Welcome to all the AI news that matters this week. The wins, the fails and the somewhere in-betweens. Across biopharma, medtech, complex manufacturing and insurance. tl;dr: And now for the consequences Last week it became clear AI agents are entering live operational workflows. This week, the consequences arrived. Meta disclosed an agent exposing sensitive data to unauthorised employees - the first high-profile failure of an agent operating inside a production system. Meanwhi

Ask many enterprise leaders if their people use AI and you'll get a confident yes. Ask how many are using it well - you'll likely get a pause. Ramp - the fintech company - publishes internal AI fluency levels. L0 is disengaged or performative. L1 is a competent user. L2 is a non-technical builder. L3 is a technical-grade builder. In 2025, a quarter of their people were L0. Half were L1. Their 2026 target moves everyone out of L0 - staying there is now grounds for dismissal -

Why insurers are navigating an exponential world with linear thinking One European insurance group spent eight years and more than $500 million on a cross-country platforming programme. They never finished it. In contrast, another completed its claims platforming project. But 500% over budget. These are not outliers. Boston Consulting Group’s insurance practice documented them as representative of a wider pattern: programmes conceived for one technology environment, execu

Is AI mightier than the pen? Perhaps it depends on context. Or perhaps there’s no conflict at all. Because there’s mounting evidence that fountain pen wielders are often the heaviest users of digital intelligence. Author and analyst Azeem Azhar - who built a 12KB personality for his AI agent and extracted 146 behavioural patterns from it - does his core thinking with a fountain pen on A4 landscape paper. Alpha Schools - which uses AI tutors and produces average SAT scores 40

Welcome to all the AI news that matters this week. The wins, the fails and the somewhere in-betweens. Across biopharma, medtech, complex manufacturing and insurance. tl;dr: Agents enter the operating loop This week's defining theme is the release of AI agents into live operational workflows. Across every sector covered here, companies announced agent deployments that sit inside core business processes – payments, underwriting, drug discovery, factory robotics and clinical doc

The hypegeist missed it. But something big just emerged in AI-driven biopharma. A new domain was solved. It's another example of digital intelligence expanding by filling the gaps it doesn't yet occupy. First chess in 1997. Then Go in 2016. Protein structure prediction fell with AlphaFold in 2020. Language generation has worked since 2022. Each time, the domain space was considered too complex - or too vast - for AI to assist. Until digital intelligence evolved and finally cr

From theory to proven, validated practice In Part 1, we established that enterprise AI adoption is a coordination problem , not merely an information problem. In Part 2, we set out the five conditions a training programme must create for a focal point to form : reduced options, shared mental models, common knowledge, group identity and visible early adopters. This final part describes what a programme built on those conditions looks like in practice - how Brightbeam's Embed p

Let's hope ‘Women in Tech’ will be a redundant idea soon, an unnecessary qualifier. Just something we used to be conscious of when recruiting, succession planning and sponsoring events. And maybe, just maybe, AI and other digital technologies will help us level the playing fields. In the meantime, before we arrive at that genderless state, we celebrate those women who are breaking through legacy barriers and shining as bright examples to others. These are the fiercely bright

Welcome to all the AI news that matters this week. The wins, the fails and the somewhere in-betweens. Across biopharma, medtech, complex manufacturing and insurance. tl;dr: AI moves inside the firewall Location is the thing this week. Specifically, the location where AI models run, whose infrastructure they sit on and who controls the data they touch. From biotech licensing on-prem research platforms to insurers discovering that most deployments now involve AI, enterprises ar

Your AI got more intelligent last quarter. Its benchmark scores improved. Error rates dropped. But what if less is sometimes more? Research from Anthropic suggests that the nature of the remaining errors have changed - more sophisticated models may also be less predictable. To come to this conclusion, the paper looks at AI failure through two lenses: bias and variance. Bias happens when a model is consistently wrong. Variance, in contrast, is inconsistent difference. Whilst

Training for coordination - as well competence Most enterprise AI training programmes are designed to answer one question: how do we make individuals competent with AI? The Schelling Point Framework asks a different question: how do we create the conditions that means everyone adopts AI within this organisation? Both matter. But its the second is what determines whether adoption scales. In Part 1 we explored the experimental framework, explaining why focal points are key to w

Nineteen investors just gave a startup $47m - to collect the data an insurer's phone system could gather before 10am. Harper is an AI-native brokerage. It didn't exist before October 2024. Within months it wrote $6m in annualised premiums with 25 employees - because its entire model is built around one idea: every call, email and policy makes the next decision sharper. More operational data in, better decisions out. Continuously. But Harper's advantage isn't the AI. It's the

