Generative AI in Marketing: Do the Benefits Outweigh the Risks?

What is generative AI? Generative AI (Gen AI) is artificial intelligence capable of generating text, images, or other media, using generative models. Generative AI models learn the patterns and structure of their input training data and then generate new novel and unique data with similar characteristics. [source]

The more data the AI models consume the more they learn. They are currently able to deliver human-level results, but with time they will be able to deliver superhuman-level results, transforming productivity. The data sources fed into a model could include marketing trends, customer purchasing behavior, demographics, digital interactions, web analytics, and more. The value and accuracy of data used for training determine the effectiveness of the outcome. The trained model can then generate content such as articles, banner ads, blogs, personalized videos, emails, and more, that resonate with the target audience.

Marketing has seen an explosion of innovation reshaping the field. Generative AI is one such game-changer technology that allows today’s marketers to stay ahead of the curve. It allows for innovative solutions to age-old problems by automating repetitive tasks, increasing scalability, personalizing interactions, and enhancing creativity. While 98% of executives said that Gen AI was a hot topic of discussion with their board [1], only 14% of organizations were using Gen AI for Marketing and Sales [4]

Source [1] [2] [3] [4]

The popularity of generative AI use has skyrocketed with the release of ChatGPT. There are many benefits of using this revolutionary technology in marketing and sales, but we should be aware of the risks as well.

Benefits and Risks of Using Gen AI in Marketing:

Top Benefits

Increased Efficiency: Gen AI can automate repetitive and tedious tasks, increasing the speed of execution, freeing up resources, and increasing efficiency. 58% of marketers reported increased performance as the top benefit of using Gen AI [source]

Personalization: Marketers can now create personalized messages that are tailor-made to individual user signals. It is possible to deliver these personalized messages at scale across multiple channels. It is a key driver for increasing customer engagement and the likelihood of conversion. Personalized content includes emails, website experience, videos, product recommendations, and more.

Increase Sales: Most CRMs now incorporate AI that allows sales to leverage Gen AI and predictive analytics to understand a prospect’s propensity to purchase and assist them throughout the sales cycle. Sellers can now automate manual tasks, decipher actionable insights from sales calls, create personalized messages, schedule meetings, and nudge customers for follow-up. The ability to respond quickly at the right time helps accelerate sales.

Reduce Cost: Automation saves time and reduces costs associated with manual labor, targeting inconsistencies, and lack of scalability. 50% of marketers reported cost efficiencies as the top benefit of using Gen AI [source]

Data insights: AI models can analyze large amounts of data providing insights into marketing trends, campaign performance, and customer preferences. These platforms can also anticipate customer behavior, identify patterns, and predict future trends. Marketing can use this information to make informed decisions to stay ahead of the curve without the need for highly skilled technical resources.

Creativity: Gen AI helps artists explore new styles or design variations that were based on their original work. This helps increase creative cycles. They can also design new media forms without having to start from scratch. 47% of marketers reported faster creative cycles as the top benefit of using Gen AI. [source]

Customer Satisfaction: The ability to have one-on-one interactions with customers based on their needs, interactions, and behaviors allows marketers to increase customer engagement and satisfaction.

Some of the Risks Include:

Security: Employees can upload confidential information onto platforms such as ChatGPT without realizing the consequences. As the model learns, they can incorporate the sensitive information into future results. It is important to choose a platform that prioritizes the handling of secure data in a manner that is consistent with a company’s policies.

Bias: AI platforms learn from what they have been programmed for and the data that was fed into them. Biases in programming and data are generally reflected in the results.

Privacy: The models learn from large data sets. Exposing personnel records or sensitive photos could result in them being incorporated into the results, resulting in privacy and legal concerns. Non-consent deep fake videos and images are a major concern that should be addressed.

Regulation: Governments have only recently started introducing legislation and some safeguards. They are well behind the curve. Many restrictive industries are hesitant to embrace Gen AI due to a lack of regulations governing its use. Future regulations could be a bit more severe to prevent misuse and this could limit the technology use for genuine uses.

Creative Limitations: Gen AI is not truly independent, nor does it have the emotional intelligence of humans. It understands the context of the data that it consumes and responds accordingly. It helps amplify human abilities. Many of the Gen AI applications use the same underlying models and are trained on similar datasets resulting in a lack of differentiation.

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