Are You an AI Marketing Leader, Learner or Laggard?

The artificial intelligence revolution in marketing isn't coming - it's already here. According to new international research from Infosys (CMO Radar Report 2024), 96% of marketing leaders have deployed AI in at least one marketing activity, and nearly three-quarters use AI across all major marketing functions. Yet despite this widespread adoption, there's a stark divide between those truly succeeding with AI and those falling behind.

The AI Marketing Divide

The Infosys report reveals that marketing leaders generally fall into three distinct categories when it comes to AI implementation:

Leaders (13%): These AI-fluent CMOs consistently generate business value from AI across multiple marketing activities. They make data-driven decisions using predictive AI to anticipate customer needs, personalize campaigns, and boost marketing performance.
Learners (60%): The majority of marketing leaders are still developing their AI capabilities. While they've had some successes, they haven't yet mastered generating consistent value from their AI investments.
Laggards (27%): This group struggles to create meaningful business value from their AI implementations, often due to insufficient planning and framework development.

Let’s dive into these categories and explore the strengths and areas for improvement within each group.

Leaders: CMOs Leveraging AI as a Strategic Asset (13%)

Leaders, representing 13% of CMOs, have managed to integrate AI deeply into their marketing operations. These CMOs don’t merely adopt AI tools; they implement comprehensive strategies that yield measurable business value across five to seven core marketing activities. This group has proven that AI can deliver significant benefits in areas like content creation, customer segmentation, and campaign personalization, enhancing both customer experience and operational efficiency.

What sets Leaders apart is their investment in AI education and upskilling within their teams. They recognize that a knowledgeable team is better equipped to maximize AI’s capabilities. As such, Leaders are committed to ongoing training that enables their teams to stay updated on the latest AI advancements and understand the underlying concepts, from machine learning and natural language processing to predictive analytics. This emphasis on continuous learning and training helps their teams stay agile and responsive to changes in technology and market demands.

Another hallmark of Leaders is the alignment of AI initiatives with business objectives. These CMOs ensure that every AI-driven project supports the broader goals of the organization. Whether it’s improving customer satisfaction, optimizing campaigns, or reducing costs, Leaders are intentional about embedding AI in a way that supports measurable success. This alignment means that their AI deployments are not isolated projects but integrated components of a cohesive marketing strategy, amplifying their impact across the organization.

Finally, Leaders establish strong governance structures around AI. They prioritize data quality, risk management, and ethical considerations, ensuring that AI applications comply with regulations and meet organizational standards. This governance framework helps Leaders sustain and scale their AI efforts effectively, fostering an environment where AI can thrive as a reliable, trustworthy, and transformative tool.

Key Takeaways for Aspiring Leaders:

Invest in ongoing AI education and upskilling to foster team confidence and competence (see our AI Marketing course to help with that).
Align AI initiatives with business goals to ensure that each project has a strategic impact.
Establish governance frameworks that prioritize data integrity, risk management, and ethical standards.

Learners: Gaining Momentum but Needing Strategic Focus (60%)

The Learners category, which encompasses 60% of CMOs, represents organizations that are making strides in AI but have yet to reach their full potential. Learners typically see value in using AI in two to four areas within their marketing functions, such as automation, basic customer segmentation, and analytics. While they are seeing some positive outcomes, there remains a substantial gap between these outcomes and the broader impact that a more mature AI strategy could deliver.

A primary challenge for Learners is the lack of fully aligned AI strategies. Many of these organizations adopt AI in a piecemeal fashion, implementing tools and systems in response to specific needs without a cohesive, overarching plan. This approach often results in isolated successes but limits the broader integration needed to make AI a fundamental part of the marketing strategy. To unlock the full potential of AI, Learners must transition from viewing AI as a tactical tool to recognizing it as a strategic asset that can drive holistic marketing outcomes.

Another area for improvement within the Learner category is organizational buy-in. Successful AI implementation requires more than technology; it necessitates cultural change and support from top management. CMOs in the Learner category often find that their teams have not fully embraced AI, either due to a lack of understanding or resistance to change. As a result, even effective AI tools can remain underutilized. To bridge this gap, Learners need to prioritize change management, building an internal narrative that communicates AI’s role in achieving both personal and organizational growth.

Finally, training and skill development are crucial for Learners to progress toward becoming AI Leaders. AI-driven marketing requires a unique blend of skills, including data literacy, analytical thinking, and creativity. Without a structured approach to training, Learner organizations risk falling behind as AI capabilities continue to advance. By implementing comprehensive training programs, these organizations can help their teams develop the skills needed to harness AI effectively and grow in confidence.

Key Takeaways for Learners Aspiring to Lead:

Create a unified AI strategy that aligns with overarching business goals and promotes seamless integration across functions.
Focus on securing organizational buy-in by highlighting AI’s benefits and fostering a culture of openness to change.
Prioritize skill development through targeted training programs that enhance data literacy, analytical skills, and creative problem-solving. (again, see our AI Marketing course to help with that)

Laggards: Getting Started with AI Integration (27%)

The remaining 27% of CMOs fall into the Laggards category, where AI deployment is either minimal or sporadic. Unlike Leaders and Learners, Laggards lack a clear strategy for AI and often implement tools on an ad hoc basis without long-term planning or defined objectives. This lack of direction hampers their ability to derive meaningful business value from AI and leaves them vulnerable to competitors who are leveraging AI more effectively.

