AWS rolled into London for their annual Summit with a message of acceleration, investment, and a little bit of magic.
At the AWS Summit London, AWS demonstrated how AI significantly accelerates overall business efficiency. This vital transformation requires modern cloud infrastructure, AI capabilities, and skilled personnel. While UK AI adoption is growing rapidly, organisations must modernise legacy systems to unlock billions in future productivity gains. To combat widespread skill shortages, AWS is investing heavily in new training programs. Furthermore, AWS demonstrated Kiro, an advanced AI agent acting as a full-stack engineering partner to rapidly generate, test, and deploy production-ready code.
If anyone were to come to you and say that they had found a way to make your company 80% more efficient, I imagine your response would be either “please, tell me more” or “you’re talking rubbish.”
When the person making these claims is the VP & Managing Director of AWS UK & Ireland, you might be willing to listen more.
“At AWS, we needed to completely rebuild the inference engine behind Bedrock from scratch,” said Alison Kay at the AWS Summit London. “Now, if you’d asked me two years ago what that would have taken, I would have said 40 engineers, 12 months and a whole lot of coffee.
“Six engineers did it in 76 days. How? Because they weren’t working alone, they were working alongside Kiro agents that wrote code, tested it, found bugs, fixed them, and deployed it around the clock. While the engineers slept, the agents kept building.”
This message around AI is one that we have come to familiarise ourselves with over the last year or so. On stage, Kay said that the speed AI can bring could be described as “magic” before scuppering her chances of entering the magic circle by revealing the foundation of how AWS are making businesses more efficient.
“Today, we are here to demystify the science behind the magic,” said Kay. “We’ve distilled it down to three building blocks.
“The first is a modern cloud infrastructure, the foundation that unlocks the full digital potential of every business. The second, well, it’s AI, the capability that transforms possibility into reality. And the third is skills, the people who know how to harness the infrastructure and the AI to create the magic.”
One of the fundamental ways AWS encouraged its customers to embrace AI is to modernise the services they use and go deeper with AWS in order to get the best out of the hyperscaler. Or as Kay put it: “You can’t build advanced AI on outdated foundations.
“The real transformation is not in the migration, it’s in the modernisation. Modernisation is about optimising workloads built, breaking down monolithic barriers, eliminating the technical debt and building for the future. It’s what helps data to stop being trapped in legacy platforms. It becomes accessible, queryable, and actionable.
“Modernisation makes systems move faster, more resilient, secure and cost-efficient, and importantly, it unlocks the transformative power of AI. Now, interestingly, our research shows that 64% of UK organisations have now adopted AI, up from 52% only a year ago. That’s the equivalent of one UK business adopting AI every 40 seconds; however, only one in four of those adopters are using AI at its most advanced levels.
“Most organisations are still in the early stages of adoption, employee productivity, basic automation and experimentation, and our research shows that the UK could unlock 35 billion pounds of productivity gains by 2030 if Basic adopters moved to advanced AI.”
Investing in Future
In the opening keynote, Kay said that the building blocks of infrastructure AI and skills can “unlock extraordinary customer outcomes, but these results don’t happen in isolation” before acknowledging the role partners have in “translating the technology into real business outcomes.”
Throughout the opening keynote, attendees were able to hear about these business outcomes. Attendees were told how Evri uses AWS generative AI to automatically analyze over 90 million delivery photos per month to detect mis-deliveries and ensure parcels arrive at the right place, how Experian has built a transformative data and analytics platform on AWS to unify fragmented data and accelerate new product launches from months to weeks, and how the Jane Goodall Institute uses Amazon Bedrock and Amazon SageMaker to digitize decades of handwritten notes and film into an AI-powered research platform for chimpanzee behavior.
But the potential for AI to do incredible things isn’t something up for debate. The biggest question to answer is how to implement it best.
“We know science, it’s only powerful when it’s in the hands of people who know how to use it,” said Kay. “Our research shows that almost 50% of UK organisations cite skill shortages as the biggest single barrier to their ability to adopt AI.
“At AWS, we are committed to creating the conditions for organisations in the UK and Ireland to succeed through investments in skills, in training and in support programmes. Take, for example, the AWS skills to Job Tech Alliance, which we announced here on this stage last year. It has a goal to prepare at least 100,000 learners with AI skills by 2030, and we are well on our way.
“We’ve now prepared over 60,000 students on Cloud skills and AI, and we all know that skills initiatives are critical, and we are continuing to invest in training in order to unlock the full potential of this technology.”
First Frontier
One of the first ways that AWS is helping businesses unlock the full potential of artificial intelligence is with its AI agent, Kiro.
“What used to take years can now be done in days and sometimes even minutes within Amazon,” said Kay. “Agents are being used across every single job, function and family, and the results are incredible.
“Our legal teams are able to synthesise Complex Regional requirements using a single prompt. Our Amazon account managers have transformed from spreadsheet warriors to trusted advisors with the ability to generate international expansion strategies on demand, and one of our most distinguished engineers was able to ship more code in five months than in the past 10 years with agents. We’re completely reimagining the way that we build software.”
Instead of just spitting out snippets, Kiro works like a full-stack engineering partner, turning natural-language prompts into user stories, acceptance criteria, technical design docs, and architecture diagrams, then generates, tests, and applies it to production-ready code according to an organisation’s patterns and steering files.
“AI-powered software development tools evolved rapidly over the past year, from inline tab completion to authoring entire functions to completing multi-step tasks,” continued Kay. “But as these tools became more powerful, we’ve noticed a gap. They were generating code, but builders couldn’t guide the process or ensure it aligned with their team’s standards.
“We wanted to take everything that is exciting about AI-powered software development and add the structure that our developers really need. Kiro works with developers, turning your prompts into detailed specs and those specs into working code.”
