Here’s something I didn’t expect to be saying two years ago: the more my team uses AI, the more time we spend talking to people. Strange, right? Let me explain.
If you’d asked me ten years ago what AI would look like, I’d have pointed to Jarvis from Iron Man: a thoughtful assistant you could talk to naturally, explore ideas with and learn alongside. Science fiction promised me conversations with a machine. It never predicted that those conversations would give me back time for the human ones. Let me explain how that happened.
In my role as head of corporate marketing for an AI company, my days are split across strategy, planning, content strategy, social media, talking to analysts, media, influencers, and a dozen other conversations happening at once. Like most marketing leaders, I don’t get more hours in the day, just more work competing for them.
What I’ve come to appreciate is that the real work isn’t just about content or campaigns. It starts with research to understand our customers, markets, competitors, the impact of technology, and the conversations that shape our industry. Every decision we make is built on that foundation.
That’s where AI stopped feeling like a tool and started changing how I approach work. Looking back over the last two years, one of the biggest surprises has been this: the more my team and I use AI, the more time we spend talking to people. It’s counterintuitive, but it’s true. That change has reshaped the way my team and I work, and it plays out across three areas in particular.
Research: Context is the real advantage
One of the biggest misconceptions about AI is that it can find you the answer to everything. To me, AI is like a map. Incredibly useful, but a map has never walked the terrain. The real advantage today comes from understanding information, and that understanding is built through conversations with people: your customers, partners, product teams, customer-facing teams, developer and analyst communities. They live the experience. That’s the context AI can never create on its own. This is especially true as organizations across India increasingly look to combine AI capabilities with domain expertise to solve real business challenges.
For my teams, using AI for preliminary research is mandatory. But the real work begins after that. We spend the majority of our time gathering organizational context, examples, and lived experiences, then combine the two to complete the task at hand. The result is work that AI alone could never produce, and that reads very much like us while being completed in nearly one-third of the time compared to traditional approaches.
The more context we bring to AI, the better it becomes. Every customer conversation, analyst insight, and lesson learned teaches it a little more about our business, our customers, and how we think.
This is where the unexpected part comes in. Because we spend less time searching and synthesizing, we have more time to talk to customers, build relationships, and ask better questions. We invest the time we save right back into creating the very context that makes AI better. That loop, more than any single feature, is what has made our work more human.
Creativity: Challenging the first idea
The second shift has been in how we approach creativity. Our rule here is simple: AI’s job is to help us think beyond our first idea, and the creation stays with us. For marketing teams navigating increasingly competitive and fast-moving markets, this balance between AI assistance and human judgment has become more important than ever.
Let me give you an example. When we’re developing a blogpost or a campaign, we may start with a specific thought in mind. We’ll then ask AI to explore different narrative directions, challenge our initial thinking or suggest angles we may have overlooked. Quite often, the first idea isn’t the strongest one. AI helps us discover that before we’ve invested time building around it by presenting perspectives we may not have initially considered.
The same approach extends well beyond writing. Whether we’re shaping a campaign narrative or planning a launch, AI helps us test different approaches before committing to one. Sometimes it reinforces our thinking. More often, it forces us to rethink it.
That has changed the way we create. Rather than running with the instincts of one person, we let the strongest idea win. AI has expanded our creativity, making our thinking more open, our discussions more balanced and our ideas more resilient before they ever become reality. . In my experience, the best outcomes come when AI acts as a collaborator that challenges assumptions rather than replacing creative thinking.
Outcomes: Better, not just faster
The most obvious benefit of AI is speed. Research that once took days now takes hours. Drafts come together more quickly, and presentations require far less manual effort.
But speed is only part of the story. The bigger change has been in the quality of our thinking. Like every leader, we all bring our own experiences, instincts and biases into the decisions we make. AI challenges that judgment, and that’s exactly where its value lies. It pushes us to question assumptions we might have overlooked, and it does so before those assumptions harden into decisions.
The effect shows up in how we work together too. Ideas get debated and stress-tested earlier, so the strategies that survive are stronger, and we apply our judgment in a more informed, balanced and effective way. For me, that’s the real promise of AI—not simply helping us move faster, but helping us think better together.
Someone to think alongside
Living and working this way has taught me something I never expected. The biggest change wasn’t in how I researched, created or made decisions. It was in how I started thinking about AI itself.
The AI I work with today understands my writing style, adapts to our company’s voice and has learned the context I work within. Just as importantly, it knows when not to guess. If I’m unclear, it asks questions rather than making assumptions. Every now and then, it’ll challenge a weak argument or suggest a perspective I hadn’t considered. Those are often the moments that lead to the best work.
Somewhere along the way, AI started feeling less like another piece of software and more like a genuine thinking partner. Looking back, I think the real appeal of Jarvis was never the flying suit. It was having someone to think alongside, and today that kind of partnership isn’t reserved for superheroes. It’s available to all of us. That’s what AI Appreciation Day means to me: a new way of working where people and AI bring out the best in each other.
