Don't view AI as just a feature set. Instead, treat "intelligence" as a fundamental new building block for software, on par with established primitives like databases or APIs. When conceptualizing any new product, assume this intelligence layer is a non-negotiable part of the technology stack to solve user problems effectively.

Customers now expect DaaS vendors to provide "agentic AI" that automates and orchestrates the entire workflow—from data integration to delivering actionable intelligence. The vendor's responsibility has shifted from merely delivering raw data to owning the execution of a business outcome, where swift integration is synonymous with retention.

Don't worry if customers know they're talking to an AI. As long as the agent is helpful, provides value, and creates a smooth experience, people don't mind. In many cases, a responsive, value-adding AI is preferable to a slow or mediocre human interaction. The focus should be on quality of service, not on hiding the AI.

Effective AI moves beyond a simple monitoring dashboard by translating intelligence directly into action. It should accelerate work tasks, suggest marketing content, identify product issues, and triage service tickets, embedding it as a strategic driver rather than a passive analytics tool.

Exposing your platform via a Model Consumable Platform (MCP) does more than enable integrations. It acts as a research tool. By observing where developers and LLMs succeed or fail when calling your API, you can discover emergent use cases and find inspiration for new, polished AI-native product features.

The end state for enterprise AI is a unified, conversational agent serving as the primary interface for a brand. This "digital concierge" will handle sales, support, and other interactions, potentially replacing websites and mobile apps as the main customer touchpoint.

Intercom's CEO predicts that companies will abandon separate AI agents for sales, service, and onboarding. A single, coordinated "customer agent" is necessary to avoid conflicting goals and create a seamless, high-touch experience for every user.

The initial impact of AI agents is cost reduction in customer service. However, the second-order effect is more profound: AI agents will become the primary interface for brands, driving sales and creating personalized concierge experiences. Companies that embrace this will gain a significant competitive edge in customer lifetime value.

Prioritize using AI to support human agents internally. A co-pilot model equips agents with instant, accurate information, enabling them to resolve complex issues faster and provide a more natural, less-scripted customer experience.