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About 35% of current jobs in the UK are at high risk of computerisation over the following 20 years, according to a study by researchers at Oxford University and Deloitte. Go to http://www.bbc.co.uk/news/technology-34066941 and type your job title into the search box below to find out the likelihood that it could be automated within the …
Canada’s economic game plan stuck in the decades-old ‘tangible production economy era’
Jan van Hövell’s KLABU turns shipping containers into community hubs for some of the world’s 120 million displaced people. PSJ just signed on to help.
“The first time we saw it navigate among trees and rough terrain, even under heavy collisions, we knew this was something different.”
In January 2026, Anthropic published an 84-page constitution for Claude, its AI model that’s notable for what it doesn’t do: it doesn’t list rules. Instead, it explains why Claude should behave in certain ways, so the model can reaso…
Organizations today are running what amounts to a continuous stress experiment on their people. Restructuring, digital transformation, remote and hybrid transitions, supply chain reorganisation and the rapid arrival of AI—change has become the permane…
I’ve stopped fighting against my own nature. I draw my best energy from solitude. Forcing myself into places outside my “zone of flourishing” means I waste a lot of time compensating for everything I’m not. Aristotle was right over two thousand years …
Below, Lindy Elkins-Tanton shares five key insights from her new book, Mission Ready: How to Build Teams That Perform Under Pressure.
Lindy is a professor at the University of California, Berkeley, director of the Berkeley Space Sciences Labor…
Last year, Amazon reported spending $26 million on non-attorney consultants to persuade employees not to unionize.
I cut my teeth getting grounded in principles of design thinking when I launched a strategic design MBA during my university teaching years. Design thinking is essentially a problem-solving process that is 50% qualitative research and 50% the application of design principles such as visualizing data and prototyping. In the design thinking world, we are well aware that 80% of the problem-solving process is grounded in making sure you even ask the right question . . . before you go running down the rabbit hole of possible solutions. All great problem-solving starts with identifying the actual problem to solve, which is discovered with really great questions.
That’s why a recent conversation with Jim Szafranski, CEO of Prezi, was affirming. He had learned the same lesson—twice—through an entirely different path. First, as an MIT graduate student in the late 1980s, applying early AI techniques in steel mill production. And again decades later, leading a global presentation platform, Prezi, into the age of generative AI. Both times, the breakthrough came not from better technology, but from asking a better question.
“The closer you are to what the ultimate point of what you’re doing is, the better,” he told me. At the steel mill, that meant shifting focus from machine efficiency to customer delivery timelines. At Prezi, it meant moving away from asking customers where they got stuck in the interface and to asking what they were actually trying to accomplish. The answer surprised Szafranski’s colleagues: “I have a deadline tomorrow. That’s my problem.” It had less to do with how pretty their deck was.
This is what I call the difference between optimizing and orienting. Most organizations are excellent at optimizing. They have dashboards, objectives and key results (OKRs), and retrospectives designed to make existing processes run faster and smoother. But orienting—stepping back to ask whether you’re climbing the right mountain in the first place—is far rarer and much more valuable.
Szafranski explained the research methods Prezi used to find its reframe. Early on, team members conducted granular user interviews about interface friction. That line of questioning was deeply useful for optimization but was limited for transformation. “That can keep you really focused on the trees sometimes, not the forest,” he reflected. The unlock came when they zoomed out to broad surveys asking about people’s goals, not their behaviors. Eventually, they made the question literal: Before users could even enter the product, they had to answer when their presentation was due.
This distinction—between improving your product and solving your customer’s actual problem—has profound implications for how leaders deploy artificial intelligence. The seduction of AI is its capacity for automation. But automation applied to the wrong problem is just elegant misdirection! Szafranski is candid about this risk: “Your job can be much higher level. Step back. Think of your customer, think of the outcome you’re trying to drive and they’re trying to drive.”
In my work as a creativity strategist, I see this pattern constantly. The leaders and organizations that thrive aren’t necessarily the ones with the most sophisticated tools, but rather the ones with the clearest view of purpose. They’ve done the inside-out work of understanding what problem they’re actually in the business of solving, so that every tool, every hire, every investment becomes purposeful rather than reactive.
Szafranski offers a practical heuristic for knowing when you’ve found the right problem: “If you can explain it over a dinner table with someone in your family who doesn’t really know what you do, then you’ve probably found the right problem.” I’d add my own corollary: If you can doodle it, you actually understand it.
The question worth sitting with this week isn’t whether your team is executing well. It’s whether you’re all pointed at the right target in the first place. The most powerful move a leader can make isn’t to hand their team better tools; it’s to help them ask better questions.