One of the primary obstacles for Laggards is the absence of formal AI strategies. In many cases, these organizations have yet to identify where and how AI can support their business goals. Without a roadmap for AI deployment, these CMOs struggle to see consistent results, leading to an environment where AI is perceived as a costly experiment rather than a valuable asset. To break free from this cycle, Laggards must develop a comprehensive AI strategy that identifies specific areas where AI can drive value and aligns these initiatives with broader marketing and business objectives.

Another barrier for Laggards is the lack of training and development for AI skills. Effective AI usage requires foundational knowledge of data analytics, machine learning, and digital strategy. However, teams in Laggard organizations often lack these skills, limiting their ability to use AI tools effectively. Establishing training programs is essential for Laggards to build the skills and confidence necessary to transition into the Learner category and eventually toward leadership. (once more, see our AI Marketing course to help with that).

Laggards also face challenges with AI integration into workflows. When AI tools are added without being embedded into existing processes, they tend to become siloed and fail to provide consistent value. Successful integration requires a systematic approach that rethinks workflows to accommodate AI insights, creating a seamless connection between technology and everyday operations. By focusing on integration, Laggards can lay the foundation for a more agile, data-driven marketing organization.

Key Takeaways for Laggards Seeking to Advance:

Develop a formal AI strategy that aligns with business goals and provides a clear roadmap for implementation.
Invest in foundational training programs to build core AI skills within the team.
Focus on embedding AI into workflows to create seamless integration and drive consistent value.

Why Training Matters More Than Technology

While the temptation is strong to focus on acquiring the latest AI tools and platforms, the research makes it clear that technology alone isn't enough. The difference between Leaders and Laggards often comes down to how well they've prepared their teams to work with AI.

Consider this striking statistic: almost half (48%) of AI deployments struggle to deliver business value. This gap isn't primarily about the technology itself - it's about how well organizations have equipped their teams to leverage it effectively.

The Skills Gap Challenge

Marketing teams today face a widening skills gap as technology evolves faster than training programs can keep pace. Even basic concepts like machine learning, predictive analytics, and natural language processing - fundamental to modern AI marketing tools - remain mysterious to many marketing professionals.

This knowledge gap leads to several problems:

Underutilization of expensive AI tools
Misapplication of AI capabilities
Missed opportunities for optimization and personalization
Reduced ROI on marketing technology investments

What Sets AI Marketing Leaders Apart

The research identifies several key factors that distinguish AI marketing Leaders from the rest:

1. Process Integration

Leaders ensure AI solutions are deeply embedded in their business processes. Their teams can:

Access real-time insights from data
Immediately adjust tactics based on AI recommendations
Work within established governance frameworks
Track progress against clear KPIs

2. Strategic Alignment

Top performers align their AI initiatives with broader business and marketing goals. They:

Maintain dynamic AI strategies that evolve with business needs
Prioritize AI use cases based on value and feasibility
Ensure active leadership involvement in AI initiatives
Create clear roadmaps for AI implementation

3. Risk Management

Leaders take a proactive approach to AI risk management by:

Embedding risk assessment into early stages of AI implementation
Establishing clear ethics protocols
Creating governance mechanisms for AI oversight
Building customer confidence through responsible AI use

4. Technology Infrastructure

Successful organizations ensure their MarTech stack is optimized for AI by:

Implementing cloud-native, scalable solutions
Maintaining robust customer data platforms
Supporting a wide range of AI use cases
Enabling seamless integration of new AI tools

Building an AI-Fluent Marketing Team

To move from Laggard to Leader status, organizations need to focus on developing their teams' AI capabilities. Here's how:

Create Comprehensive Training Programs

Focus on Fundamentals: Ensure teams understand basic AI concepts and capabilities
Develop Practical Skills: Provide hands-on experience with AI tools
Encourage Experimentation: Create safe spaces for teams to test and learn
Measure Progress: Track skill development and implementation success

Foster a Culture of Continuous Learning

Make learning part of daily work routines
Reward innovation and experimentation
Share successes and lessons learned across teams
Provide regular opportunities for skill updates

Align Training with Business Goals

Connect learning objectives to specific business outcomes
Demonstrate ROI of training investments
Track improvements in AI implementation success
Measure impact on marketing performance

The Path Forward

The research shows that AI's role in marketing will only grow stronger. Already, marketing leaders report that AI handles:

59% of campaign management
57% of content creation
57% of personalization efforts

These numbers are expected to increase, with companies projecting double-digit percentage point improvements in productivity (15%), cost savings (13%), and speed to market (11%) over the next 18 months.

Conclusion

The divide between AI Marketing Leaders and Laggards isn't primarily about technology - it's about people. While having the right tools is important, success with AI marketing ultimately depends on having well-trained teams who understand how to leverage these tools effectively.

For organizations looking to move up the AI marketing ladder, the path forward is clear: invest in your people. Create comprehensive training programs, foster a culture of continuous learning, and ensure your teams have the skills they need to make the most of AI technologies.

As marketing continues its AI transformation, the organizations that prioritize building AI-fluent teams will be the ones that thrive. The question isn't whether to invest in AI marketing capabilities - it's how quickly you can develop the human skills needed to unlock AI's full potential.

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