It’s important to implement robust data security measures to safeguard personal data from any unauthorised access, disclosure, or alteration.

7 Data Protection Impact Assessments (DPIAs)

DPIAs must be carried out every time new technology is introduced that could impact personal data – making it necessary to perform a DPIA when implementing any AI system. A DPIA helps to identify and mitigate potential privacy risks, demonstrating your commitment to responsible data management.

8 Third-Party Agreements

If you’re using third-party AI services or collaborating with other organisations, comprehensive data processing agreements can outline the responsibilities of all parties involved. When using AI tools that are general use and open source, strong policies governing the use of those tools in business should be put in place.

9 Retention and Disposal Policies

Personal data should never be kept longer than necessary; when data is no longer required, dispose of it securely.

10 Privacy First Planning

Embedding the best possible data privacy settings and technical means – such as data pseudonymisation and anonymisation – into AI processes can help to ensure ethical usage.

Discover how we can support your marketing campaigns with personalised print that builds trust and boosts results. We’ll even give you a free data health check to ensure the data you’re relying on is healthy, before helping you to optimise it with our data management service!

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Discover how effective your mailing data is with our free report and recommendations. You’ll gain insights into the quality of your data and see how much of your data is healthy. Plus, we’ll include recommendations for improvement and next steps.

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