Posted by: Theo Paraskevopoulos
09 June 2025
It has been over two years since ChatGPT launched. The technology has finally matured, and so has the conversation around it. What was once a playground for experimentation is now a serious tool ready to deliver business value.
The time for pilots and proofs of concept is over. It's now time to deploy generative AI in real projects that demand a return on investment.
If you're a CTO in a regulated sector, your teams are already experimenting with AI but without a clear strategy.
Artificial intelligence is already a central part of daily workflows. Teams are summarising documents, generating content and writing code. However, what began as productivity gains has now become a governance risk.
When AI usage is invisible, it's unmanageable. And if it's unmanageable, it's unsafe.
The question isn't whether we should use AI, but how do we scale it securely and strategically?
Why waiting for AI to settle down is no longer a strategy
Shadow AI is already happening. Individuals and departments are using tools without oversight, policy or accountability.
Trying to lock it down won't work. Banning AI tools creates bottlenecks and pushes adoption further underground. But embracing it without structure is just as dangerous.
The answer lies in moving from isolated pilots to a properly governed, scalable strategy. That's where Azure AI Foundry comes in and why we use it as the foundation for our enterprise AI deployments.
The real challenge is not technology but ROI
Over the past 18 months, we've worked with enterprise tech leaders who are enthusiastic about AI but stuck. Not because the tools don't exist but because the pathway to adoption isn't clear. They've run the pilots and had the conversations, but they're still stuck because:
- Procurement teams have not adapted to emerging tech
- InfoSec teams need real answers
- Business leaders need proof of value
- Pilots haven't scaled
The solution is structured AI adoption
Azure AI Foundry
We deploy on Azure AI Foundry because it provides enterprise teams control, not just access to tools. With Foundry, you can:
- Build and fine-tune models in your own Azure environment
- Switch between LLMs depending on task, performance, or budget (no rebuilds required)
- Enforce compliance with native Azure governance
- Avoid vendor lock-in and retain complete control
- Own the infrastructure, the models and the security policies.
This is what makes AI enterprise-ready.
Growcreate AI adoption framework
Our AI Adoption Framework guides your AI journey from initial deployment to enterprise-scale adoption.
Support
Deploy inside your existing Azure setup. Engage InfoSec early. Set up guardrails. Treat AI like any other enterprise-grade service.
Enhance
Start small but smart. Use cases like AI search, summaries, copilots, and chat interfaces to deliver quick, low-risk wins.
Evolve
With governance and early results in place, we help you scale by integrating AI into systems, training custom models, and automating intelligently.
Real outcomes and ROI
We're not here to tell you AI will transform your business overnight. It won't.
But deployed well, it will make real, measurable improvements:
- Faster workflows
- Fewer bottlenecks
- Better access to knowledge
- Happier teams
And most importantly, you'll be able to say: "Yes, we're using AI. And yes, we're doing it right."
What do you do next?
You don't need a transformation programme. You need traction. Start with targeted deployments in areas where natural language interaction or task automation can make a difference. Use an iterative approach to test, learn and expand.
Like any tool, the value of generative AI depends on its application and the context in which the tool is used. The difference now is that it is ready. Are you?
From AI experimentation to adoption
We help businesses deploy technology boldly but thoughtfully. Our AI Adoption Framework follows the same principle.
Book a 30-minute AI Readiness Review to identify your first production use case and deliver results fast.
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