Tagged with: #digital-transformation

AI answer engines like Claude, ChatGPT, and Perplexity are fundamentally reshaping how value flows through information ecosystems. Unlike the web era’s simple traffic exchange, these systems synthesise and enhance proprietary data, creating entirely new possibilities for value creation. Bloomberg and the Financial Times demonstrate how organisations can transform this shift into competitive advantage through innovative AI models and sustainable value exchange frameworks. This article explores how Boards can leverage these lessons to build ecosystems where data owners, AI platforms, and users all benefit from the extraordinary value being created.

In June of 2024, I introduced the concept of the AI Stages of Adoption (AISA), a framework for understanding where organisations are in their AI journey. Since then, I’ve had countless conversations with business leaders about how this framework helps them navigate their transformation. Today, I want to share a deeper perspective on AISA and how you can use it to accelerate your organisation’s AI adoption.

Last night, I had the pleasure of returning to the Chief Wine Officer event series on behalf of AWS, this time addressing leaders from private equity portfolio companies on a topic close to my heart: turning organisational data into strategic value. The evening, hosted at Spring at Somerset House, brought together executives eager to explore how to accelerate value creation through data monetisation within PE timeframes.

In 1998, I walked into the headquarters of our newly acquired newspaper group in Leeds, a result of a private equity-backed management buyout of United News & Media’s regional newspaper and magazine titles. Tasked with ‘doing the internet’, I found a small semblance of online activity in the form of a basic advertising website for the Yorkshire Post. A couple of weeks of getting my feet under my desk yielded a digital goldmine - 271 years of content waiting to be transformed into digital assets.

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.

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.

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.

For many Boards, the pandemic has catalysed broad business change by accelerating digital transformation initiatives. The availability of cloud computing has democratised access to technology, and businesses of all shapes and sizes have seized on this opportunity to: increase revenue, margin, and profit; enter new markets and launch new products and services; delight, excite and get closer to their customers; and become more operationally efficient, increasing productivity, cutting waste, and reducing costs.