#7 Tour de France: Trying to win with a penny farthing + 5 things to use Claude.ai for right now

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As the Tour de France hits Stage 12, will breakaway or sprint teams prevail on 203.6km route from Aurillac to Villeneuve-sur-Lot today? I'm breaking with the usual newsletter format to talk about it...

Jonas Vingegaard claimed victory on stage 11, and the race is on to find out which of these front runners will be this year's victor. But as we flick between football, Wimbledon, and Tour de France these sunny July days, one thing is quite certain: Vingegaard, Pogacar, or Evenepoel... if we stuck one of them on a penny farthing they're not going to win. If we put an old Wilson Jack Kramer Autograph in the hands of Djokovic, victory slips away.

Steve Jobs' analogy of the computer as a bicycle for the mind is an apt one when we think about how Generative AI extends human capabilities.

In a 1990 interview, Jobs harkened back to an article that caught his interest as a child about the most efficient creatures in movement.

"The condor won, came in at the top of the list, surpassed everything else, and humans came in about a third of the way down the list," he said...

"...But somebody there had the imagination to test the efficiency of a human riding a bicycle. Human on the bicycle blew away the condor, all the way off the top of the list. And it made a really big impression on me, that we humans are tool builders, and that we can fashion tools that amplify these inherent abilities that we have to spectacular magnitudes."

"And so for me a computer has always been a bicycle of the mind, something that that takes us far beyond our inherent abilities." - Steve Jobs, 1990

GenAI: Our New Racing Bike

Like the customised version of the HEAD Graphene 360+ Speed Pro that Djokovic wields, or like the custom-made Colnago V4Rs bike Poga?ar's masterfully leverages right now, technology extends our human capabilities. It does not, however, plug and play. You and I won't be winning the Tour de France no matter how awesome our bike is.

When GenAI gives us access to the quantity of data and information no human or even group of humans could ever have a hope of accessing, the question is not whether this racing bike replaces the human, but how do we humans best go about riding it.

The fact is, an incredible bike is not enough: we need the skills, the training, and the team in order to ride it effectively; we need to know what route to take on this stage of the Tour de France, we need to map our environments, chart the path, be aware of the wind patterns, and make plans for how to change gears, pace ourselves, and strategise to win. The bike doesn't win for us.

Humans have, since the beginning of time, fashioned tools that extend our capabilities. From the earliest stone axes that allowed us to hunt more effectively to the complex computers that power our world today, our ability to use tools has been a cornerstone of our success. The adjustment period - learning to wield them expertly - that's where new winners and losers are made, where heroes of adaptation emerge.

So it's not the strongest or most intelligent of the species who wins out, but since time immemorial, the most adaptive to change.

So far, we're not wielding our new tools very well in business at all.

We know AI has the potential to boost labour productivity by 40% + by 2035. Those businesses who are using it effectively are seeing revenue increases to the tune of 2.4x those who are not using it effectively, and McKinsey suggests effective implementation will generate up to 30% revenue increase in the banking and asset management sectors within the next five years. [McKinsey Global Institute: The State of AI in 2023: Generative AI's breakout year]

However, the reality is that businesses are NOT seeing the expected ROI on their GenAI efforts. Why?

Because businesses are treating GenAI like a plug & play, not paying enough attention to the humans who use it:

“Over 90% of large scale AI-focused transformation projects have failed to return significant gains, the most often-cited reason being insufficient attention paid to the operational side: skills, communication, culture, engagement.” - MIT Sloan

“Winning with AI found that only 10% of organizations achieve significant financial benefits with AI. The main reasons for failure include lack of skills and poor communication between technical teams and business units." - MIT

Don't know where to start?

No matter where you sit, the best starting point is a single step.

Many of our clients have started with an hour lunch & learn, if they like it and find themselves excited about the idea of becoming over 40% more productive, they can progress to an AI audit. And if they like that, we'll head into a Race Plan that moves the whole team from Point A (fear / misunderstanding / reluctance) to Point B (seamless integration, improved employee engagement and satisfaction, huge productivity gains, increased profitability) over six to 12 months.

To finish up, here are some fun examples of what AI could be helping you with today:

It's nearly the weekend - have a great one!