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Announcing Pearson's acquisition of Faethm 🚀

Retain, retrain and redeploy

Why does automation matter to the future of work?

Economics tells us that automation is what drives increased productivity (and therefore economic growth). We can improve productivity slightly by making processes smoother and more efficient, but ever since the beginning of the industrial revolution we’ve mostly relied on the invention of new machines to drive economic growth, by letting us produce more, in less time, with less human labour. 


You have to pay humans to labour; machines are generally cheaper, because once you’ve made the investment they have very low running costs. 

The problem is, since the beginning of the industrial revolution, this has also meant job losses for people, when the work they did became possible to do by machine. The earliest/most famous victims of this were the Luddites – handloom weavers put out of work by the new industrial looms. They broke machinery and burned down factories as a protest against the new system. 

Ever since, there’s been tension between workers who rely on selling their labour and skills, and employers who are invested in buying or inventing machines to replace those skills and make the labour obsolete. In theory, these productivity increases should benefit those workers as much as everyone else – the goods they need to buy will get cheaper because they’re easier to produce, and will be more in demand, and the workers who aren’t made redundant can argue for higher wages on the basis that by partnering with the machine, their work now produces much more profit. 


How can AI replace human skills? 

AI doesn’t automate whole jobs, it automates tasks:  It’s about tasks and skills, not people.

People can’t be made obsolete, but some of their skills can, when the tasks involved in their jobs become more efficiently done by machines. Everyone in the workforce now is likely to find that some elements of their jobs disappear as it becomes easier to automate them.  Luckily, these also tend to be the more routine and less interesting elements of the role.  

Faethm’s system assumes that all tasks can either be automated or augmented. Automation means they can be done entirely by machine; tasks that can be augmented are ones where humans will still be needed, but that can be made faster or better by including machines as well.

The speed at which this change is happening is what has worried (or excited!) people. Of course, by getting ahead of competitors and adopting technology faster, firms can also improve their productivity and make a lot more money – though they will need to make changes to their workforce at the same time. This could involve hiring people with different skills or reskilling the people they already employ. This is where Faethm can step in to advise. 

“The skill set of our workforce is constantly changing. As an industry, we battle for top market talent to try and fill that gap.  At Zurich, we don’t believe it has to be this way. Whilst we can’t ignore the benefits that automation brings, it’s important to retain, nurture and educate our teams. This is a clear opportunity, not a threat to our employees. It’s crucial that we factor the future skills requirements for the business into the process now. If we know what’s coming, we can start transitioning existing employees into new careers today.”
John Keppel, COO, Zurich UK - Information Age Future of Work

A renewable NOT replaceable workforce!

We take the position that it is always possible to create new work and new industries that will employ enough people. Our contribution is to use AI to predict the opportunities for work created by new technologies. We’re aiming to smooth over that period of uncertainty where people and businesses are adapting to a new working world. By figuring out which skills can be adapted to new roles, we can help people transition from jobs that are becoming obsolete to ones where there is potential for growth.

If you deploy a particular technology into a particular context of work, you affect the supply and demand for the skills and tasks in that job.  Some tasks are automated, some augmented and some tasks are added.  When you automate enough tasks in a job, that role becomes redundant.  When you add a lot of tasks, you create the job. By looking at the attributes of a technology, and how it affects individual tasks, we can build a model of what's going to happen, when any technology is deployed into any company, anywhere.  So that in turn helps companies to ask:

  • Who do we need in the future?
  • What skills do they need?
  • How do we train them?
  • Who do we want to hire?
  • Who do we need to let go?
  • When should we let people?
  • How can we train them into other jobs in the community?
  • Which technology is going to be most effective for us?
  • Which should we prioritise?
  • What should our technology roadmap look like?  
  • How much should we spend on technology?
  • Which technology is really going to move the needle for our organisation? 

We can also look across an industry, to see what the impact of technology might be across a whole population of people.

“My team is a perfect example of how to nurture existing employees for the future. There are many preconceived ideas about implementing automated processes into a business and how these roles must be carried out by tech specialists. In reality, the best people to do this effectively have worked within the function that you’re looking to automate as they really understand the process.”
Alastair Robertson, Head of Continuous Improvement and Automation, Zurich UK - Information Age Future of Work

The challenge is how we move people from what they’re currently doing, to the jobs of the future, so they are able to participate and we don’t lose people as part of that transition process.  It’s cheaper to retrain and redeploy, than to make people redundant and rehire.  Giving employees the skills they need to be successful in the economy, because we’re also part of that economy.

Media and publicity inquiries:

Please contact marketing@faethm.ai

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