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Most conversations around AI focus on implementation. Which model should we use? How quickly can we build it? What capabilities does it have? But increasingly, we're seeing a different challenge emerge. How do you keep an AI system effective when the technology beneath it is constantly evolving? Models are updated, APIs are deprecated, new providers enter the market, and user expectations continue to rise. Recently, our team upgraded a Realtime AI application and were reminded that building an AI solution is often just the start of the journey. The organisations getting the most value from AI aren't necessarily the ones chasing every new release. They're the ones building systems that can adapt. A few thoughts from a recent project in the carousel below 👇 Read Ellen's full write-up, here: https://lnkd.in/esnWc6W3 #AI #RealtimeAI #ArtificialIntelligence #SoftwareDevelopment #DigitalTransformation

AI isn't the first technology to transform business, and it won't be the last. From the internet and cloud computing to smartphones and big data, every major technology shift has brought excitement, disruption and opportunity. AI may be the most significant of them all but one thing hasn't changed: successful transformation starts with the business problem, not the technology. In this clip from our recent webinar, Dolo reflects on more than 30 years of digital transformation and explains why organisations that take a thoughtful, problem-first approach are the ones most likely to unlock lasting value from AI. Watch the clip below, and if you'd like to see the full webinar, you can catch the replay here on LinkedIn: https://lnkd.in/e5Fjjr7g

Most organisations don't have a technology problem, they have a business case problem. Too often, conversations start with "What should we build?" instead of "What business problem are we trying to solve?" That's how organisations end up investing in software, AI and digital transformation initiatives that look impressive but fail to deliver meaningful value. Technology should never be the starting point - the business outcome should. Whether the right answer is bespoke software, an existing platform, AI, or simply improving the way a process works, the technology should follow a clear business case, not lead it. In Josh's latest blog, he explores: • Why a business case should come before requirements gathering. • Why the best solution isn't always the most technical one. • How to identify AI opportunities that solve real business problems. • The questions every organisation should ask before approving a technology investment. If you're planning your next software project, AI initiative or digital transformation programme, it's worth asking one simple question first: If you removed the technology from the conversation, could you still explain why the investment matters? Read Josh's full article below - link in comments.

The best digital transformation projects don’t start with technology. They start with the business problem. Very pleased to have published my first blog at New Icon, thanks to everyone who takes the time to give it a read.

One thing I've been thinking about recently is how quickly AI adoption can become so fragmented. Different people use different tools, develop their own workflows and find what works for them - that's a good thing. But if those lessons aren't shared, organisations can end up with inconsistent ways of working, duplicated effort and knowledge that's locked away with individuals. Ive added below why I think the hidden challenge of AI adoption isn't technology, but consistency. Read it here: https://lnkd.in/erV2s9Jg Would love to hear whether you're seeing the same thing.

One thing we've been discussing internally is how quickly AI adoption can become fragmented without organisations realising it's happening. A developer might use Claude to create diagrams, someone else might rely on Gemini for documentation, while another person uses ChatGPT for code generation. Individually, there's nothing wrong with that. In fact, experimentation is an important part of the process. The challenge comes when those discoveries stay with individuals instead of becoming part of the organisation. We're seeing a lot of businesses roll out AI by giving people access to tools and hoping they'll figure it out. Over time, everyone develops their own way of working, but nobody is capturing what works, sharing successful workflows or creating a consistent approach across teams. That's when AI adoption stops being a technology challenge and starts becoming an operational one. The organisations seeing the greatest value from AI won't necessarily have the biggest budgets or the most licences. They'll be the ones creating systems around AI adoption, with agreed ways of working, governance and security guardrails, and mechanisms for sharing knowledge across teams. Because AI doesn't remove the need for structure. If anything, it makes it more important. The conversation is changing. It's no longer, "Should we adopt AI?" It's becoming, "How do we stop AI adoption becoming fragmented?" Zoe explores this idea in more depth in her latest blog, looking at why the hidden challenge of AI adoption isn't technology, but consistency. 📖 We'll add the link in the comments. How is your organisation approaching AI today? Are teams still experimenting independently, or are you starting to build repeatable ways of working around it? #AI #AIAdoption #DigitalTransformation #AIGovernance #EnterpriseAI #BusinessTransformation

Yesterday was our company Vision Day - one of those days where we all step back from the day-to-day to look at the bigger picture. We spent the day reflecting on what we've achieved over the year so far, where we're heading next, and how we'll continue helping organisations navigate digital transformation and AI in a way that delivers real business value. We also took the chance to celebrate some brilliant work from the team, and talked about the opportunities we're excited to tackle over the coming months. Of course, it wasn't all strategy... we rounded off the day with bowling and shuffleboard at Roxy Lanes before settling in to watch England get the win. 🎳⚽ A great mix of planning, collaboration and a bit of healthy competition!

AI is no longer a question of if. It's a question of where it can create the most value. During last weeks webinar on 'The good, the bad, and the ugly of AI', Dolo Miah shared the biggest takeaways that emerged from his conversations with business leaders across multiple industries. One message came through consistently: • AI is here to stay • Access to AI isn't the challenge anymore • The organisations seeing the best results are the ones focusing on business problems first, rather than implementing AI for the sake of it. Here's a short clip from the webinar covering those key takeaways. If you'd like to watch the full session, you can catch the replay here on LinkedIn: https://lnkd.in/e5Fjjr7g

Most businesses do not realise they have a technical debt problem until innovation starts slowing down. Technical debt rarely appears because teams are careless, it appears because businesses move quickly: - priorities change - systems evolve - integrations grow - temporary fixes stay longer than intended The issue is not whether technical debt exists, the issue is whether it is being managed intentionally. Because eventually technical debt becomes: - operational friction - delayed transformation - AI adoption barriers - rising delivery costs Sustainable innovation is not about endlessly adding new technology, it is about building systems that can evolve confidently over time. Read the full blog: https://lnkd.in/eVi_2Cuv

It's always great to receive feedback like this following a recent Hackathon Day with Crawford & Company. What stood out most was the emphasis on real-time collaboration between design, engineering and operational teams, turning a clearly defined problem statement into a tangible solution in a matter of hours. A couple of lines from the testimonial that really resonated: "This wasn't a theoretical discussion, it was a hands-on, iterative development with continuous validation of both user value and technical feasibility." "By the end of the day we had both a tangible solution and a clear view on next steps." This is exactly why we run these sessions - they create the space to challenge assumptions, test ideas quickly and build momentum around real business problems. Thanks again to the Crawford & Company team for trusting the process! #Innovation #Hackathon #DigitalTransformation #ProductDevelopment #DesignThinking