Welcome to all the AI news that matters this week - across biopharma, medtech, manufacturing and insurance. tl;dr: the price of position This week, the cost of having – or lacking – a clear position in the AI value chain became visible. In stock prices. In capital flows. And in and competitive strategy. In one case, the position was geopolitical. But despite common misconceptions, capital is not retreating from AI. It is moving directionally – toward specific chokepoints in t

Two exponentials walk into an advanced manufacturing plant. What happens next? We're about to find out. Because yesterday Nvidia shipped its Vera Rubin platform - promising up to 10x lower inference costs. And Anthropic bought Vercept, to make its platform even more capable of using computers autonomously. One announcement makes AI cheaper. The other makes it more able. They’re different forces. And as they collide, they'll multiply again on impact. The capability curve is st

An electrician uses AI to write quotes, saves 3 hours and sleeps soundly. A corporate strategist drafts reports, saves more and lies awake. Which may be a concern for employers planning to become AI-first, because how much we use a tool is often shaped by how it makes us feel. The electrician's identity lives in practical, physical outcomes. Admin is an overhead - scheduling, invoicing, chasing customers. Removing it feels like a gift today. And a gift to be used again tomorr

A research-grounded approach to training, coaching and culture change The Core Thesis There is no question that Enterprise AI is an information problem - people need to know how to use AI. But is that sufficient? Is it also a coordination problem, a cultural issue? Does it need to be a shared experience - common sense even? In our experience, most training programmes don't think this through, confining themselves to educating individuals about AI's capabilities. At Brightbeam

Its taken a full weekend to get our heads round this. Three wins at the Digital Business Ireland Awards last week. 🥇 Digital Impact of the Year: ALONE , one of our most rewarding clients; 🥇 Women in Digital of the Year: Melissa Proxenos ; and 🥇 Digital Trailblazer of the Year: Brian Hanly With our previous success, that adds up to a lot of glassware. We're now saving to buy a new shelf. Or perhaps we might just reinforce the current one? It's difficult to add anything els

Welcome to all the AI news that matters this week - across biopharma, medtech, life sciences, complex manufacturing and insurance. tl;dr: AI goes live The week's dominant signal across all four sectors was the same: AI moving from experimental to operational. In biopharma, Merck's partnership with Mayo Clinic centres on a production data environment - where Merck will run AI models against de-identified clinical records at scale. The deal signals that a competitive edge i

Agents, disruption and the question of readiness In December 2024, we published ' Cheaper than a Peanut ' - tracking the cost of compute from $20 trillion per GFLOP in 1945 to roughly a penny. Fourteen months later, that same penny can buy you far more. The peanut was a metaphor. But that metaphor is now too expensive. And as a result there are no longer waves of progress. They have united as converging exponentials: cost collapse, efficiency breakthroughs, benchmark annihil

The waves converged. What happened next? A companion to Cheaper than a Peanut (December 2024) In December 2024, Brightbeam published Cheaper than a Peanut , tracking the exponential decline in compute costs from (a theoretical) $20 trillion per GFLOP in 1945 to roughly a penny in 2023. We mapped the history of computing as a series of waves - mainframes, personal computing, the internet, cloud, mobile - each crashing ashore faster than the last. We argued that a second meta w

The polite expert problem In a recent paper, a team at Stanford described how they set out to prove whether agent teams could achieve 'strong synergy'. Would a team of different AI models outperform its best individual member? They did not have human comparisons in mind. But they did reach for the tools organisational psychologists have used on human teams for decades. The same team-building exercises used in MBA programmes and corporate retreats. NASA Moon Survival. Lost a

tl;dr This week’s AI-based developments across biopharma, medtech, life sciences, complex manufacturing and insurance reveal an acceleration of digital intelligence that is structural rather than incremental. AI is moving from advisory to autonomous, from augmenting human decision-making to executing workflows end-to-end. The enterprises that grasp this distinction are pulling ahead. Those treating AI as a bolt-on efficiency tool are discovering – through their share pr

Will AI really mean we end up doing less? What if we end up doing more? And what if task intensity keeps increasing? New research from Berkeley Haas - published in HBR - studied a 200-person tech company for eight months. They found AI intensifies work in three specific ways. 1. Task Expansion: Employees take on responsibilities outside their traditional roles as AI makes unfamiliar tasks feel accessible. Product managers write code, researchers handle engineering tasks and w

A little more than a month ago, we published our Productivity Clock hypothesis . It holds that, for two years, markets have been pricing GenAI on narratives. And that, as a result, 2026 is going to feature a lot of actual measurement. If AI is found to be sufficiently productive, there will have been no bubble. But if enterprise uptake - and therefore spend - is slower than currently forecast, investors will not be able to justify current prices with the updated future ca