The same logic applies outside the company. A brand agent must not only reply intelligently. It must be able to retrieve data, trigger a campaign, update a journey, escalate an issue, and maintain a coherent experience across the entire lifecycle.
Build, Buy, or Experiment?

The AI world is exciting, but it is also disorienting. Every week there is a new model, agent, feature, or tool claiming that a complex business problem can be solved in two hours.

Beerud’s advice was balanced. Experiment rapidly, but do not confuse a prototype with a production system. Creating the first version is often easy. Maintaining it, improving it, integrating it, measuring it, and ensuring it does not damage the brand is the real work.

A complete conversational AI platform may need:

• Campaign management for outbound communication

• Customer journeys for different segments and moments

• Human escalation for difficult or sensitive cases

• Advertising and acquisition integrations

• Conversation analytics rather than only click path analysis

• Connections across messaging, voice, and video channels

• Integration with core systems such as banking, catalog, booking, or CRM platforms

The principle is simple: build your differentiated customer experience, segments, objectives, and journeys. Use platforms and tools wherever they help you move faster without creating fragmented systems.

Do not build one AI agent for WhatsApp, another for RCS, another for Instagram, and a fourth for voice. That is equivalent to having four different versions of the same salesperson with inconsistent knowledge. You need one core brain, continuously updated and consistently governed.

From Broadcast Marketing to Conversation Marketing

One quote from Beerud stayed with me because it captures the urgency for every marketer.

“The era of broadcast marketing is over.”

Message costs are rising. Consumers are blocking brands, opting out, and tuning out irrelevant communication. This means each message needs to work harder. The old spray and pray model is becoming economically and behaviorally unsustainable.

The transition is from sending a message to starting and supporting a conversation. A message may promote a new product. A conversation should anticipate the questions that follow:

• What colors are available?

• Is this product right for me?

• Can I compare options?

• What is the price history?

• Can I get a refund, exchange, upgrade, or appointment?

That is why reply rate and quality of conversation should become important marketing metrics, alongside opens and clicks. In categories with medium or high ticket sizes, purchases are often made through questions, reassurance, and qualification. Marketing cannot simply generate interest and walk away.

Marketing, sales, and support are converging into one customer experience. The consumer does not care which department owns the next step. They are talking to the brand.

The best analogy Beerud shared was the neighborhood storekeeper. Unlike a giant store with endless aisles, the shopkeeper asks what you need, understands your context, recommends a few products, adjusts based on your response, and helps after the purchase as well. That is conversational commerce at its best.

Why AI Creates Superhuman Campaigns

A human marketer may define ten segments, build three journeys, run a campaign, and optimize results daily. An AI system can create thousands or even millions of microsegments, tailor content at an individual level, manage many journeys at once, and run continuous testing much more frequently.

This does not make the marketer less important. It makes the thinking part more important.

“The execution part has become a lot simpler. The thinking part is going to be far more critical.”

The difference between a good marketer and a great marketer may become even bigger. AI removes a large share of manual execution. What remains is judgment: who to serve, what value to communicate, how to earn trust, when to intervene, and how to create a meaningful relationship.

This is closely connected to the themes in our discussion on agentic marketing and the future of customer engagement. The future is not AI performing random tasks. It is AI operating toward commercial and customer outcomes.

The Framework for the Next Level of Marketing Work

Beerud shared a framework that I think every marketer, product manager, and founder should keep in mind. It describes how work evolves through increasing levels of abstraction.
Humans → Prompts → Loops → Graphs

• Humans: People manually create campaigns, landing pages, code, reports, and customer journeys.

• Prompts: People tell AI what to create.

• Loops: AI repeatedly creates, tests, measures, and improves against a defined objective.

• Graphs: Connected context, memory, workflows, and goals coordinate multiple loops across an entire business process.

For example, a product launch may require landing pages, email copy, campaign templates, website updates, analysis, and follow-up journeys. Instead of managing each task separately, a graph can coordinate the full workflow around a goal.

This is where marketing becomes more strategic. The opportunity is not merely to generate a campaign faster. It is to create systems that continuously learn and improve.

What Entrepreneurs Must Build in the AI Era

For young founders, Beerud offered a necessary caution. Building has become easier for everyone. That also means a lightweight wrapper around a general AI model can be quickly overtaken by the next release of that model.

The question is not only, “Can I build this?” The more important question is, “Why will this still matter when the next model becomes much better?”

The answer often lies in proprietary context. Durable AI products are built around company-specific data, integrations, workflows, policies, industry knowledge, and systems that are not publicly available. A generic capability may become a feature. A deeply embedded, context-rich solution can become infrastructure.

Beerud’s larger message was optimistic. AI will reach every part of the economy, across industries, countries, and use cases. The opportunities are enormous. But the winners will not just add AI to an existing process. They will combine intelligence, context, and real outcomes.

The Real Shift: From Clicks to Relationships

We are moving from clicks to messages, from click paths to conversation logs, from broad segments to a segment of one, and from campaign output to customer outcomes.

In the earlier digital era, brands had to infer what customers wanted from behavior. In the conversational era, customers can state their intent directly. A message contains nuance, sentiment, objections, needs, and preferences. If a brand can understand that context and respond well, it can create something previously reserved for premium customers: a personal relationship at scale.

A bank can give every customer access to the knowledge of its best relationship manager. A retailer can provide every person with a shopping assistant. A hotel can offer every guest a concierge. That is the real promise of conversational AI.

It is not about replacing human relationships with cold automation. It is about making useful, responsive, contextual service available to far more people.

I am Saurabh Agrawal and we come with a new episode on Dilse omni talks every fortnight and cover different aspect of omnichannel with amazing speakers.