What has your organization done to ensure data privacy and security while beginning to explore AI?
Marketing campaign automation using AI is frequently cited as a strong lever for business growth. 88% of marketers believe AI adoption is critical for meeting customer expectations, promising improved acquisition and retention. In a reaction to concerns over consumer privacy and data security, businesses are applying AI instead to internal marketing operations.

SAESO are technology consultants with a successful track record in executing complex technical solutions, specializing in data privacy, security, and AI in marketing.  SAESO helps clients in highly regulated verticals take the first steps with AI. 

Marketing Operations: A Starting Point for AI Integration
New opportunities are rapidly emerging as business apply AI technology to various functions to achieve greater efficiency and innovation. Marketers have taken to integrating AI into consumer facing campaigns, but in light of mounting compliance concerns, as a recent article highlighted, using AI to streamline internal processes instead may present less resistance in the privacy and security domain.

Marketing operations represent a promising starting point for AI integration – with the ability unlock significant opportunities in efficiency and effectiveness within the organization.  AI can free up internal value by identifying and removing limiters with existing marketing processes. 

Rather than advocating for use of AI on customer data sets, SAESO works with clients to apply AI to internal data sets – in order to streamline creative processes, organize measurement, and prioritize internal initiatives.  The crucial step is in identifying which business processes will benefit most – those with clear objectives and substantial data generated for AI to analyse.

Hidden Opportunities and Removing Bottlenecks
Unsupervised AI, which learns without labelled data, can be advantageous in understanding and automating repetitive internal business processes. This approach can uncover patterns otherwise hidden – without the decision-making errors that can impact human supervised AI systems, often used in campaign automation.  A 2023 MIT study examined how human labelling can unfavorably impact machine learning (ML) models.

Even without AI, businesses have has seen an explosion of campaign variants due to modern martech capabilities, and Marketing’s ability to service has become the bottleneck.  Human inputs – large volumes of content and consumer insights – are now the limiting factor in enabling experiences that consumers expect.  Businesses can use AI to help internal teams keep up and, thereby, realize these opportunities.

Marketing Campaigns and AI Compliance Risk

Businesses using AI in consumer marketing face a landscape of shifting legal concerns. Legal experts are still evolving an understanding of the implications of AI. Emerging laws on data privacy and AI controls have put business compliance in the spotlight. Governance helps minimize risk but is often insufficient. A 2023 report found only 21% of organizations with AI adoption had established policies governing use of generative AI​​​.

Some risks associated with using AI in consumer facing experiences include:

  1. Errors in Data Handling – risks lie with programmatically managing data, particularly in the handling of AI inputs and outputs.
  2. Data Breach Risks – As AI data consumption increases, breaches are more likely, and severity of consequences increasing.
  3. Errors in Generation –  AI-generated content can contain inaccuracies or unintended biases, leading to potential misinformation or reputational damage.
Accounting for Privacy and Security from the Start

Navigating this complex landscape means taking a realistic look at complying with privacy laws and protecting sensitive data.  With the right approach, businesses can derisk the use of AI.

By focusing AI internally, businesses can wade into the opportunities presented by AI. As regulations limit the use of AI, an organization can take this lower risk approach to begin figuring out what AI means for the business.