The Human in the Machine: Consumer Centricity in an AI World

In today’s rapidly advancing AI landscape, customer centricity is no longer about simply keeping the customer at the center—it’s about leveraging cutting-edge technology to anticipate and meet their needs with unprecedented precision. As AI reshapes industries, businesses must radically redefine what it means to truly understand and serve consumers.

 Jeff Bezos, the founder and Executive Chairman of Amazon, famously places an empty chair in meetings to represent the customer, compelling his team to prioritize their perspective. This concept is foundational for consumer insight teams, whose mission is to capture the voice of the consumer. But what does it mean to be a consumer insight expert in a world where AI is rapidly becoming indispensable, promising a level of precision and personalization beyond anything we've seen before?

 AI and the Evolution of Consumer Centricity

 Two prevailing views dominate the conversation. Some believe we’re entering an era where machines will understand us better than we understand ourselves—a trend that’s been escalating for years through machine learning and algorithms. Others are more cautious, highlighting the flaws in newer AI models, such as large language models and generative AI—citing concerns over errors and biases.

These binary arguments miss the larger point: AI isn’t about achieving human-level intelligence; it’s about evolving into a distinct form of intelligence. As Yuval Harari aptly notes, "It’s like defining and evaluating planes through the metric of bird-level flight. AI isn’t progressing to human-level intelligence. It is evolving an alien type of intelligence." 

AI, unlike previous technologies, mirrors human behavior—efficient, yet unpredictable and biased. This is because AI is trained on human data, embedding our biases into its algorithms. However, this very trait allows AI to excel at understanding human decision-making and mastering creativity. This wave of technology goes beyond automating administrative tasks; it encroaches on the creative endeavors that have traditionally been the hallmark of human ingenuity.

As AI takes on more human-like tasks, technology is no longer just about automation—humans must now contribute strategic and creative input. In marketing, we are already witnessing how AI is revolutionizing creative and product development. And with AI integrated into the consumer insights toolkit, the ability to analyze trends and patterns will be exponentially enhanced.

Rather than viewing humans and machines as adversaries, we must embrace their collaboration as essential. If AI contains biases, it is our job to course correct. As Ethan Mollick argues in Co-Intelligence: Living and Working with AI, we must ensure that AI evolves in a way that aligns with human ethics and values.

The partnership between AI and humans must be iterative, with consumer insight teams leading the charge in responsible design, establishing guardrails to prevent unethical or irresponsible outcomes. In this new dynamic, AI becomes an invaluable team member, augmenting our abilities rather than replacing them.

The Role of Connected Data in AI-Driven Insights

Despite the clear potential, many businesses remain unprepared for this new wave of AI integration. Before even considering how to collaborate with machines, businesses must first train AI on their own datasets.

A study by the American Marketing Association (AMA) and Zappi reveals that 43% of businesses are still mired in disconnected and fragmented data. As businesses grapple with the crucial question, 'What data should we train our AI systems on to remain at the cutting edge of innovation?' it becomes evident that many organizations need to first get their data houses in order.

The AMA and Zappi have segmented the market into three types of organizations:

• Level one (8% of organizations) is characterized by disconnected data, where insights are reactive and projects are ad hoc. 

• Level two (35% of organizations) is defined by fragmented data, where insights are more proactive but still managed by separate systems and processes. 

• Finally, level three (56% of organizations) demonstrates a clear agenda for connected data, where insights are strategic, and data is systematically organized.

While the trend toward systematized insights is gaining momentum, it is far from universal. However, one thing is clear: companies that master this integration will secure a significant competitive advantage. Gartner even forecasts that “by 2025, AI-driven insights will be the primary driver of competitive advantage for leading consumer brands.” Companies that effectively connect their data will outpace competitors, leveraging AI as a powerful tool for strategic leadership and innovation.

Embracing AI as a Strategic Partner

While disconnected data is wasted potential, truly connected data integrates insights across departments and geographies, transforming tools into systems. CMOs who strategically leverage AI will unlock insights that transcend demographics and business units, paving the way for true consumer centricity and category leadership.

The time to act is now—companies that hesitate risk falling into irrelevance. AI isn’t just an enhancement; it’s the cornerstone of future consumer-centric innovation. Embracing AI as an integral part of our capabilities will unlock unprecedented opportunities for those daring enough to lead. The future is already unfolding, and it won’t wait. Will your business take the lead, or be overtaken by those who do?