The AI readiness checklist: Is your brand really ready for effective AI?

By Harsha Solanki, VP GM Asia, Infobip

Most brands can launch an AI chatbot. Far fewer can deploy AI that learns from every interaction, works across channels, and becomes a durable part of the customer journey.

Indian enterprises are moving fast on digital channels and AI. WhatsApp adoption is widespread, in-app messaging is common, and RCS is gaining momentum. Yet channel adoption does not equal AI readiness: only 27% of brands use a true orchestration platform, and just half say their tools are fully API-ready.

Customer experience is no longer measured by reach, but by continuity. When a customer has to repeat their issue after moving from WhatsApp to email or voice, context is lost, and AI sits on top of siloed data instead of improving the journey. For leaders, the real question is not “Do we have AI?” but “Are we ready for AI to create meaningful outcomes?”

Answering that question calls for a clear AI readiness checklist. Brands should focus on four building foundations: meeting customers on the channels they already use, ensuring context and data travel across those channels, orchestrating journeys rather than deploying isolated tools, and building trust, privacy, and governance into every interaction. So, the questions every brand should answer before scaling AI are:

1. Are you really where your customers are?

Customers do not think in channels; they move between them. A customer may get an order update over SMS, ask a question on WhatsApp, follow up on email, and call support when an issue becomes urgent. The experience should feel like one continuous conversation.

Ten years ago, 73% of traffic was single-channel, as per our latest Messaging Trends report. By 2025, that had fallen to 2.3%, with 98% of interactions spanning multiple channels. SMS still accounts for 62% of traffic on our platform, reinforcing its importance as a dependable channel for essential communication. But messaging applications and rich channels are rapidly expanding the scope for interactive engagement. WhatsApp grew 314% between 2021 and 2025, while RCS interactions in India grew 70% in 2025, signaling growing demand for richer and more conversational messaging.

For brands, being present everywhere does not mean sending the same message across every channel. It means giving each channel a clear role. SMS can deliver critical alerts and authentication. WhatsApp, RCS, chat, email, push notifications, and voice can support service, discovery, transactions, and deeper engagement. The real opportunity emerges when these channels work together rather than operating as separate stacks.

That requires a unified communication platform in which customer data and AI capabilities share a common foundation. Only then can AI choose the right channel at the right time based on a customer’s history, preferences, and immediate needs.

2. Can context, conversations, and data actually travel?

Automation is already widespread. Around 96% of brands automate some customer interactions. However, only 58% say their channels are fully in sync, and 60% have centralized customer data. This explains why many automated experiences still fall short.

AI experiences break when context does not travel. A customer moving across channels should never have to repeat their identity, intent, or urgency; agents and AI should see what has already been tried and whether a query has been resolved, escalated, or left unfinished.

This requires centralized, searchable conversation records, reliable identity resolution, and a clear link between conversations and outcomes, such as a purchase, a resolved complaint, or a renewal. A conversational customer data platform and journey intelligence layer can ingest events in real time and feed context to AI agents and workflows. Without this foundation, AI cannot learn from past interactions or personalize the next one.

3. Are you orchestrating journeys, or just deploying tools?

Deploying an AI tool is not the same as orchestrating a journey. A tool answers questions; orchestration understands an event, determines the next best action, triggers systems, and brings in a human when needed.

Today, only 1/4 of brands use orchestration platforms, and only half call their tools fully API-ready. A chatbot that cannot check an order, update customer data, or trigger a workflow is little more than a sophisticated FAQ engine.

Effective AI blends rule-based flows, automation, generative AI, and agentic AI, each suited to different levels of journey value and risk. The readiness test is simple: can your automation do things, not merely say things? Can AI agents manage a multi-step onboarding, service, or collections journey with the right guardrails?

4. Trust, privacy, integration, and leadership questions

AI cannot scale without trust. Only 9% of organizations report a comprehensive understanding of the Digital Personal Data Protection (DPDP) Act. User trust, privacy, and integration remain leading barriers to deeper adoption. Sustainable AI requires governance of data, permissions, and the actions an AI agent may take autonomously, as well as human-in-the-loop design and safe escalation paths for sensitive interactions.

The real question is not, “Can we launch AI?”; it’s, “Are our foundations ready for AI that learns, orchestrates, and earns trust at scale?” The brands that can bring customer data, AI agents, automation, and journey orchestration into one operating layer will be best positioned to turn AI readiness into meaningful business results.