Date: 22 Jul 2025

With over 30 years of experience in marketing and leadership roles, Milind Pathak has seen plenty of technological shifts. But nothing quite like AI. As Chief Marketing Officer at Proximus Global, he says that it won’t reinvent marketing but enhance it.

“At the heart of effective marketing lies the ability to leverage data intelligently” Milind says, “and AI takes this to the next level.” Between automating A/B testing and performance analysis, he believes AI is helping marketers make faster and more informed decisions along every step in the process.

But there’s nothing to be afraid of here. “You’re just replacing the old tool with a slightly better one. A tale as old as time,” he told us. AI may excel when it comes to processing data and surfacing patterns, but human marketers are the ones who bring context, empathy and creativity. “AI offers insights and optimises campaigns,” Milind explains, “but it’s still human intuition that makes those insights mean something.”

Milind’s advice to marketing teams beginning their AI journey is to stay grounded: “Start small. Treat AI as just another tool to complement your creative strategy.” He recommends beginning with projects where AI can simply handle the heavy data lifting, allowing teams to test the waters before diving in.

“AI might be the answer, but it’s better to start with the question first.”

For Milind, the real success will come from combining AI’s analytical power with the emotion and strategy only humans can provide.

With the cautious approach that Milind suggests, the real impact of AI won’t appear overnight but over time. Considering this patient mindset, we started by asking him how AI has affected his working life longer term.

How has AI changed the way you approach digital marketing over the past few years?

AI has emerged as an indispensable asset for digital marketers, especially at an enterprise scale. At the heart of effective marketing lies the ability to leverage data intelligently, and AI takes this to the next level. By using AI, marketers can make more informed decisions, deliver highly personalised content at scale, and optimise engagement.

While AI is just one tool in the marketer’s arsenal, its efficiency and scalability make it a game-changer, seamlessly replacing some of the tools that came before. For instance, predictive analytics and machine learning empower marketers to anticipate customer behaviour and tailor campaigns for maximum impact. These technologies also streamline processes like A/B testing, budget allocation, and performance analysis. By facilitating faster iteration and refinement of strategies, AI doesn’t necessarily uncover entirely new practices but enhances the speed, scale, and precision of existing ones.

Yet, even before AI entered the scene, ethical data collection and usage were already significant concerns. Now, AI elevates the stakes further, particularly for companies developing their own tools. Technologies like deep learning and natural language processing enable sophisticated customer interactions, but ensuring their accuracy and reliability requires significant effort. These advancements demand massive training data, constant refinement, and rigorous testing. Building a system that reliably understands and responds to user inquiries involves meticulous debugging and ongoing optimisation, underscoring the complexity of ethical AI implementation.

In your experience, how effective is AI at understanding and predicting customer behaviour compared to traditional methods?

AI has changed what’s possible for analysing customer behaviour, but again, it’s really about speed and scale rather than being better than human analysis and intuition. While marketers have always looked for patterns in data, AI can simply process vast amounts more in real-time, providing insights that traditional methods would take much longer to uncover. This real-time point is crucial. Because AI tools are ‘always on,’ they can act as the first layer of analysis, giving marketers instant insights to make smarter decisions.

Of course, on the scale at which we operate, it’s unrealistic to suggest our human marketers were actively analysing the data themselves. Before AI, we were mostly relying on more static, rule-based approaches and adjusted these based on results. While we still use this in many areas, machine learning will increasingly allow us to refine predictions based on new data, making forecasting far more dynamic. The same goes for personalisation – something marketers have done for years but can now deploy with far more precision. This is thanks to more dynamic audience segmentation, meaning we can look to tailor campaigns based on individual behaviour rather than broad demographic assumptions.

Agentic AI, which can autonomously make decisions and take actions, further amplifies these capabilities. It enables more sophisticated and adaptive marketing strategies, ensuring that campaigns are not only personalised but also responsive to real-time changes in customer behaviour.

While AI is a powerful tool, we are looking to use it to complement rather than replace skilled marketers. AI currently makes mistakes and cannot sense-check strategies or think outside the box the way humans do. The best campaigns will still come from tapping into human creativity, which can now be enhanced by AI-powered insights. Striking the right balance is key. AI should be used for its scale and efficiency, but it’s essential not to lose the essence by completely removing human nuance.

Personalisation has become a key marketing trend. How has AI helped you deliver more personalised experiences at scale?

