Lenzing Group

Vincent Leung is the Global Head of Digital Brand Marketing for Lenzing Group's TENCEL brand. He spearheads digital marketing strategies for this sustainable fashion brand used by brands like Calvin Klein, Levi's and Mara Hoffman. Leung oversees TENCEL's global digital marketing,  including influencer collaborations, social media, campaigns,  SEO/SEM and content aligned with sustainable fashion and ESG goals. His initiatives drive Lenzing's digital transformation, revamping processes, implementing Al-driven solutions and optimizing ROI through advanced analytics. With over 15 years of experience, Leung is a seasoned marketing leader championing eco-conscious brands.

Recognizing Leung’s leadership in driving marketing innovation, this exclusive interview explores his insights on how companies need to swiftly adapt their marketing strategies, and MarTech stacks and upskill their teams to harness the potential of Al for content creation, personalization, audience targeting and driving revenue

AT A GLANCE ✔ Adapt or Fall Behind – Seamlessly integrate AI into their marketing strategies will lead the next wave of industry innovation, while others risk obsolescence. ✔  Human Intelligence Meets AI for Smarter Marketing – AI can optimize workflows, but human oversight is essential for accuracy, compliance, and brand integrity. A hybrid approach combining AI efficiency with human expertise is the key to success. ✔ The Next Frontier in Marketing KPIs – Traditional metrics are evolving—AI-driven predictive modeling will redefine success measurement and help brands anticipate trends rather than react to them. ✔ Ethical AI: A Regulatory Imperative – The EU AI Act and evolving global regulations are setting clear standards for responsible AI use in marketing. Companies must adopt strict governance frameworks to remain compliant and build consumer trust. ✔ Balancing Automation and Creativity – AI should amplify human creativity, not replace it. A carefully governed approach ensures intellectual property is protected while leveraging AI’s power for ideation and efficiency.

AI in Marketing: Using Technology with Purpose, Not Just Speed

Marketing has always been about understanding people—what they need, what they value, and how they connect with brands. AI isn’t changing that. Tools like ChatGPT and OpenAI’s SORA are making content creation, personalization and audience targeting faster and more precise. But speed without strategy is just noise.

I’ve seen companies rush to adopt AI, expecting it to be a silver bullet. The reality? AI is only as good as the strategy behind it. Without a clear purpose, it can lead to generic messaging, brand dilution, and a loss of authenticity. We always need to make sure AI enhances brand identity rather than replacing the human element that makes marketing resonate.

For me, the most effective use of AI is as an amplifier, not a substitute. It should make good content stronger, insights sharper and engagement more meaningful. The companies getting it right aren’t just adding AI into their workflows; they’re training teams to use it intentionally, integrating it into omnichannel strategies, and ensuring it aligns with their brand’s values.

AI is already shaping the next era of marketing, but how we use it will determine whether it builds trust or erodes it. Companies that take an intentional, brand-first approach will not just adapt to change but lead it.

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“AI can be a powerful enabler, but human judgment remains the driving force behind responsible, impactful, and authentic marketing strategies.”

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Human Intelligence Meets AI: The Key to Smarter, More Impactful Marketing

The integration of human touch is key to every aspect of MarTech.

AI-powered tools have accelerated automation, making campaign execution faster and more efficient. However, technology alone isn’t the answer—successful implementation requires a hybrid approach that blends AI-driven efficiency with human expertise.

While AI can optimize workflows, it still lacks the human touch. Advanced models can automate content creation, personalization, and chatbot interactions, but they are not infallible. AI-generated outputs must be carefully reviewed to ensure accuracy, compliance, and brand integrity. Marketing leaders must recognize AI’s limitations and maintain oversight to prevent misinformation or misalignment with brand values.

In today’s AI-driven landscape, the key is intelligent adoption—leveraging AI-powered solutions like ChatGPT and large language models while ensuring they seamlessly fit within existing social media management and internal systems. Strategic implementation of pre-built AI tools can still unlock significant efficiencies for companies without extensive proprietary AI resources.

But AI alone isn’t enough. While AI excels at keyword recommendations, trend analysis, and automation, it lacks human intuition and critical thinking—meaning human oversight remains essential. AI-generated content, from chatbot responses to audience engagement strategies, must be validated for accuracy, relevance, and brand alignment to maintain authenticity and trust.

