We’ve been out and about a lot this month, chatting with teams across retail, grocery, and third-party logistics.
And if there’s one thing we’ve learned? Everyone’s tackling the same big challenges… just in very different ways.
So, here’s a question for you: Who actually drives innovation in your business? Is it someone with “Continuous Improvement” in their job title (and a set of KPIs to match)? Or a Head of Innovation with a mandate to shake things up? Or is it simply whoever shouts loudest in the next project meeting?
It’s an interesting area particularly because, as people keep telling us, keeping up with tech is hard. Even the experts are scrambling to stay ahead. We like to think this newsletter helps, at least a little, but if there’s something you’d love us to cover (or something you’ve been quietly researching in between meetings), just give us a nudge.
Phil, CEO
AI in Business
Let’s be honest: there’s no shortage of AI hype, but turning big promises into day-to-day results? That’s where most companies are still stuck. Gartner’s latest research states that only 23% of supply chain organisations actually have an AI strategy in place. The rest? Still figuring it out. (6 mins)
For those making progress, the focus is shifting fast, from isolated experiments to real business impact. Capgemini’s new report shows how companies are moving beyond chatbots and pilots to full-blown operational change. One specific finding that stood out for us: AI is, “delivering cost savings of 26–31% across supply chain and procurement, finance and accounting, and customer and people operations.” (7 mins)
There’s a human side to all of this. One of the most interesting reads this month is from VentureBeat: it highlights how empathy is often missing in AI rollouts. Their argument? The real barrier isn’t the tech: it’s how leaders communicate change and manage fear. If you’re rolling out AI, skip the buzzwords and talk to people like… well, people. (5 mins)
On the infrastructure side, there’s a growing conversation around AI’s environmental footprint, and the importance of ESG factors in supply chain decisions makes this an important topic. Here’s the thing: With AI workloads skyrocketing, data centres are coming under pressure, both in terms of capacity and carbon emissions. Two reads worth your time: one from Supply Chain Digital on the strain data centres are under, and another from Quartz on how AI chip demand is driving energy use through the roof. (5-6 mins each)
And if you’re wondering how much energy AI actually uses… Wired’s deep dive highlights the uncomfortable truth that most AI companies aren’t saying.
There’s a lot of guesswork, but not much hard data. (7 mins)
There’s some hope though. A new PwC, Microsoft, and Oxford University study poses a provocative question: Could AI eventually offset its own energy use by driving broader efficiencies? Too early to tell, but it’s a conversation that’s gaining momentum. (8 mins)
AI Everywhere
AI keeps finding new corners of life to reshape.
First up: cats. Yes, really. Rabo has developed a project that uses AI- powered sensors to detect stress in pets. The thinking? Spotting early signs of feline anxiety could help owners intervene before bigger health issues develop. It’s another reminder that AI isn’t just about boardrooms and data centres, it’s showing up in pet care too. (3 mins)
Meanwhile in Brazil, a new pilot called Dwallet is testing how people can take more control over their own financial data. Users get to decide exactly which apps or services can access their data and when, part of a bigger global trend toward giving consumers more power over their personal digital footprint. (6 mins)
On the psychology front, a new study is asking: can AI detect empathy? The answer seems to be “kind of.” Algorithms are getting better at picking up emotional cues from language, but the research also shows how often humans get it wrong. If you’ve ever misread the tone of an email, you’ll relate. (6 mins)
In the world of neuroscience, Australian researchers have developed a new brain-computer interface that lets AI decode actual words from brain signals. It’s early days, but the hope is this could help people who’ve lost the ability to speak. Naturally, it also raises fresh ethical questions about privacy and thought-to-text tech. (4 mins)
And finally, something a bit more playful: Historic Mentor, a new edtech tool, lets you have AI-powered conversations with historical figures; from Cleopatra to Einstein. It’s part classroom tool, part entertainment, and a glimpse of how generative AI is reshaping education and storytelling. (5 mins)
About Predyktable
Off the back of all the conversations we’ve been having, we’ve been busy adding new capabilities to the platform, making it easier for teams to make better, faster decisions and tell clearer, more confident stories (whether that’s in a corridor chat or a high-stakes QBR).
You can now track performance across multiple sites, so if you’re managing a network of DCs or warehouses, you’ll get a single view built from task-level data right up to estate-wide performance.
We’ve also beefed up our budgeting tools. Now you can see exactly how your labour spend is stacking up against SLAs, targets, or any other metric that matters to you.
But for us, explainability isn’t just about the numbers. It’s about showing the why behind performance. What drove the results? What changed? Who moved where and why?
From visual tools like Sankey diagrams, which highlight how team movements can help reduce agency use, to natural language queries that let you simply ask (in plain English) “Why does this graph look this way?” All without needing a data science degree.
If you fancy seeing it in action, just give us a shout, we’re always up for showing and learning.
Team Predyktable