The Hidden AI Skills You Didn’t Know You Had

Think AI expertise is all about coding and algorithms? Think again.

When I first dipped my toes into the world of artificial intelligence, I felt like an explorer venturing into uncharted territory. The algorithms, the data models, the technical jargon—it all seemed overwhelming. But then it hit me: the skills I’d honed over years in marketing and business were not just relevant—they were incredibly valuable in the AI landscape.

If you’ve ever structured a brand narrative, navigated an IPO, or analyzed a customer journey, you’re more AI-ready than you might think. Let me share how my journey revealed the surprising overlap between everyday marketing skills and the world of AI.

From Crafting Brand Narratives to Data Storytelling

In marketing, telling a compelling brand story is key to connecting with your audience. It’s about understanding your customers’ needs, desires, and pain points, and weaving that into a narrative that resonates. When I was tasked with rebranding MaibornWolffs’s and QAware’s identity, I delved deep into market research, customer feedback, and industry trends. Sifting through heaps of data, I had to identify patterns and insights to shape our new brand story.

This process mirrored what data scientists do when they interpret complex datasets to extract meaningful insights—a cornerstone of AI. By transforming raw data into narratives that inform strategy, we’re essentially engaging in data storytelling. Tools like Tableau and PowerBI make this possible by allowing us to visualize data in ways that highlight trends and patterns. If you’ve ever presented a data-driven marketing report, you’ve tapped into the power of data storytelling.

Navigating an IPO and Algorithmic Thinking

Steering a company through an IPO is no small feat. It requires strategic planning, meticulous forecasting, and a keen eye for risk assessment. During our IXOS Software’s IPO, I was immersed in analyzing financial models, predicting market responses, and crafting strategies to position us favorably. This experience honed my ability to think algorithmically—breaking down complex problems into smaller, manageable components and using logical steps to reach a solution.

It’s akin to how algorithms function in AI, processing input data through a series of steps to produce an output. Utilizing Excel’s advanced (AI) functions to model financial scenarios is a practical example. If you’ve built financial models or used forecasting tools, you’re already familiar with the foundational concepts of algorithmic thinking.

Analyzing Customer Journeys and Pattern Recognition

Understanding the customer journey is all about recognizing patterns in behavior and interactions. Whenever I launched a new product line, I spent countless hours mapping out customer touchpoints, analyzing engagement metrics, and identifying drop-off points in the sales funnel. This pattern recognition is directly related to machine learning, where algorithms learn from data to identify trends and make predictions.

By using platforms like Google Analytics to track user behavior or segmenting audiences for targeted marketing, we’re applying the same principles that underpin AI technologies. If you’ve ever adjusted a marketing strategy based on customer data, you’ve engaged in a form of machine learning.

Ethical Communication and Responsible AI

Clear and ethical communication has always been at the heart of good marketing. Crafting transparent privacy policies, being upfront about data usage, and building trust with customers are essential practices. In the realm of AI, these skills translate to developing and advocating for ethical AI practices.

Understanding frameworks like Google’s Responsible AI Practices can guide us in aligning AI initiatives with ethical standards. Ensuring that AI systems are transparent, fair, and respect user privacy is crucial. Your ability to communicate complex ideas simply and ethically is a significant asset in the development of responsible AI.

Bridging the Gap

The realization that my marketing skills were transferable to AI opened new avenues for innovation and growth. The bridge between marketing and AI is built on understanding people, interpreting data, strategic thinking, and ethical considerations—all areas where marketers excel.