The future of marketing belongs to those who strike the right balance. Companies that embrace AI while implementing rigorous human validation processes will maintain brand consistency and credibility. AI can be a powerful enabler, but human judgment remains the driving force behind responsible, impactful, and authentic marketing strategies.

AI-Driven Marketing Metrics: Shifting from Past Performance to Predictive Intelligence

The way we measure marketing success is being rewritten in real time. With AI-driven analytics, predictive modeling, and synthetic data expansion, we are moving toward a future where traditional KPIs alone are no longer enough. Yet, AI-powered marketing metrics are still in their infancy, and even industry leaders recognize that we are in a critical testing phase—one without definitive measurement algorithms.

AI’s true potential isn’t just in automation—it’s in foresight. While generative AI has already reshaped content creation, personalization, and campaign execution, its next frontier lies in predictive analytics and trend forecasting. To get there, AI must evolve beyond static insights and into real-time market intelligence capable of anticipating consumer behavior shifts.

Breakthroughs like Retrieval Augmented Generation (RAG) are accelerating this transformation. This cutting-edge approach is pushing large language models like ChatGPT to new levels of human-like interaction, enabling them to process real-time data, sustain multi-turn conversations, and generate insights beyond their original training set. These advancements are paving the way for AI-driven strategies that don’t just react to trends—they predict them.

The future of marketing metrics will be shaped by those who embrace AI not just as a tool, but as a strategic partner. As language models continue to evolve with techniques like RAG, we are inching closer to a world where AI-powered predictive analytics, synthetic data modeling, and dynamic marketing KPIs will drive decision-making.

Striking the Right Balance: Amplifying Creativity Without Replacing It

How we integrate AI without replacing human creativity is an art. As generative AI floods the market, its greatest value isn’t in automation alone but in its ability to enhance ideation, streamline workflows, and unlock new creative possibilities. The future of marketing will be shaped by those who use AI as a tool to amplify human ingenuity, not replace it.

The biggest challenge isn’t AI’s capabilities—it’s how we manage its risks. Generative AI models are built on human-created content, making copyright infringement a serious concern. Without the right safeguards, brands risk unintended IP violations, legal challenges, and loss of consumer trust.

Marketing leaders must rethink AI governance before AI reshapes the industry for them. A minimal and carefully governed approach is essential—leveraging AI for brainstorming, ideation, and content assistance while ensuring that every output is audited, compliant, and aligned with ethical standards.

The Ethics of AI in Marketing: Navigating Regulation, Compliance, and Trust

Ethical considerations are no longer optional—they are business-critical. As AI-generated content becomes more prevalent, regulations are rapidly evolving to ensure that innovation does not come at the cost of intellectual property rights, data privacy, and consumer trust. The EU AI Act, built on GDPR principles, is set to establish clear rules for generative AI models, particularly those repurposing copyrighted data.

Europe is leading the charge, but AI governance will soon be a global priority. The goal is not to stifle AI’s potential but to strike the right balance between innovation and risk mitigation. For marketing leaders, this means defining strict policies and governance frameworks to ensure AI-powered content creation remains compliant, ethical, and aligned with brand values.

A reckless approach to AI could lead to reputational damage, legal challenges, and a loss of consumer confidence. Industry players—especially creatives—must shift from unrestricted AI adoption to a carefully audited, assistive approach where AI enhances ideation rather than replaces human ingenuity.

Advice to Peers: Embrace AI or Get Left Behind

The present and future of marketing is here. Digital marketing leaders who fail to strategically integrate AI into their MarTech stack risk falling behind in an era where data-driven decision-making, automation, and personalization define competitive success.

The key isn’t reinventing the wheel—it’s leveraging what works. Instead of building proprietary AI models from scratch, marketing leaders should focus on adopting proven AI solutions and embedding them into existing platforms and workflows. By actively utilizing native AI functions within marketing tools, companies can enhance efficiency, scale content production, and optimize audience targeting without overcomplicating AI adoption.

The numbers speak for themselves. Accenture research shows that companies embracing next-gen AI—such as large language models and generative AI—are 2.6 times more likely to increase revenue by 10 percent or more. This isn’t just a technological shift; it’s a business imperative.

The gap between AI leaders and laggards is widening. Proactively integrating AI into strategy, execution, and measurement will define which companies emerge as industry front-runners in this decade of technological disruption. Those who act now will lead—those who hesitate will struggle to keep up.