Board

While here in San Francisco for a business trip, I got the opportunity to spend time with technology innovators and leaders, and what struck me was the contrast in AI adoption approaches, and openness to transformation using AI compared to my experiences in Europe. A new benchmark report from Gallup has confirmed what many of us in technology leadership have long suspected: Europe’s lag in AI adoption isn’t a matter of insufficient capital – it’s a cultural challenge that runs deep.

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.

I recently spoke with Duncan Jefferies about how businesses can effectively harness generative AI to drive organisational transformation. The resulting AWS executive’s guide to generative AI offers a comprehensive roadmap for business leaders navigating this transformative technology. Here are the key insights and practical steps for organisations looking to unlock the potential of generative AI.

Last night I had the pleasure of speaking at the Chief Wine Officer event hosted by AWS at London’s National Portrait Gallery. The focus was on demystifying generative AI and helping business leaders understand how to harness its potential for real organisational transformation.

I recently contributed to the AWS Executive’s Guide to the Digital Workplace, exploring how organisations can successfully navigate digital transformation and build robust cloud-based infrastructures. Here are the key insights leaders need to consider when driving workplace digitalisation.

In my article about not taking your foot off the gas, published just as the world returned to some degree of normality in July 2021, I discussed that the pandemic was the forcing function that challenged businesses to adapt and engage in broad organisational transformation using the cloud, and that it should not be seen as a reason to slow down.