Tag: DigitalTransformation

The GenAI Imperative: Are You Leaving Money and Time on the Table?

A little while ago I wrote an article that talked about the urgency of adopting Generative AI (GenAI). The more organisations I speak to, who then see the potential of GenAI, the more I realise that it’s an imperative – that the world is changing around organisations and those that are not planning to adopt are leaving both time and cost savings on the table (the ROI is tangible). This hesitation could be costing businesses more than they realise – the loss of a competitive edge.

It’s all about the interface: How Natural Language Interfaces are Redefining the Way We Work

Mulling over why systems like ChatGPT, Perplexity, Gamma, Gemini, Claude etc. are so successful – it’s all about the interface. It isn’t just about their perceived intelligence – it’s about how they interact with us – it’s about the interface; the natural language interface . It’s a shift in how humans and machines collaborate. What does this mean as an approach to business.

GenAI Projects: 30% will be dropped by the end of 2025…. hmmm… is that really a problem?

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.

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.

Identifying AI Risks: A New Tool for Businesses

Understanding the risks in any organisation or project takes time and usually involves one or more risk workshops, more often than not starting with a blank sheet of paper. Massachusetts Institute of Technology (MIT) have provided us with a short cut to identify risks associated with artificial intelligence using a new resource, the AI Risk Repository – save time and improve the breadth and depth of risks.