In a world where everyone is exploring GenAI, few truly understand how to drive business value from it. Gyan Gupta, Chief AI Officer at AI in Action, cuts through the noise with hard-earned insights on what it really takes to move from AI experimentation to AI enablement. From real-world use cases and strategic frameworks to human-AI collaboration and the next MarTech revolution, Gyan unpacks the layers of AI readiness and what businesses often miss in the rush to adopt. Here’s our conversation.

Everyone is jumping on the GenAI bandwagon but few know the real tricks. What’s your take on the gap in understanding?
Absolutely—and I see this every day. Most people think GenAI is just ChatGPT or Perplexity. But it goes far beyond that.
The real value of GenAI isn’t about asking better prompts—it’s about:

• Designing smart workflows

• Using agents to automate tasks end-to-end

• Integrating AI into CRMs, ERPs, CMSs, and your existing tools
  That’s where business impact happens—not just writing faster emails.
  But here’s the catch: most people don’t know where to begin.
  That’s why we built AIRSA—a proprietary AI Readiness & Strategy Assessment that shows you:

• Where you stand

• What gaps to fix

• How much impact AI can bring in rupee-terms
  It’s your map from AI buzz to business results. We’ve created it for both organizations and individuals, because whether you're a business owner, founder, C-suite, or a working professional, your AI journey starts with clarity.

Can AI replicate human empathy or intuition in decision-making?
AI can process complexity, but it doesn’t feel. It won’t know that a client is upset or that a campaign feels emotionally off-brand. That’s still very human.
What AI can do is augment our intuition with data—spot patterns, flag risks, and recommend what’s working.
But for emotional nuance, relationship management, and empathy? That’s where humans shine.
It’s not human versus AI—it’s about the human and AI partnership. I often say: Let AI be your co-pilot, but you still hold the steering wheel.

Where is AI being overhyped versus where is it truly making an impact?
Overhyped? Definitely in areas where companies try to make AI replace strategy or leadership judgment—like end-to-end creative campaigns or boardroom decision-making.
Real impact? When the objectives are clearly defined, and you get the organization ready for it.
We’ve seen measurable gains in:

• Better lead conversion through smart scoring

• LTV growth via predictive retention

• Increase in average order value

• Higher customer stickiness with personalized nudges

• Customer engagement and personalization
  One brand we worked with improved funnel efficiency by 35 percent—just by moving from manual targeting to AI-led segmentation and automated follow-ups. That’s the kind of ROI-driven AI businesses need to focus on—not vanity experiments.

What about ethics—bias, privacy, and responsible use?
This is a real concern—and it’s why AI readiness isn’t just about tools. It’s about trust.
In our DPPR framework, People and Roles come before tech. You need to define:

• Who is using the AI

• For what purpose

• With what boundaries
  Ethical use requires:

• Bias checks

• Human-in-the-loop reviews

• Data privacy protocols

• Right guardrails
  I believe transparency is the new currency in AI. If people don’t understand how AI works—or feel it’s making invisible decisions—you’ll lose trust, no matter how accurate the model is.

AI gives data insights, but many struggle to act on them. How do we make insights more usable?
Exactly. AI can give you a 20-page dashboard, but you really need a one-line decision like:
“Pause this campaign.”
“Double down on these leads.”
“Shift spend to Instagram.”
When you train the model on your business trends and nuances, with a feedback process to help it learn what works and what doesn’t, that’s when it becomes valuable.
It’s a continuous process to make it learn and train, and it will be able to give you valuable insights.
What we focus on in AIRSA is closing that last mile of insight. That means:

• Training AI to think like your business

• Feeding it the right signals

• Teaching it what success looks like

• Defining how insight leads to action
  The companies winning with AI are the ones who ask:
  “What will we do with this insight—today?”
  Not just, “What does this data say?”

Why aren’t more companies fully leveraging AI in customer experience and content?
Because they try to plug AI as a tool and think it is another tech upgrade, whereas this is a mindset shift. Most of them don’t know:

• Where to start

• What to measure

• Or how to scale
  The companies seeing results are those who assess:

• Where they are

• What their objective is

• What they want to achieve
  And who design their workflows with AI at the core
  That’s the exact gap AIRSA fills.
  We help businesses define the right use cases, estimate the potential impact, and build a phased AI roadmap.
  We’ve seen ad production time drop by 60 percent, campaigns personalized in real time, and team bandwidth freed up dramatically—but only when AI is integrated with intention.

Marketers are hesitant to let AI make high-stakes decisions. What builds trust?
Trust comes from two things: transparency and track record.
We guide teams to start small. Define the role of AI. AI can do one of the six roles:

• AI as an Advisor: Providing insights and recommendations

• AI as an Assistant: Helping humans perform tasks more efficiently

• AI as a Co-Creator: Working collaboratively on tasks

• AI as an Executor: Performing tasks with minimal human input

• AI as a Decision-Maker: Making decisions independently

• AI as a Self-Learner: Learning from tasks to improve over time
  You have to start small, define the role, and then build it from there.
  When teams see results firsthand, trust follows. That’s our model:
  Start with one person → one department → the entire organization.
  You don’t have to believe the hype. Just experience it for yourself.

What’s the next big AI breakthrough in MarTech?
The next wave is AI-orchestrated marketing.
We’ll see:

• Decision engines that adjust budgets in real time

• Customer advocacy models that detect promoters before surveys go out

• Data fusion from CRM, web, social, and behavioral signals to personalize campaigns on the fly
  It’s like having a full-stack growth team running 24/7—an analyst, media planner, copywriter, and performance manager—all powered by AI. The role of AI changes from being Co-Creator to Decision-Maker and Self-Learner.
  But here’s the thing: this only works if you’re ready.
  The right systems, data, and people must be in place. That’s why frameworks like AIRSA are not just useful—they’re essential.