Something very unpleasant is happening to us all: rapid change. Rapid change is very uncomfortable for humans so we do anything we can to avoid it, particularly if it strikes at the heart of our sense of self, status, affections or aspirations. The speed of technology development is always hard to manage for humans but the speed of (Gen)AI -driven change is truly startling. Here are some examples. 1. Investors that I meet are struggling to find stability in this AI quicksand.

As I meet more and more prospects in the mid-market, I see similar patterns. One of these is the lack of a CRM tool. There is often something else acting in the role (a spreadsheet or a highly customised application that was first designed to do something else). If you want to get insights on your customers (and you do) then you should think about getting a solution that is designed for the purpose, and can form the data foundation of your AI future. There are lots of good, c

If you are looking to start using AI in your business then this is a great litmus test for likely success: It’s not the most technically impressive workflows that move the needle. It’s the ones that are: 1. Easy to adopt 2. Embedded in the way people already work 3. Instantly useful

There are three modes of AI usage in the corporate environment. 1. Ad-hoc. Using Microsoft Copilot or ChatGPT to achieve or speed up tasks. Summarise this, idea that, create a picture etc. 2. Data Driven. Data science heavy scenarios using Machine Learning and other AI tooling to spot patterns in data. 3. Structured Workflow. Combining documents and data with AI technology to automate and transform businesses. We do number 3. It's a new category and we're leading the way with

If you are deploying an AI solution and it requires all of your general users to become really good at prompting, in order to get accurate answers, then your solution will fail.

When doing an online course for compliance training at work, you often need to complete a quiz. Top Tip: If you are unsure how to answer, the longest answer is usually the right one. Question setters don’t bother writing long false answers (and employees read LinkedIn posts like this one) because they don’t enjoy doing the task. People will generally take the path that requires the least amount of work unless they are specifically motivated for some other reason. If you are l

Love this line: That means if you’re still shipping AI features that require users to figure out the prompt, you’re not building for the new standard. You can't expect users to become prompt engineers. It won't scale.

As I interact with businesses in my day-to-day life, I see so much opportunity for them to transform. As a case in point, I had a disappointing experience with WeBuyAnyCar.com this week and it could have been so much better. You may not be surprised to hear that the offer I got on arrival was not the offer made via the original enquiry. My car was rated Grade 3, and one of the reasons given was that it did not have <5k miles, despite giving them the mileage (68k) on the origi

If you see a company try to “ban” the use of AI, without a coherent plan or alternative, then that is a big red flag imo. It’s an indicator of potential business challenges for them in the medium term. Companies need to sign up for the future or they will become irrelevant really fast. Why not ask ChatGPT how AI could transform your business? The answers are very interesting. You don’t need a consultancy to identify opportunities, but you might need one to help you pick and d

Interesting article yesterday on the BBC: person reacts in horror and potential loss of personal relevance due to introduction of AI (link below.) Horrific reactions are not known to stop the march of technology. The cause of this latest burst of horror is debut of an AI actor, Tilly Norwood, who is now being represented by a talent agency. This is beginning of a new pattern. Human interest will determine what happens next, but let's imagine that the AI actor is cheap and wil

We used to run a business that drove a Social Mobility agenda into early career technology roles. We stopped that because we saw AI taking over those early-career roles in the future. And that now appears to be happening in a number of industries. The problem is that you still need to hire early-career people, or else you will not create the next generation of expertise for your business. Having spent quite a bit of time in this area, here is my advice for any company hiring

Humans make mistakes and some humans make more mistakes than others. Where we see persistent failure, we tend to inspect more and trust less. This is a patterns that humans have learned to follow, based upon as assessment of risk through probability and impact. AI agents are not perfect, either, and they can make mistakes. They are an unproven risk in your workflow. You should treat them as would a new junior analyst in your team, and ensure you are checking the work. This do

This is going on in pretty much every organisation, I suspect. If your teams do upload pii data to ChatGPT, say, it’s used to train models. This means that the data is broken in chunks and used to refine models at a statistical level. Say you work at xyz plc and upload a customer list. I can not then go to the AI service and say “show me all customers for xyz plc.” (Note that the AI vendor employees can see all the data in its message form.) Ultimately, this is still a breach

If you are rolling out Copilot or ChatGPT to your company and are trying to teach everyone “prompt engineering” then you are heading for a mess. Why? Prompts are critical for accuracy of outcomes. A small, human, variation in prompts will produce huge variations in quality and outcome. This is just a non-starter for structured workflows. Effective prompts and instructions sets are non trivial; some of our scenarios run into 100s of lines. How do you audit all the prompt

Adoption is the number one item in corporate AI projects. By miles. People will only start to use new tools if they understand why, know it’s not a threat and if they are fit for purpose. I would not punish/reward usage in the way being suggested in this article. If the tools are no good then people won't use them. Instead, perhaps punish the people serving up the tools: they should link usage KPIs to the promotion of the business system tool teams. Employee KPIs should

When the Internet/SaaS took over the world, people had to create or repurpose the budgets for tooling. IT spend is still very low in most companies, perhaps <2% of revenue. The global IT market that spooled out from that is very large indeed (say $5T in 2025 according to Gartner). Consider the four following ideas: 1. With AI automating tasks or outcomes, the budget allocated will likely be re-purposed from the labour cost, which will by closer to 30-50% of revenue. 2. AI en

Adoption is the number one item in corporate AI projects. By miles. People will only start to use new tools if they understand why, know it’s not a threat and if they are fit for purpose. I would not punish/reward usage in the way being suggested in this article. If the tools are no good then people won't use them. Instead, perhaps punish the people serving up the tools: they should link usage KPIs to the promotion of the business system tool teams. Employee KPIs should be cu

Around the year 2000 (ish) lots of people said these words: “No-one will buy a t-shirt on the Internet.” I agreed with this. You can’t try it on and returning it was (is) a pain. At that time I thought people might buy a known commodity, like a bottle of Jack Daniels, but the cost and wait time would be too high. Now I mostly buy clothes online. ASOS made a business out of it, along with many other retail channels. My weekly shop is all online. I can even do panic sho

It is the story of new technology since the beginning of technology. You can’t make a cynic an early adopter. Trying to change their mindset is a waste of time. I show prospects the power of AI and some run towards the possibilities and others run away from them. I think the law of diffusion is a useful guide here. Perhaps 15% of any audience is an early adopter. Focus all the attention there. https://lnkd.in/e9isKbT8

If someone walks in to your office to sell you “AI”, and they start demoing a software product, then don’t expect the next step to be a magical transition to an AI future. Tools should not be the starting point. Start by talking about what your business is trying to achieve. Start by designing solutions to pressing business problems. Start by learning more about how AI can enable brand new business models and services that you had not even considered. This is the right way to