Luke McNamara
Sales Director – Trusst AI
June 24, 2025
Around 2010 there was a popular phrase attributed to social media that stated, “if you’re not paying for the product, you are the product.” We can see a similar trend with Generative AI applications in the Customer Experience (CX) space.
Conversations – whether voice, chat, sms, social or email—have become one of the richest sources of customer insight. Yet despite this, many organizations still treat those interactions as transactional, not strategic.
The reason? Their AI isn’t really theirs.
McKinsey warns: “CDOs need to assess the broad risks associated with exposing the business’s data, such as the potential exposure of trade secrets when confidential and proprietary code is shared with generative AI models, and prioritize the greatest threats.” McKinsey Digital: The data dividend: Fueling generative AI
Many businesses have outsourced their AI (and thus their IP) to third-party platforms where the models and data are hosted by the vendor. These tools that are generic, in that they are one-size-fits-all across all industries and importantly, they do not understand the specifics of your business.
When you don’t own the models underpinning your customer experience, you’re effectively training someone else’s system. You’re feeding them your most valuable data while getting back generic functionality in return.
Why Ownership Matters
Owning your AI isn’t just a technical preference – it’s a strategic imperative.
When you control the system that interprets, responds to, and learns from your customer interactions, you can embed your unique knowledge, tone, and priorities directly into every experience. Examples:
- Banking & Financial Services: Embed institution-specific compliance language and complaints regulations
- Retail & eCommerce: Tailor product recommendation logic based on local inventory, customer lifetime value, or seasonal campaigns
- Healthcare: Adapt intake questions, follow-ups, and triage flows to reflect clinical protocols
- Telecom & Energy Retailers: Recognize subtle language cues that signal upsell, downgrade, or cancellation intent
- Insurance: Route claims using internal triage models based on claim type, severity, and past interactions
- Travel: Recognize loyalty triggers in traveller behavior and tailor offers accordingly
Off-the-shelf models are built to be general-purpose. They’ll never understand your business the way a system trained on your own data can.
AI Should Fit Into Your Stack and Not the Other Way Around
Ownership also means integration on your terms. The best AI applications don’t require you to rip and replace your tech stack. They live where your data already resides. They adapt to your workflows and systems, whether that’s contact center, CRM, ERP, service management, or internal analytics tools.
Just as importantly, they evolve in line with your teams; not behind a closed roadmap.
This approach avoids vendor lock-in and allows for long-term adaptability as your business adapts. You decide what the AI learns, how it behaves, and where it shows up in your customer journey.
From Automation to Institutional Memory
AI trained on your data becomes a memory system. It remembers what customers asked, how you responded, what worked, and what didn’t. Over time, that knowledge can inform not just service delivery, but product development, marketing strategy, and operational planning.
This kind of system-level intelligence is only possible when the platform resides in your virtual private cloud (VPC) and you control the data.
Owning your AI doesn’t just improve customer experience. It sharpens your competitive edge and turns every interaction into a feedback loop for the entire business.
Ownership isn’t optional anymore. It’s the difference between building long-term value OR building someone else’s model.