Smart Enterprises choose Native AI first.

The decision to build custom enterprise AI wrappers or leverage native AI within existing systems represents a critical strategic choice for orgs.

Custom enterprise AI wrappers built by centralised AI teams initially appeal to executives for understandable reasons:

✅ Consistent user experience across platforms

✅ Unified security and governance controls

✅ Enterprise data integration across silos

✅ Tailored capabilities for specific use cases

This approach creates a comforting illusion of control. But it often results in:

⚠️ Lengthy development cycles while native AI capabilities rapidly evolve (see image)

⚠️ Tech debt when frontier models evolve too quickly

⚠️ Adoption friction as users must learn yet another interface outside of their workflow

⚠️ Widening gaps between central AI teams and frontline business needs

⚠️ Delay of practical AI application for months or years

In contrast, Native AI available OOTB within existing systems of records like Salesforce Einstein, Microsoft Copilot, ServiceNow Now Platform etc., provides immediate benefits:

🚀 Zero learning curve for basic functionality

🚀 Contextual awareness of existing workflows

🚀 Automatic updates as capabilities evolve

🚀 Lower implementation barriers and faster adoption

The most successful organisations I've observed take a staged, hybrid approach.

1. Begin with native AI tools to drive immediate adoption and baseline capabilities

2. Monitor actual usage patterns to identify genuine gaps and friction points

3. Build custom capabilities selectively ONLY where native tools demonstrably fall short

4. Focus central AI teams on enablement, not just development

This approach ensures your enterprise resources are not wasted and your AI strategy addresses real user needs rather than hypothetical ones.

Start with what works now and is embedded within your systems of record. 

And remember that your technical integration approach matters far less than your human integration strategy. 

(Ref: https://lnkd.in/gkY_nyFG).

Animation credit: Peter Gostev

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