Digital transformation is more than just a buzzword; adopting artificial intelligence (AI) in marketing strategies has become a pivotal turning point for agencies and marketers alike. The question is no longer about whether marketers should adopt AI but when and how to integrate it effectively. This evolution brings forward many considerations, ranging from choosing the right area of implementation, navigating the complexities of data security, sorting through the variety of tools available, and fostering an AI-centric culture within an organization. Let’s dive into some of these critical aspects to help marketers navigate the AI landscape with confidence and clarity.
1. Adoption: It’s Not Should Marketers Adopt AI, It’s When and How
Integrating AI into marketing strategies offers unparalleled advantages, including enhanced customer insights, automation of repetitive tasks, and the ability to predict consumer behavior more accurately. However, the adoption process involves strategic planning and a step-by-step approach. Start by identifying specific marketing challenges or opportunities where AI can provide a competitive edge, such as personalization, customer segmentation, or real-time optimization of marketing campaigns. It’s crucial to set clear objectives, understand the capabilities of AI technologies, and ensure alignment with overall marketing goals. The use of AI alone isn’t enough to stand out in the marketplace. Differentiating your work through strategic and innovative use of the tools will be what sets you apart, not the tool itself.
2. Tips for Effective Implementation
To harness the full potential of AI, marketers must focus on effectiveness and efficiency. Here are several tips to consider:
- Start Small and Scale: Begin with pilot projects to test and learn. This approach allows for adjustments and implementation of best practices before a full-scale implementation, reducing the risk and investment. One of our first tests at KSM was using ChatGPT to streamline time-consuming tasks in our Ad Trafficking QA process. We started small, combining two documents in a process that previously required manual data entry from one document into another. It took a few rounds of testing, training, and ensuring accuracy, but we now use AI to perform that step with human oversight, saving us hours of manual input time.
- Be Specific: When crafting prompts, be specific. Provide background, goals, desired tone and format, and anything else to help the AI get you closer to your desired output. Develop prompting templates for similar tasks to become even more efficient.
- Focus on Data Quality: AI systems are only as good as the data they process. Invest in data cleansing and enrichment to ensure AI models generate accurate and actionable insights. If you have 1st party data, leverage it for the most accurate results.
- Continuous Learning and Adaptation: AI models can improve over time through machine learning. Regularly update the models with new data and feedback to enhance their accuracy and relevance.
- Integration with Existing Systems: Ensure that AI tools seamlessly integrate with existing marketing platforms and tools to streamline workflows and data analysis.
- Generate and Edit: AI is not the be-all-end-all. Always review outputs and edit/iterate as needed. Especially when working with creative and strategic outputs, a hybrid AI/human approach gives you the best of both worlds. This article, for example, started as an outline with bullets entered into ChatGPT, which filled out some details. From there, human editing reworked any inaccuracies or awkwardness and added additional information. Finally, Grammarly checked the article for grammar errors and opportunities to streamline and ensured that ChatGPT hadn’t plagiarized any elements. With humans and AI alternating work, this four-step process cut overall production time in half while maintaining integrity in the output.
Keep in mind: if you’re not paying for a product, your data is the product.
3. Data Considerations and Risk
The use of AI in marketing often involves processing vast amounts of client data, raising critical privacy and security concerns. Adhering to data protection regulations, such as GDPR in Europe or CCPA in California, is non-negotiable. Ensure clear communication with your agencies or marketing teams about how your data is used, the risk/benefit analysis, and guardrails around what can and cannot be used. For the best data security, avoid “off-the-shelf” AI solutions; many tools now include paid enterprise features that promise security and confidentiality. Keep in mind: if you’re not paying for a product, your data is the product.
There are also legal considerations surrounding AI-generated content creation. Copy created with the assistance of AI tools may be copyrighted or inaccurate and requires a human review. Copy or art created wholly by AI is not currently eligible for copyright protections under U.S. law. Given these, using AI to develop original content is not recommended—instead, remix, rework, and test to save on time and costs without risking legal, ethical, or quality concerns.
4. Creating a Culture of AI
Creating a culture that embraces AI within the organization is as important as selecting the right tools. This involves fostering a mindset of innovation and continuous learning among team members, driven by support from leadership. Include diverse perspectives when discovering and developing new use cases and best practices to make scaling across the organization easier. Finally, promoting an environment of experimentation, curiosity, and openness to change can help demystify AI and encourage creative applications of AI in marketing strategies. At KSM, our AI Exploratory Cohort—which includes KSMers of various levels and across all disciplines—gathers at least monthly to share success stories, brainstorm new ways of applying AI to our work, and make recommendations for scaling successful integrations across the agency. This approach has allowed us to test and learn at a manageable scale while creating excitement and a desire to adopt AI more broadly.
The Biggest Risk is Not Leveraging AI at all.
Integrating AI into marketing is not a fleeting trend but a fundamental shift in how marketers understand and engage with their audiences. By carefully considering when and how to adopt AI, focusing on effective usage and efficiency, navigating the complexities of using data and creating content, and fostering an AI-centric culture within the organization, marketers can leverage AI to reach their goals with greater efficiencies and an emphasis on innovation and creativity. The future of marketing lies in the strategic use of AI, and the time to start planning and implementing AI strategies is now.