AI & The Great Reorientation

600 words, 3 minutes. This is an image

In this bite-sized post I’m going to talk about the lag between initial adoption of transformative technology and the increase in productivity it’s supposed to bring. I’m going to talk about the disappointment felt when such technology meets established, dogmatic structures in business (or government), and what executives can do about it. Not all new technologies have the potential to transform business but those that do demand special care, because they are a pill that you swallow not a topical cream.

Over the next few years a whole range these transformative technologies will move from niche to mainstream. Many of them have already begun that journey. I’m going to pick on just one, Artificial Intelligence. I’ve chosen AI because it covers a broad class of capabilities the first of which (Machine Learning) is already being deployed successfully in products and services.

“The future is already here – it’s just not evenly distributed.” - William Gibson.

AI/ML is coming of age. However it will be decades before society adapts fully and reaps maximum benefit from it. Implementation always lags behind innovation. Reorientation trails further still. Don’t believe me? Look at retail banking. The first UK ATM appeared in 1967, online banking in 1997. Only in 2017 do we see banks that are totally and utterly structured around online, electronic, mobile service delivery. In the UK I’m talking about Monzo, Atom, and Starling.

It’s a pattern we’ve seen before with the introduction of steam power, electrification of factories, and the computerised office. Simply introducing technology to an old pattern of working does not supercharge productivity. It is for this reason that I’m sceptical that “old” retail banks will attract new generations of customers. The old banks will add new technology, but I doubt they will allow themselves to be completely transformed by it.

It will be no different for AI/ML. The businesses which benefit most from it will be those who reorientate their entire operation around it. Knocking a few holes in walls and slotting in some technology is a start, but it isn’t going to be enough in the long term. Retail banking has been lucky until now, the industry had already consolidated on a handful of providers, it was heavily regulated. Automating the most popular functions of a bank cashier in 1967 provided convenience and cost savings, but it didn’t transform banking. Venture Capital investors know it. The challenger banks know it. You know it.

Martins bank whose ATM you see being fitted above, was acquired by Barclays. Martins was famed for it’s early adoption of technology. It achieved an impressive list of firsts including mobile branches, a drive-through bank, computerised current-accounts, and the first cash-machine outside London. In spite of all that new technology, it was still a bank, structured and operated like any other. As such it was never going to threaten larger high street banks in a meaningful way. Those larger banks may not be so lucky this time, because the challengers are banks built around technology rather than technology built around a bank.

Machine Learning has arrived and will be followed by other forms of Artificial Intelligence with the power to transform your business. Consider whether you should be putting them on a patch of skin like a cream, or swallowing them whole like a pill.

Buying technology requires money.

Implementing it requires skill.

Reorientating your whole business around it requires courage.

Which of these commodities is in the shortest supply?

Nick Hutton

Engineer, Investor, Founder, Product Manager

London, England