The Gist
- AI enhances creativity. Generative AI revolutionizes content creation, enabling personalized customer experiences that boost engagement.
- Govern with care. Establishing strong governance frameworks for generative AI ensures ethical use, aligning with company and legal standards.
- Aim for balance. While generative AI excels in speed and efficiency, human insight remains crucial for genuine creativity and innovation.
According to IDC, enterprises spent an estimated $19.4 billion on generative AI solutions in 2023 — and may invest as much as $151 billion by 2027. As ChatGPT, Google Gemini and other generative AI marketing solutions take up residence in marketing departments everywhere, organizations are finding new uses for them daily.
From writing website content and articles, to creating email campaigns, company newsletters, branding campaigns and a host of other content, the speed at which it can be created is astonishing — akin to the fascination of cave dwellers seeing fire for the first time.
Yet despite all of its benefits, there are certain downsides, and organizations need to take a strategic approach to make sure they benefit from AI, without burning their corporate reputation, or reducing their hallmark of quality. It’s crucial for enterprises to establish robust governance and best practices to ensure ethical and effective generative AI use.
Let’s take a look at generative AI in marketing.
The Rise of Generative AI in Marketing
Generative AI, a subset of artificial intelligence, uses algorithms fueled by training data to generate content, automate tasks, analyze data and make decisions. In addition to content, generative AI in marketing is proving to be invaluable in various applications, such as predictive analytics, customer segmentation and campaign optimization.
Content Creation and Personalization
One of the primary ways marketing departments are harnessing generative AI is through content creation. AI-driven tools can generate compelling and relevant content at scale, freeing up marketers to focus on strategy and creativity. This enables businesses to create personalized experiences for their target audience, increasing engagement and brand loyalty.
Predictive Analytics and Customer Segmentation
Generative AI is a game-changer when it comes to predictive analytics and customer segmentation. By analyzing historical data, AI algorithms can identify patterns, predict customer behavior and segment audiences more accurately. This allows marketers to tailor their campaigns to specific customer segments, maximizing the impact of their efforts and allowing them to better engage with specific audiences and personas.
Campaign Optimization and Performance Monitoring
Digital marketing is a fast-changing specialty requiring constant pivoting, so real-time optimization is crucial. Generative AI algorithms can continuously monitor campaign performance, analyze user interactions and make data-driven recommendations to optimize the campaign. This ensures that marketing efforts are always aligned with the evolving preferences and behaviors of the target audience.
Related Article: Beyond Hype: Practical Applications and Limits of Generative AI in Marketing
The Problems With Generative AI
While generative AI presents numerous opportunities for marketing success, there are inherent challenges and potential risks that require sound governance to ensure responsible and ethical use of this powerful technology. Consider the following to ensure safe and fair AI usage.
While generative AI presents numerous opportunities for marketing success, there are inherent challenges and potential risks that require sound governance to ensure responsible and ethical use of this powerful technology.charles taylor on Adobe Stock Photos
Ethical Considerations
Issues such as bias in algorithms, privacy concerns and the potential misuse of AI-generated content are very real issues to be addressed. Enterprises must establish clear guidelines to ensure that their generative AI applications align with their ethical standards, consistent with their company image and comply with legal requirements.
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Data Security and Privacy
A recent study by Cisco revealed that most organizations are limiting the use of generative AI over data privacy and security issues; and that 27% have banned its use altogether. Generative AI relies heavily on data, and marketing departments must ensure the security and privacy of the information they use. Implementing robust data protection measures, obtaining user consent when using their data and complying with data regulations are critical aspects of generative AI governance.
Transparency
In line with data privacy measures, clear accountability and transparency are essential components of generative AI governance. Marketing teams should have a thorough understanding of how their generative AI solution is making decisions and what datasets it was trained upon and be able to explain the decision-making process to stakeholders. The problem is that models can’t always distinguish between fact and fictional data, so accurately vetting that data is crucial.
How to Establish Generative AI Governance
To establish effective generative AI governance, marketing departments in enterprises should follow best practices and solidify rules of play. This governance, however, can’t be confined to the marketing team, but must be established enterprise-wide, through cross-functional collaboration between marketing, legal, IT, HR and line-of-business departments. This can help to ensure that the use of generative AI aligns with the overall business strategy, complies with legal requirements and adheres to ethical standards.
Below are other concrete steps that can be taken.
Define Clear Objectives
Before implementing generative AI, determine what it is you are hoping to accomplish with it and then set key performance indicators (KPIs). This can help you determine what may be the right solution for your enterprise and track progress.
Offer Training Programs
Generative AI is a brand new concept for many employees. Marketing teams should be equipped with the knowledge and skills to understand, implement and monitor AI applications effectively. Training programs should cover ethical considerations, data security protocols and the potential impact of AI on job roles.
Appoint a Generative AI Leader
Staying abreast of evolving data protection and privacy regulations will continue to be a moving target as both federal and state governments continue to work to set policy and legislation. By making it one person’s, or a small committee’s responsibility to stay on top of changing requirements, as well as validate the data being used to train large language models, you can avoid legal complications and ensure that your organization is a responsible data steward.
Take an Incremental Approach
Starting small with a less risky project can help you better understand how generative AI will fit into your organization. Using a generative AI tool, for example, to help come up with a tagline for a branding campaign, can help you better understand the role it can play, identify challenges and make necessary adjustments before scaling up across the entire organization.
Build a Governance Framework
The training criteria for every generative AI solution being used should be understood, documented and readily available when requested. This framework should require that end-users receive clear notification when they are interacting with AI. Determining whether to label content created by AI should be an enterprise decision that is not currently mandated by law. When content created by generative AI is drastically altered by human writers, companies may choose not to label it as AI generated; however, each company should determine and articulate its own standards.
While creating a generative AI governance framework is essential, enterprises need to consider a less tangible and overarching philosophy to how they approach the use of generative AI and instill it into their company culture.
Marketing is a creative endeavor, requiring the writing skills, design specialty, insights and ingenuity that ultimately can only be created by humans. By treating generative AI in marketing as a research tool to ignite new ideas or content, instead of the final product, we can be assured that it takes its rightful role as a facilitator to the brilliance of marketers.
