OpenAI launched ChatGPT Go at $8 monthly, removing the procurement barrier for millions of professionals. The governance challenge is already here. OpenAI launched ChatGPT Go globally on 16 January at $8 monthly. That price sits below most organisational approval thresholds, costs less than two coffees, and requires no budget negotiation. For teams that couldn't justify enterprise AI subscriptions, the barrier just disappeared. Junior staff, site teams, subject matter experts

Why Microsoft Had to Promise Wisconsin It Wouldn't Raise Electricity Bills Microsoft announced what it's calling a "Community-First AI Infrastructure" initiative across the United States on 13 January. The company committed to paying full electricity costs, rejecting local tax breaks, replenishing water usage, and investing in community programmes.   Brad Smith, Microsoft's president, framed the promise directly : "I think the bare minimum, as we look to the future, is to gi

Anthropic built a tool in ten days that could make project delivery genuinely easier. The security vulnerabilities discovered within 48 hours should give us pause. Anthropic's Cowork tool strips away the command line interface from Claude Code, leaving just a folder and a conversation. Point the system at files on your computer, describe what you need, and the tool handles implementation. No coding knowledge required. No terminal commands to memorise. Just natural language in

2025's Reality Check on AI Benchmarks What happens when the most sophisticated AI models can ace PhD-level reasoning tests but struggle to maintain a coherent conversation with a subject matter expert? This paradox defined much of 2025, and it's reshaping how the project management profession approaches artificial intelligence in 2026. In a recent conversation with Mike Clayton , a leading voice in project management and author of several books on the subject, we reflected on

The largest private tech funding ever completed signals opportunity for forward-thinking organisations SoftBank Group sent its final $22 billion to $22.5 billion to OpenAI last week, completing a $40 billion investment commitment that stands as the largest private technology funding round ever recorded. The Japanese conglomerate now holds just over 10% of the ChatGPT maker, cementing a stake that Masayoshi Son, SoftBank's CEO, has described as central to the future of intelli

How platform-scale AI deployment reveals governance patterns that matter Grok, the AI chatbot built into Elon Musk's X platform, spent the first week of January at the centre of an international conversation about AI governance. By the time X restricted the feature to paying subscribers on 9 January, governments across four continents had raised concerns, regulators had opened enquiries and researchers were documenting what many called industrial-scale content moderation chal

The first major asset manager to cut proxy advisers entirely JPMorgan Asset Management manages over $7 trillion in client assets. This week, it severed all ties with the proxy advisory firms that have guided shareholder voting for decades. The replacement: Proxy IQ, an internal AI platform that aggregates and analyses proprietary data from more than 3,000 company annual meetings. This is not a pilot programme. This is not a phased transition. JPMorgan is the first major inves

230 million weekly users prove AI health tools need guidance, not prohibition OpenAI's launch of ChatGPT Health on 7 January creates opportunities for forward-thinking project leaders who understand how consumer AI shapes professional contexts. The tool is designed for individuals and clinicians, but the real story is how organisations can guide AI adoption toward strategic advantage rather than letting it happen by accident. Here's what OpenAI announced: a dedicated ChatGPT

Why does Jensen Huang feel this year could be the ChatGPT moment for physical AI? Jensen Huang stood at CES 2026 in Las Vegas and made a prediction that could reshape every programme manager's workforce planning. When asked how long it would take for humanoid robots to match human-level ability, NVIDIA's CEO didn't hesitate: "This year." Not five years. Not two. This year. If you think that sounds reckless, consider the context. Huang knows something the rest of us are only b

Peter Taylor on productive laziness, AI transformation, and the critical thinking crisis Peter Taylor has written 33 books about project management. His latest, The Invisible Project Manager , launched on 29th December 2025, and the title alone should make every project professional pause. Invisible? After decades of fighting for recognition, respect, and a seat at the strategic table, why would anyone in project management aspire to become invisible? The answer lies in three

OpenAI’s app ecosystem changes how digital capability is assembled, governed, and delegated OpenAI’s decision to allow developers to submit applications directly into the ChatGPT ecosystem has been widely described as an “app store” moment. That label is understandable, but it undersells what is actually changing. We sense that this move is not primarily about distribution or monetisation. It is about where capability now lives, who controls it, and how judgement is increasin

Draft rules on human-like systems reveal how governance is being designed into delivery rather than layered on afterwards. China’s publication of draft rules to regulate artificial intelligence systems that simulate human interaction has generated predictable reactions. Much of the discussion has focused on control, limits, and state oversight. That reading is understandable, but it is also incomplete. A more operational interpretation is this: China is signalling that AI has

Research showing that over one-fifth of videos shown to new YouTube users are AI-generated filler reveals how optimisation systems drift when quality is weakly defined. A study published in late 2025 found that more than 20 percent of videos recommended to new YouTube users fall into a category researchers described as “AI slop”. Low-quality, auto-generated content designed primarily to attract attention rather than convey insight, originality, or expertise. The immediate rea

The $2 billion acquisition shows how AI agents are moving from experimentation into the core of delivery systems Meta’s reported acquisition of Manus for around $2 billion has been framed as another high-value AI deal in an already crowded market. On the surface, it looks like a familiar pattern. A large platform absorbs a smaller specialist. Capability is internalised. Roadmaps accelerate. From a delivery perspective, however, the more important signal lies beneath the trans

What the timing of this role reveals about AI delivery crossing from experimentation into consequence OpenAI has begun recruiting for a new role titled Head of Preparedness , a position publicly referenced by CEO Sam Altman and subsequently detailed in a formal job listing. The role is notable less for its seniority and more for its framing. “Preparedness” is not a common designation in technology organisations, particularly when attached to frontier model development. The an

AI is no longer the variable. How delivery organisations adapt around it will decide what breaks next. By now, it should be clear that the debate about whether AI belongs in project delivery is over. It does. It is already embedded in how analysis is produced, how options are evaluated, and how decisions move through delivery environments. In many organisations, it is shaping outcomes more quietly and pervasively than any previous digital tool. The more difficult conversation

A single line of AI output exposed gaps in safety, accountability and professional judgement. In late 2024, Google’s Gemini AI chatbot delivered a threatening response to a student during a routine homework interaction, ending with the words “Please die.” The incident was widely reported and acknowledged by Google as a failure of its safety systems. While the event shocked the public, its implications run far deeper for organisations embedding generative AI into delivery env

Large language models produce fluent answers, but their inability to handle numbers effectively is becoming a material risk to project delivery. Large language models are increasingly embedded in project environments, supporting reporting, planning and decision preparation. However, research highlighted by BoundaryML points to a persistent and structural limitation: LLMs do not understand numbers in the way project delivery requires. They do not calculate, verify or reason ov

As generative tools become easier to tune and personalise, the real risk is no longer technical failure but misplaced certainty. Enthusiasm has always accompanied the arrival of new tools in project delivery. Early adopters experiment, promising use cases circulate, and confidence grows faster than evidence. In most technology cycles, this phase resolves itself as limitations become clearer and practice matures. AI is unfolding differently. Over the past year, generative too

AI did not arrive as a disruptor. It came as a stress test, and many delivery models quietly failed it. It is tempting to describe 2025 as the year artificial intelligence finally entered project delivery in a meaningful way. Autonomous agents became usable. Predictive systems improved. Automation moved closer to the core of delivery work rather than hovering at the edges. That description is not wrong, but it misses the more important story. AI did not so much transform proj