My Strange Interview Experience
When academia does not see eye to eye with industry
Last week, I was all set for my interview, prepped to discuss my passion for research, and ready to share my ideas. The interviewing panel showed up 35 minutes late, no apologies, no explanations. Yes, that was my experience when I interviewed for one of the leading IIMs (Indian Institute of Management) for the PhD in Marketing Management (Practice Track) program. To say it threw me off would be an understatement. While I remained composed and proceeded with the conversation, the initial impression left me questioning the level of respect for candidates’ time. It was a disconcerting start to what should have been a constructive and engaging discussion, and it set the tone for what turned out to be a rather strange conversation!
The awkwardness didn’t end there. Instead of introductions or setting the context for the discussion, one of the panelists launched straight into questioning my research motive: “Why do you want to pursue research *now*?” The emphasis on “now” left me puzzled. Why does the timing of my decision matter so much? Does age suddenly become a barrier to pursuing research? I’ve always believed that passion and curiosity should drive research, not some arbitrary timeline.
This experience got me thinking about the disconnect between academia and industry, a gap I’ve noticed throughout my career, which I vociferously stated in the interview. Academic research often feels detached from real-world application. As someone who’s worked in the industry for 25+ years, it frustrates me to see how little value is placed on practical insights. This frustration is, ironically, one of the reasons I want to contribute to academia in the first place! I want to bring a practitioner’s perspective to research and contribute in ways that feel relevant and impactful to both the industry and academic worlds of today.
Bringing AI and Practical Insights to Academic Research
My proposed PhD research topic is about the role of AI in Product Marketing and how AI-native Integrated Development Environments (IDEs) can be used to build enterprise-grade, commercially viable applications. It’s an area I’m passionate about because I believe AI has the potential to reimagine, specifically in the product communication and storytelling domain of product marketing. Product communication and storytelling shape how customers perceive, remember, and connect with brands, and yet these areas are often ignored in both academic research and AI innovation. AI could push product communication and storytelling forward, but isn’t yet being fully explored and here are some approaches that come to my mind:
- Content Personalization at Scale
AI can analyze audience data to tailor product stories for different segments. Imagine product launches where every customer sees a version of the story that resonates with their values and needs. - Narrative Testing and Optimization
AI could help marketers A/B test not just headlines, but entire story arcs or product narratives. - Visual and Multimodal Storytelling
Generative AI can create images, videos, and interactive experiences that bring product stories to life. - Cultural and Contextual Adaptation
AI could help adapt stories for different cultures and contexts, ensuring relevance without losing authenticity. - Measuring Story Impact
AI can analyze sentiment, recall, and behavioral data to measure the effectiveness of storytelling, not just clicks or shares, but actual changes in perception or purchase intent.
As a marketer, I have struggled to communicate a product’s value in a way that sticks, and I am sure I’m not alone. What if I had an AI tool that could suggest story structures, test emotional impact, or even generate new metaphors based on the audience’s language?
B2B or Enterprise marketing faces even more neglect when it comes to product communication and storytelling. Most academic research still focus on B2C, where emotional stories and flashy campaigns are common. In B2B, the assumption is that buyers are rational, so storytelling gets sidelined. But in reality, B2B decisions are complex, high-stakes, and often personal. Relationships, trust, and clarity matter even more. A handful of researchers address this reality. It is because B2B sales cycles are longer and harder to study, and B2B marketers themselves haven’t pushed for better tools!
Open AI’s recently published paper on brings up an interesting use case on how AI models are improving product performance.
But when I explained this research theme to the panel, I couldn’t tell if they were genuinely interested or if they just didn’t get it. I spent five minutes breaking down how AI-native products have transformed the product marketing domain over the last couple of months. Still, I felt like my enthusiasm wasn’t reciprocated. ☺
The Widening Skills Gap
This isn’t just about my interview, it’s a broader issue. Academic research grants seem to reward theoretical novelty, and perhaps not real-world application. I don’t know if this is because decision-makers behind these grants have little experience outside academia themselves. When digital marketing took off, academic research eventually followed, but most of it focused on campaign effectiveness or ad technology. AI in marketing still seems to be narrowly scoped or understood as Google or Meta advertising management. There’s still so little research being done on how AI could reshape the fundamentals of product marketing.
One one hand, academic institutions prioritize publishing papers over solving real-world problems. On the other hand, the industry is laser-focused on customer outcomes. This divide is frustrating because both sides have so much to gain from working together.
Bridging the Gap with AI
Could AI help bridge this gap? I think so. Imagine if AI could track outcomes that matter to both academia and industry, like measuring the real-world impact of research while ensuring it meets rigorous academic standards. This kind of collaboration could lead to innovation that benefits everyone.
But for this to work, academia needs to shake things up a bit. They need to place greater emphasis on integrating hands-on industry experience into their programs, particularly at the graduate and postgraduate levels. Traditional academic pathways often prioritize theoretical knowledge over practical expertise, leaving students underprepared for the demands of industry today. By designing career-focused curricula that balance theory with real-world application, institutions can better equip students to bridge the divide between research and practice.
This shift is especially critical in management and other interdisciplinary fields where the gap between academia and industry is most pronounced. Collaborative programs, internships, and partnerships with companies can provide students with exposure to industry challenges while also offering businesses access to fresh academic insights. Such initiatives would not only enhance employability but also foster a culture of mutual learning and innovation.
Ultimately, achieving this balance requires a concerted effort from both academia and industry. Universities must adapt their priorities to value practical impact alongside academic rigor, while industries should actively engage with academic institutions to co-create solutions. By leveraging AI as a catalyst for collaboration and aligning educational frameworks with real-world demands, we can unlock a future where research drives meaningful progress across sectors.
The integration of AI into this equation is not a distant possibility — it is an opportunity that is already within reach. If embraced thoughtfully, it has the potential to transform the way academia and industry interact, ensuring that innovation is not only cutting-edge but also deeply relevant to the challenges facing our world today.
Reflecting on the Experience
Reflecting on this experience, I’ve realized that sharing your passion is always worthwhile, even if it doesn’t immediately spark visible excitement in others. Sometimes, planting the seed of an idea is just as important as seeing it bloom right away. And who knows? Perhaps my words will inspire someone on that panel to explore this research topic further down the line.
