When AI agents rewrite the rules of brand leadership

In most organisations, marketing and customer experience once ran on parallel tracks.

One built desire. The other built loyalty. That separation no longer exists.

AI agents are collapsing the gap between awareness and retention, between acquisition and advocacy. And as they do, the roles of CMOs and CXOs are being rewritten in real time.

It is no longer about adding AI to an existing playbook. It is about leading in a world where the playbook itself is generated, adjusted, and executed by intelligent systems that never sleep.

Across industries, brands are changing. Take Hindustan Unilever Limited (HUL), for example. It is embedding AI into decades-old operations across every layer of the customer journey.

In contrast, brands like Zepto are born AI-first, designing their go-to-market strategies, support systems, and intelligence layers around real-time consumer feedback. Whether legacy or challenger, all firms are adapting to a new reality: brand leadership today means orchestrating systems, not just strategies.

So what does modern leadership look like in this AI-led landscape?

The evolution of leadership

The CMO who stops at campaign launches is already behind. The CXO who only worries about NPS is too.

AI agents don’t acknowledge silos. They operate end-to-end. From discovery to retention, they adjust the customer journey in real time. To keep up, leadership must evolve.

Today, CMOs are leading AI enablement pods. They are focusing on cross-functional team training and monitoring AI agents across the funnel. CXOs are hiring Experience Prompt Engineers who fine-tune how AI interprets user behaviour and responds contextually.

Leadership in this environment requires a new blend. It includes data fluency, AI tooling literacy, and ethical oversight. These elements need to be embedded into every decision, not bolted on as an afterthought.

And these shifts aren’t theoretical. They are already happening at scale.

Consumer engagement in an AI-first era

The AI evolution is not a distant prospect—it is unfolding now.

Legacy brand HUL is reimagining the way it engages with customers. Through a mix of AI, NLP and martech, it is delivering personalised experiences across categories.

From AI-enabled skin and hair analysers to virtual try-ons and AR-guided tutorials, its beauty brands are creating experiences that blend convenience with personalisation. With over five million consumer trials and conversion rates exceeding 2.5%, these tools are turning technology into tangible outcomes.

On the other hand, AI-first challengers like Zepto are redefining brand intelligence altogether. Its Zepto Atom suite introduces Consumer Personas—AI-generated, data-rich profiles that allow marketers to run interactive sessions with virtual customers, test messaging, analyse drop-offs, and deploy precision campaigns in real time.

As Zepto’s leadership explains, this toolkit compresses what used to be a multi-week, multi-agency insight loop into minutes, powered by first-party behavioural data.

Whether it’s lead qualification, post-purchase engagement, or creative optimisation, AI agents are no longer simply assisting humans. They are co-owning the journey. And as brands adapt, their partners must adapt too.

Agencies as AI orchestrators

The role of the agency is shifting from production to orchestration.

When AI agents can generate, test, and deploy creative in real time, the traditional creative process is disrupted. But this does not mark the end of creativity—it marks its reallocation.

The smartest agencies are now helping brands decide where human creativity brings nuance and where AI’s speed and scale deliver value. They are building proprietary workflows, ensuring consistency of brand voice across millions of touchpoints, and guiding clients on layering human insights into machine-driven experiences.

This is not about fewer ideas. It is about faster iteration, tighter feedback loops, and always-on brand storytelling.

But in the middle of this acceleration, clarity matters—especially at the intersection of human and machine.

Mapping the human–AI handoff

AI handles high-volume, low-complexity tasks with ease: answering FAQs at 2 a.m., adjusting discounts mid-conversation, or identifying frustration before it is voiced. Yet edge cases still belong to humans. These include sensitive complaints, crisis moments, irregular requests, or situations that demand emotional nuance.

The most effective organisations map this handoff carefully. They identify where AI prepares the human, where AI stays in the loop without leading, and where human contact is non-negotiable.

This doesn’t slow things down. It ensures that speed and empathy coexist.

However, with this responsibility comes an equally important focus: ethics.

Ethics is now a performance metric

Bias. Hallucinations. Consent.

These are no longer footnotes in AI implementation plans. They are front-page leadership issues. Driving conversions with a biased model, or prioritising efficiency over transparency, can erode trust and weaken brand equity.

Leaders are increasingly aligning with global standards such as DPDP and CCPA to ensure that AI systems protect user privacy while delivering value. But principles alone aren’t enough—they must be operationalised. That means mitigating bias for fair outcomes, driving sustainable business growth, and ensuring explainable AI that supports customer trust.

Trust isn’t just a brand value anymore. It is infrastructure.

And this is where AI doesn’t simply fit into the funnel—it begins to own it.

AI agents own the funnel

When designed well, AI agents don’t just optimise individual funnel stages. They connect them.

Go-to-market AI integrates CRM, ad platforms, website analytics, and customer success tools. It maps how each touchpoint relates to revenue outcomes and tracks the complete customer journey.

With unified data, it can also identify patterns that individual tools miss. Why do some leads convert faster? Which touchpoints influence deal size? What signals predict churn?

According to the report, “companies that dedicate over 50 per cent of their GTM tech stack to AI are dramatically outperforming their peers.” This is not just automation. It is a rethinking of go-to-market itself, where every interaction becomes both insight and action.

Naturally, these changes are reshaping organisations from the inside out.

Organisational shifts and emerging roles

As AI takes on more responsibility across marketing and CX, organisations are rewriting their charts.

In recent months, I’ve seen new hybrid roles emerge. Agent Orchestrators are tasked with managing multi-agent systems across touchpoints. CX Prompt Engineers shape the nuance, tone, and timing of AI responses.

These roles demand skills that are part creative, part technical, and part strategic. Traditional career paths rarely produce them, which is why forward-looking companies are focusing on retraining rather than recruitment.

But even amid such transformation, one constant remains: trust.

AI brings speed, scale, and intelligence. But these are now baseline expectations. The true differentiator is confidence.

As I often say, “If customers walk away from an interaction feeling more understood, more in control, and more reassured, then the tech did its job. If not, the AI becomes just more noise.”

In the age of AI, leadership isn’t about keeping up with machines. It is about ensuring that machines keep up with the brand.

- Apurv Agrawal, co-founder and CEO, SquadStack.ai