In the rapidly evolving world of marketing, artificial intelligence (AI) has transitioned from mere technological advancement to a cornerstone of strategic innovation. With nearly 80% of companies expecting AI to significantly impact their industries within the next two years,1 the urgency for marketers isn’t just about adopting AI — it’s about quickly and thoughtfully harnessing it to redefine strategic marketing.

AI doesn’t just merely enhance creative strategy with data-driven insights, it’s reshaping what’s achievable, promising a deep return on investment far beyond content creation. And as the marketing function emerges as a primary domain for AI application (second only to supply chain innovations),2 the path to effective AI integration unfolds through a strategic framework underpinned by five foundational pillars, which we’ll cover later in this article. But first, let’s look at how AI can be effectively used in marketing and some of the challenges that come with its adoption.

Understanding AI: Marketing impact, applications and ethics

AI’s pervasive influence across the marketing funnel — from customer segmentation to personalized consumer experiences — signals a transformational shift. And while Gen AI is the right solution for many applications, it is not the right solution for every scenario. Here are some key marketing processes where AI excels:

  • Content generation: Automating the content creation process, generative AI enables the production of large volumes of high-quality content. This not only saves time and resources but also maintains brand voice consistency.
  • Insight generation: By summarizing complex data patterns, AI provides valuable insights that facilitate strategic decision-making, allowing marketers to understand and predict customer behavior better.
  • Personalization: Generative AI crafts customized content, suggestions and solutions, enriching the customer experience, elevating the personalization of marketing campaigns to new heights and enabling more nuanced segmentation that informs strategic content development.
  • Anomaly detection: Recognizing irregular patterns in data, AI can be utilized for use cases like fraud detection, cybersecurity and quality control to ensure the integrity and security of marketing operations.

The agility of AI to adapt to various objectives and tactics underscores its critical role in today’s marketing strategies. However, adopting generative AI requires a nuanced balance: on one hand, preserving the human touch that connects with audiences on a personal level; on the other, upholding brand security to prevent misuse and ensure content aligns with the company’s values. Both are essential for maintaining the overall integrity of the brand while leveraging the advantages AI offers.

Applying AI in marketing: A problem-driven approach

Implementing generative AI in marketing demands a problem-driven approach to ensure its effectiveness for specific tasks. This strategy leads to targeted deployment, optimizing AI’s benefits and aligning with organizational objectives. The process includes:

  • Problem identification: Begin by clearly defining the specific challenge or goal, such as aiming to boost email campaign engagement by 15%.
  • Lever assessment: Next, determine the key factors influencing the issue, considering generative AI’s strengths and limitations.
  • Solution structuring: Develop an AI strategy tailored to the identified levers, whether it’s a chatbot or analytics tool, ensuring it remains adaptable to market dynamics.
  • Implementation: Seamlessly integrate the AI solution into your marketing tech stack to foster collaboration between tech and marketing teams and initiate pilot tests to reduce risks.
  • Performance monitoring: Continuously track the AI solution’s effectiveness using predefined KPIs for real-time insights, ready to iterate and address new challenges as they arise.

Overcoming challenges: AI-driven success stories

From increasing privacy regulations to customer churn, operational and financial challenges persist in the rapidly evolving marketing arena. Companies have navigated these complexities by leveraging AI for creating immersive omnichannel experiences and virtual try-ons, respectively. Netflix's AI-driven recommendation system, accounting for 80% of viewer engagement, exemplifies the strategic use of first-party data to craft personalized content. Similarly, Kroger and Cadbury demonstrate AI’s potential to enhance customer feedback analysis and cost-effective content creation, illustrating practical successes in overcoming marketing challenges with AI solutions.

Embracing AI: 5 pillars of strategic innovation

To navigate AI's transformative potential effectively, organizations must adhere to a structured framework consisting of:

  1. Governance and alignment: Aligning AI initiatives with business goals to drive growth synergistically
  2. Data as the foundation: Leveraging high-quality, standardized customer data as the core of AI systems
  3. Cross-functional agility: Building adaptable, interdisciplinary teams to oversee scalable and responsive AI solutions
  4. Change management and risk mitigation: Proactively navigating AI adoption with strategies that address compliance, privacy and ethical concerns
  5. Measuring success: Continuously evaluating AI initiatives to ensure alignment with marketing KPIs and sustainable ROI

These pillars not only guide the strategic deployment of AI, but also emphasize its role as a complement to the marketer’s toolkit, enhancing creative instincts with analytical precision.

Looking into the future: AI’s growing role in digital marketing

To learn more, please watch an on-demand webinar where L.E.K.’s Chuck Reynolds, Gavin McGrath and Alexa Allen discuss this topic in greater detail.

For more information, please contact us.

L.E.K. Consulting is a registered trademark of L.E.K. Consulting LLC. All other products and brands mentioned in this document are properties of their respective owners. © 2024 L.E.K. Consulting LLC

1L.E.K. Consulting Digital Survey (2023) 
2L.E.K. Digital Survey

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