Last week, I had the privilege of delivering a keynote presentation at Monday.com’s Elevate conference in London. The topic, “Leveraging data and artificial intelligence (AI) for organisational transformation,” allowed me to challenge some common misconceptions about AI adoption and share practical insights on harnessing the power of existing data. In this post, I outline the key themes discussed and provide some additional context.

In the wake of the meteoric rise of generative AI, it’s easy to get swept up in the hype and believe that this single branch of artificial intelligence (AI) is the whole story. Platforms like ChatGPT have undeniably captured the public imagination, marking the first mass consumerisation of AI technology. However, focusing solely on generative AI risks overshadowing the diverse and equally transformative types of AI that have been quietly but powerfully driving business innovation.

Earlier this week, I got the opportunity to speak at our Amazon Web Services (AWS) office in London, to an audience of Private Equity firms and their portfolio company executives about driving value creation through AI and data. The presentation focused on how Private Equity firms and their portfolio companies can drive value creation through AI and data. I also took the opportunity to introduce a new concept called the AI Stages of Adoption (AISA), which is designed to help organisations assess their maturity and readiness for AI adoption.

As artificial intelligence (AI) advances into the workplace rapidly, one of the most pressing questions on everyone’s mind is, “If machines can do our jobs faster, more accurately, and at a lower cost, what happens to us?” It’s true that AI is beginning to redefine the very essence of work, raising concerns about the potential displacement of knowledge workers. However, I’d like to propose an alternative perspective—one where those same workers earn the same or more whilst working far fewer hours.

I had an incredible afternoon as a guest lecturer at the The London School of Economics and Political Science (LSE) where I got to discuss harnessing AI for organisational transformation led from the Board, at this summer’s Data Science for Executives class.

Custom Model Import’s = game changing! If you own your own corpus of data and are using it to train your own models, you can now bring those models to Amazon Bedrock’s secure, managed environment.

Just as we were catching our breath on Claude 3 Opus arriving on Amazon Bedrock, here we go again, this time it’s Meta’s Llama 3 model - designed for you to build, experiment, and responsibly scale your generative artificial intelligence (AI) applications; now with improvements in reasoning, code generation, and instruction.

This just in! Anthropic’s Claude 3 Opus foundation model is now available on Amazon Bedrock, joining Claude Sonnet and Claude Haiku. Bedrock is now the first and only place to offer all three Claude 3 models in general availability.

The Amazon Web Services (AWS) executive’s guide to generative AI is out now; I spoke to Duncan Jefferies about how businesses can use generative AI to drive organisational transformation.

Given Adam’s announcement yesterday about Amazon PartyRock powered by Amazon Bedrock, I decided I couldn’t wait to get my hands on it and see what kind of app I could build.