Harnessing Generative AI on AWS: Insights from our CTO, Rhys Jacob.

Generative AI, once considered experimental, is increasingly recognised as a core capability for organisations seeking innovation and competitiveness. At D55, we’re working with clients to explore how AWS services like Bedrock and SageMaker can unlock new possibilities, from automating processes to enhancing customer experiences.  

We sat down with our CTO, Rhys Jacob, to talk about where Generative AI is heading, how businesses can take advantage of it, and what role AWS plays in making it enterprise ready.  

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Why Generative AI matters now

Generative AI isn’t just about chatbots or creating content. For CTOs, it’s about scaling intelligence across the business, making insights, automation, and innovation available in real time.  

As Rhys explains:  

“Generative AI has moved from hype to practical use cases. It’s about embedding intelligence into everyday workflows, whether that’s supporting customer service teams, speeding up development, or providing predictive insights for decision makers.”  

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The challenges leaders face

Despite the opportunities, there are key hurdles:  

• Security & compliance: How do you ensure AI models don’t expose sensitive data?  

• Integration: How do you bring AI into existing systems without rebuilding everything?  

• Cost & efficiency: How do you experiment without runaway infrastructure bills?   

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Rhys points out that these challenges are solvable with the right foundation:  

“CTOs need to balance innovation with governance. AWS gives you the tools to deploy AI responsibly, with enterprise-grade security, transparency, and cost controls-built in.”  

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Why AWS is leading in AI

AWS is investing heavily in making AI accessible and safe for enterprises. Amazon Bedrock provides API access to third-party foundation models (such as Anthropic, Cohere, and Meta), enabling businesses to harness Generative AI without the need to build or maintain infrastructure, while Amazon SageMaker enables scalable training, parameter-efficient fine-tuning, and deployment for custom AI models.  

As Rhys says:

“AWS isn’t just providing models; it’s giving enterprises a platform to innovate responsibly. From data privacy to seamless integration with existing cloud workloads, it lowers the barrier to entry while ensuring scale and governance. With tools like Amazon Q, Code Whisperer, and Bedrock, along with SageMaker for customisation, AWS is embedding Generative AI directly into development and productivity workflows.”  

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Looking ahead

Generative AI will move from standalone pilots to being woven into the fabric of business applications. Customer support, analytics, software development, and even supply chain optimisation will all be transformed by AI-powered capabilities.  

Rhys adds:  

“The future isn’t about AI as a separate tool, it’s about AI becoming invisible, seamlessly powering better decisions and customer experiences behind the scenes.”  

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Why D55

At D55, we help businesses move beyond experimentation and put Generative AI into action on AWS. Our team combines deep AWS expertise with a pragmatic approach to ensure AI delivers measurable business outcomes.  

• AWS Specialists – As an AWS Advanced Partner, we understand the latest services like Amazon Bedrock, SageMaker, Amazon Q, and CodeWhisperer, and how to apply them effectively.  

• Outcome-Driven Approach – We focus on business value first, whether that’s faster innovation, improved customer experience, or operational efficiency.  

• Trusted Across Industries – From energy and utilities to SaaS and financial services, we’ve helped organisations modernise and prepare their data and infrastructure for AI.  

• Innovation with Governance – We ensure responsible AI adoption by addressing data privacy, compliance, and scalability from day one.  

With D55, you get more than a technology partner, you get a team that knows how to translate the promise of Generative AI on AWS into real-world impact.  

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Book a discovery call to see how Generative AI can help you with your business workflows.

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