A week or two ago I came across an article from Business Standard that summarised a Gartner report suggesting that over 30% of GenAI projects won’t survive beyond proof of concept (PoC) and will be dropped by the end of 2025. Having run a large project portfolio I’m always interested in stats like this so I decided to pick at this a little and see whether this is indeed an issue, or just a headline.
Tag: FutureOfWork
The Role of Unions in an Agentic AI World
The upcoming rise of Agentic AI – AI that operates more like an independent worker than a traditional tool will fundamentally transform the landscape of work. This evolution prompts an important question: what role do unions play in a world where AI acts as a virtual employee?
HR’s Role in the World of Agentic AI: Shaping the Future of Virtual Employees
The world of AI is evolving rapidly, moving from passive tools to dynamic, “agentic” AI – technology that can operate autonomously, making decisions, interacting with employees, and handling tasks like a true virtual team member. While this shift brings exciting opportunities for efficiency it also brings new challenges for oversight, ethics, and integration into workplace culture. HR stands at the heart of this, ensuring that these “virtual employees” align with company values, policies, and workforce goals.
The GenAI Skills Gap Seems Real: Are most people just getting started?
Am I living in a GenAI echo chamber? While my LinkedIn feed overflows with the latest AI breakthroughs and ‘must-try’ features, my experience in the trenches tells a different story. As a volunteer leading GenAI projects, delivering prompt engineering training and talking about GenAI in the non-profit sector, I’ve witnessed a gulf between the breathless pace of AI innovation and how most people actually use these tools day-to-day. (I have to say that I have not noticed resistance, concern – yes, but not resistance and in all cases I see the ‘wow’ moment happen when people realise the possibilities and practical applications.)
How AWS, IBM, Google, and Microsoft Are Shaping the Future of Business (AIaaS)
After completing certifications in the various platforms from IBM, Amazon Web Services (AWS), Microsoft and Google I wanted to take a high level look at what these platforms really mean for organisations. These organisations are offering powerful AI platforms that provide a way to access AI functionality without having to develop and run your own infrastructure and manage your own AI deployments.
Beyond ChatGPT 4.0: Meet the Next Step in AI Assistance
(This week is an experiment to see what you think about the new ChatGPT o1-preview model output. I iterated through prompts to ask o1-preview to introduce itself and explain its abilities using my usual article format. The title of this article and all of the main article text below are 100% generated by the o1-preview model. What do you think? My opinion is at the end. For the record it took 29 seconds to generate the content.)
The Urgency of Generative AI: Today’s Competitive Edge, Tomorrow’s Necessity
As I explore the AI development platforms from major providers like IBM , Google, Amazon Web Services (AWS) and Microsoft it’s clear that they are increasingly offering tools that provide easy access to both pre-trained models and custom model training (we also have easy API access to models like ChatGPT and Gemini). A recent report from the IBM Institute for Business Value included a sentence that resonated with me: “The competitive edge that generative AI delivers today will be table stakes tomorrow.” This insight feels particularly relevant when considering the services these major platforms offer – its power to differentiate will diminish.
AI and Change Management: OCM’s crucial role in AI Projects
In a Gartner presentation by Max Goss this week the subject of Organisational Change Management (OCM) in AI projects was brought up. OCM has always been important in IT projects but what makes it different in AI projects? Well, no surprise, it’s not just about the technology, it’s about the usual suspects such as communications, involving the right stakeholders, leveraging change networks and delivering training but there are more things to consider in the rapidly evolving landscape of AI.
Deploying AI: What Somebody Seems to be Putting Together
After posting last weeks article (Deploying AI: What nobody seems to be putting together) where I suggested that we have fragmentation in approaches to AI deployment I saw a number of things come together. EY launched EY.ai (actually, back in Sept 2023), then a great post from Chris Howard at Gartner (Top of Mind – “Are 100% Accurate AI Language Models Even Useful?”) where Chris mentions ‘…as we hit the trough of disillusionment with generative AI…”.
AI Risk and AI Management Formalised by NIST & ISO
These two subjects, with separate sections below are intertwined – understanding AI risk and the management of AI systems go hand in hand. Luckily NIST and ISO provide us with some tools to help with both.