AI is the perfect tool for personalisation. On an enterprise scale, personalisation isn’t personal at all: it’s about using data and algorithms to analyse behaviour and preferences to deliver a tailored experience. The result is more personal, but how we get there is very process-driven.

AI’s ability to sift through vast amounts of data in real time should enhance this, meaning we no longer have to rely on broad demographic segments. Instead, we can craft personal experiences based on preferences and patterns. This real-time insight helps us pick the right message, at the right time, and across the right channel.

Once again, AI provides a layer of efficiency and scale that wasn’t possible before, but it doesn’t replace human creativity and intuition. Our team will still craft the messages and tactics, but AI gives the insights to refine them and, crucially, can automate when, where, and how we deliver these messages to each individual.

I’m excited by the potential for AI to help us deliver these personalised experiences at scale by handling the heavy data-lifting and pattern recognition. But human marketers will be important to ensure that the final output is engaging, empathetic, and fits our brand’s voice. This balanced approach leverages the best of both worlds, making interactions more meaningful and effective.

How do you see the role of human marketers evolving alongside increasingly sophisticated AI systems?

Technology is always evolving and changing. But currently, I see AI as taking some of the operational toil away from marketers and simply allowing them to do their jobs more effectively by replacing tools they are already using with better ones.

AI can handle the heavy lifting of processing massive data sets to identify trends, predict customer behaviour, and power better experiences. Marketers are either doing that themselves, freeing them up to focus on strategy or storytelling, or they are using slightly less sophisticated tools, which means you’re just replacing the old tool with a slightly better one. A tale as old as time.

AI offers insights and optimises campaigns, but it’s still human intuition that ultimately makes those insights mean something. While machine learning can dissect behaviours and segment audiences with incredible accuracy, it can’t replicate the creativity and oversight that humans bring. Authenticity is also becoming ever more important in marketing (and comms more broadly), so while AI can help us be more efficient and accurate, it’s important to make sure messages still feel ‘real’.

Finally, as AI becomes more sophisticated, the need for human oversight won’t go away; it will become even more important. You can’t leave tech to verify its own insights, manage biases, and ensure ethical use of data.

Which AI trends or developments do you believe will have the biggest impact on digital marketing in the next 3-5 years?

Over the next three to five years, I expect AI to massively evolve. We may not even be looking at any ‘net new’ use cases, but three years of maturity could completely change the picture from where we are today.

Take hyper-personalisation. As machine learning becomes more refined, AI systems will process data in real time to deliver nuanced, individualised experiences. This will allow us to segment audiences more effectively and anticipate customer needs to craft offers and messages with higher conversion rates and better ROI.

Another one that will be interesting to watch develop is generative AI. Using AI to generate content is perhaps one of its most divisive use cases in the industry, not least for how it could impact jobs, but also just how effective it is. As always, AI can add efficiency and speed up the process, but it’s a balancing act. As generative AI continues to develop, however, the equation could change.

Finally, as these systems grow more powerful, ensuring ethical and transparent use of data will be crucial. I’d like to think the future of digital marketing will be about leveraging AI’s strengths in data and automation while preserving the creativity and trust that only human marketers can offer. Perhaps only time will tell.

If you could give one piece of advice to marketing teams just starting to explore AI, what would it be?

We are still in this process ourselves, but I would say to start small. Treat AI as just another (powerful) tool to complement your creative strategy, rather than a silver bullet. When looking at a new tool, you need to test it first and figure out how (and if) it works. Begin with a manageable pilot project. I’d recommend one where AI can handle the heavy data lifting. This could be processing customer interactions, uncovering trends, or delivering actionable insights in real-time.

This approach means you can test the waters without diving in headfirst. As your team gains more confidence in how AI works and you prove the business case, you can consider ingraining it in more of your day-to-day campaigns. Remember, AI excels in crunching vast amounts of data and identifying patterns, but (in my opinion at least) it’s humans that turn these insights into engaging, emotionally resonant campaigns. You could do it the other way around, and feed AI with insights to create campaigns – but personally, I feel this is the wrong way around, at least for now. Like with any experimentation, it’s crucial to target and measure them against some form of control. It’s also important to understand that AI isn’t always the right tool for the job. Don’t implement it just for the sake of it. Start with the challenge and assess your options. AI might be the answer, but it’s better to start with the question first.

Publication: TechFinitive: Milind Pathak, CMO at Proximus Global: “AI isn’t always the right tool for the job”