In just a few years, artificial intelligence has moved from being experimental to essential. It’s no longer some optional add-on, but is built into how teams operate, communicate, and deliver.
Chaitanya Anumakonda, Director, Biddable Media, GALE, India (Source: prhandout)
Whether it’s helping decisions happen faster, making backend systems more efficient, or creating more relevant customer journeys, AI has become part of everyday life. And this shift isn’t small. Marketing-related use of AI rose from 21% in 2022 to 74% in 2023, a clear sign that it’s now central to how businesses think about growth.
Where are we today with AI in MarTech?
But for all the momentum, something still isn’t quite right in how AI is being used in most organisations.
Imagine dining at a Michelin-starred restaurant, excited for a seven-course meal. Your hors d'oeuvre appears promptly in under five minutes. Then, an hour-long wait for the soup. The next course follows quickly, but then the main course and dessert arrive simultaneously. Clearly not a great experience for the diner. However, this mirrors the reality that many businesses encounter while using AI across different departments.
Even as AI becomes more prevalent in marketing, the creation of tools designed for isolated problems has inadvertently led to silos.
Campaigns are more targeted.
Sales forecasts are sharper.
Service workflows are smoother.
Each department optimises for its targets, without knowing or worrying about what’s happening elsewhere. And while individual teams are seeing improved efficiency, overall organisational efficacy and efficiency remain elusive. So, the whole is still less than the sum of its parts.
What’s missing then?
At many companies, the tools work, but not together, leading to a sort of tunnel vision.
This fragmented use of technology affects both efficacy and efficiency. And the irony? AI is supposed to solve exactly this kind of inefficiency.
Real efficiency gains come from more than just isolated insights; it requires a coordinated approach that integrates information from various tools to create a comprehensive, unified understanding. The kind where a slowdown in campaign performance instantly influences how leads are prioritised, what content goes out next, and when delivery needs to happen.
That level of intelligence doesn’t come from more tools. It comes from how systems are designed to listen, learn, and act together. And that’s the shift more and more companies are starting to make. They’re moving away from big stacks built on long feature lists, and toward leaner platforms focused on real outcomes. It’s no longer just about what AI can do. It’s about how it connects.
So, what’s the ideal way forward?
We’ve seen it in other spaces: when different technologies come together, they create simpler, smarter, and more powerful tools. The same is true for AI.
Companies should for opportunities that bring their existing tech stack and departments, or tools together as opposed to making each of them individually better. Look for opportunities to automate across department touchpoints in a holistic and data driven manner.
For MarTech, this will be a big step forward.
When operating as one coordinated engine driving the whole system forward, information moves faster, decisions get made in real time, and teams can respond to what’s happening, not just what their dashboard tells them. That kind of alignment doesn’t just improve efficiency. It enables the entire business to be agile and resilient.
In summary, AI should unify the value chain by democratizing across tools, processes, and technologies, eliminating silos and driving collective progress.
By continuing you agree to our Privacy Policy & Terms & Conditions
