This interactive dinner took place at the Covent Garden Hotel on the 22nd June. It was a dinner for industry leaders from backgrounds as diverse as broadcasters, accountancy firms, architect bodies, and the public sector. The dinner was kindly sponsored by Box and Okta; two companies uniquely well placed to profit from the digital revolution.

Box is about storage: an online drive which combines innovations across fileshare and filestorage technology. Okta is about access management: it combines single sign-on, multifactor authentication, mobile device use. The idea is streamlined password management software.

Guests were asked to think about the following topics:

• Key trends in today’s workforce: how has the digital revolution challenged established corporate structures?
• Ushering in a new era of productivity: what’s driving the rapid evolution of process automation?
• Assessing the outlook over the short to medium term - could AI fundamentally alter business models?
• What are future possible scenarios for the shape and structure of the ideal digital workforce and what new skills will be required for this era of automation?
• How might automation improve internal customer relationships and the internal customer experience more profoundly?

Below are some of the most pertinent thoughts from the discussion.

OFFSET STRATEGY

In the 1950s, President Eisenhower devised an “offset” strategy to help avoid a hot war between the U.S and the U.S.S.R. The theory ran that for the U.S. to make certain there would be no war, they needed to preserve a distinct technical capability over their enemy; in Eisenhower’s case, it meant substantial investment in nuclear weapons. In retrospect, this was judged correct by the military: they have undergone two more “offset” movements since. But the U.S. Military is unusual, for a large organization, to see big innovation investment. Most large companies do not have offset strategies, or top dollar innovation spending. This is frequently to their detriment. The once mighty Kodak Cameras, blindsided by the rise of digital, filed for bankruptcy in 2012. This is just one example of hundreds – redundancy via technology could happen to any player in any industry that does not look forward.

It follows that businesses should all be anxiously peering forward; however, the first major anxiety of the dinner was that frequently, they do not. Tech is too often an afterthought. Many delegates had previously had to rescue ageing and decrepit internal systems in their respective industries – an emphasis on ‘beautiful basics,’ and implementing yesterday’s tech today. Fewer had the luxury of looking forward and investing proactively in tomorrow’s tech services.

Counter-intuitively, this is especially true of highly profitable industries. Despite being able to afford higher investment in innovation, and the best people, these industries have a vested interest in the status quo, and can often be complacent. Implementing new tech, after all, may constitute efficiency savings which actually cut premiums in the meantime. It is very difficult to persuade people that making large investments, and cutting profits, will be necessary to survive.

Generally, therefore, innovation drive for large companies must come from imminent competitive threats. New technologies begin to trespass overtly on the profit areas of an industry: such as Transferwise, or Monzo, or Nutmeg, in the case of banking. Then comes noise, and then movement. Banks, and industries like it, will recruit more people with specific skills that pertain to computing and to cast around for solutions to falling revenue. This reactive rather than proactive approach will kill some of today’s large businesses.

This throws up a further implication. To innovate, every company must become in part a tech company. It may become easier for a large tech company, which has easy access to top programming ability, to move into the technologized version of your field, than it is for you. Honda did not invent the Google Car. Ordnance Survey did not invent the Google Map. Lloyds Bank did not invent Apple Pay. The NHS did not invent IBM’s Watson. Competition for large established businesses may well come from tech companies which believe they can do it better – frequently they can.

This implies that large non-tech companies across industries are at a profoundly greater risk than they are likely to realize, and ought to invest now.

TOMORROW’S WORKERS

The largest operating cost of most businesses is wages. It follows that in a highly competitive environment, this is the easiest place to cut costs. Where humans can be automated, from a balance sheet perspective, they should be.

This is truer for AI than it ever has been for physical automation. Whereas each new piece of hardware requires fresh investment, once a piece of software is built, it can be replicated for free. This means that expensive work could become cheap work – and the people that did that work, unemployed.

Job titles are already disappearing. Radiographers have gone, some bank teller functions, lift operators –  also much of stock trading is done algorithmically. IBM’s Watson, already mentioned, should make a better GP than many current GPs, and probably will – downloading an app is easier than going to the doctor. Driving jobs are very vulnerable; the Google car is not a speculative proposition. It is here, now. Also, jobs you might not expect – some of the more laborious law work is going over to AI. This may constitute a training crisis in the field, as human lawyers will be unable to cut their teeth on such tasks.

Although most current work overtaken by AIs so far is mainly blue-collar work, this does not imply that white-collar work is safe. Indeed, AI learning potential should be unlimited – and there is a much greater incentive for a company to replace someone earning a high wage.

Unemployment could become a problem, then. Only a small percentage of people need to be unemployed to constitute a crisis, and the progress of technology is so rapid that people could become unemployed faster than the capacity of a growing economy to absorb them in new roles. Further, they may not have the skill sets these new roles demand. New and bold political solutions such as the ‘Universal Basic Income’ may be on the table down the line.

Whatever happens to the current workforce, it is worth thinking about how young people should act now to make themselves valuable in the changing economy.

Perhaps the following steps would be useful:

1. Becoming adept at understanding and operating computers. Maybe a level of coding proficiency would help.
2. Becoming adept at those things that computers will find very difficult: communication, talking to people, creativity, lateral thinking.
3. Do not trap yourself into a specific profession that may face redundancy – undergo a rounded, generalist, education, and improvise from there.

These are based on key insights: if every company must become a technology company, that means technology skills will be in extremely high demand for a relatively small supply. If AI could already do some GP work, we can infer that most professions are not safe; rather, a worker is likely to be made redundant at some point so transferable skills and improvisation will be more useful. And perhaps, we will be looking at a more ‘soft skills’ jobs market going forward. Some hotels now have hospitality robots, but these fail to make a hotel feel hospitable. Robot doctors are all well and good, but who would want a robot to tell them they have cancer? Who would want their depression counselling to come from an AI? (The University of Southern California have already built a depression counsellor AI called Ellie). They may try, but customers are unlikely to choose the automation any time soon.

It is also possible that AI could disrupt employment so dramatically that it could change how careers work altogether. One means of increasing labour cost efficiency might be increased use of freelancers – the oft-maligned ‘uber’ model. There was some disagreement about this: is this technological change at all, or is this social change dressed in a tech outfit? Besides, much of the motivation for millennials was argued to be fulfilment; perhaps this is why many employers make a conscious bid on a ‘work culture’ basis for interest among millennials. If millennials do want a more varied career, and they are not just responding to a capricious jobs market, they are likely to want the purpose and direction that comes with a full-time role. Many organisations are ultimately human enterprises, and there will be a sluggishness to make staff redundant and implement software because people prefer human beings. The most important factor in choosing to hire somebody was considered to be whether they fit culturally; AIs do not do this.

THE FUTURE OF WORK

People tend to overestimate the short-term abilities of AI; and to underestimate the long-term changes it will bring. Once a person understands that AI could do anything a human could do, and better; it can be very easy to get carried away in employment doomsday-guessing, and lose oneself in big-idea contemplation about the robot future that awaits. This is premature. But change is happening, and has happened. Previous technological change, delegates observe, has seemed to ‘creep up’ on them. There was no big day one announcement for the birth of the internet, its presence has grown incrementally – but access now seems as basic and tangible an amenity as clean water supply. A phonebook and a VHS tape seem bizarre, antiquated devices – the preserve of museums. Much work will change, and many of today’s large companies will fail to improvise fast enough to survive.