Organisations will turn to external partners for GenAI implementations and the success of your GenAI project depends heavily on the clarity of your requirements.
A well-prepared RFP with comprehensive requirements isn’t just bureaucratic paperwork – it’s your blueprint for AI implementation success. Let’s dive into some insights on creating requirements that will attract the right vendors and set your GenAI project up for success.
In today’s fast-paced business environment, Project Managers are continually seeking innovative tools to enhance efficiency and deliver successful outcomes and the Project Management Institute (PMI) seems to be stepping up.
I have written previously about technical debt and GenAI choices and when you add on Shadow GenAI the situation becomes even more complex. The accessibility of Generative AI (GenAI) tools means that everyone can innovate like never before. However, this surge in un-monitored GenAI usage, often referred to as “Shadow AI”, combined with GenAI only now starting to come down from the ‘Peak of Inflated Expectations’ can lead to significant challenges, including the accumulation of technical debt within organisations.
In preparing last weeks article I came across a series of blog posts from Ardoq (thanks to Ed Granger) that deserves more attention (catch it here). There are quite a few posts (maybe too many) on how GenAI and Agentic AI can be used in organisations but not much on how we conceptualise and plan for this from a Enterprise Architecture (EA) perspective. Ardoq’s insightful blog series delves into GenAI’s impact on EA and more – it’s really worth a read.
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?
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.
I couldn’t believe the timing this week. As I’m working through the course material for the Microsoft AI Engineer exam a post dropped from Rajani Janaki Ram with a Framework on Adopting AI on Azure – brilliant! I thought I’d review the framework this week and what it means.
Generative AI (GenAI) is full of potential, but like any rapidly evolving technology, it carries the risk of technical debt. Making the right decisions now can prevent future headaches. Let’s explore how you can be shrewd about your GenAI investments.
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…”.
