Three new jobs to train for in an AI world

AIs will soon be taking over a lot of jobs and the roles of people will be changing. So, which new jobs should we be training for?

I’ve taught hundreds of MBAs all over the world and they want to know how they can take advantage of the AI revolution. The best way is to learn how to compliment AIs, how to do the things that AIs will not be able to do soon or never at all.

I’ve already written about Four things that AIs can’t do better than humans. How neural net AIs are limited by how they are trained with giant datasets, by the techniques they use to find patterns in those datasets and by the ways that those patterns can be employed.

But human Intuition draws on our many past experiences, which provide much wider and deeper training data than AIs have access to. And human Creativity benefits from past experiences which might seem totally unrelated to the current problem.

Also, we humans can use Critical Thinking to check why something is as it is. We check things as a reflex, without being programmed to.

Lastly, we all have our own emotional experiences to draw on using Empathy. We can give advice when we recognise problems and having “been there and done that” also generates trust and confidence in those we give advice to.

So, which jobs will make use of these very human abilities and make us more valuable in an AI world? Here are three jobs which compliment AIs and a few tips for getting good at them.

Job 1: Finding new AI capabilities to glue onto your firm

All firms are going to be using AI capabilities. And this job is about finding and adding new AI capabilities to your business processes. Or even breaking up your old business model, reengineering it and then pasting it back together.

For example, if your firm makes physical products then you could add Wi-Fi to them to make them Internet Of Things products. Next, use the Wi-Fi connection to add some AI capabilities. Simple voice controls using Amazon’s Alexa would be a good start.

But make it count, prioritise AI capabilities only where they make a difference.

For example, voice control is a priority where users need hands-free control, or where reaching for a remote control is inconvenient. But maybe your customers would prefer to prioritise price reductions or reliability? As usual, start with listening to your customers.

Finding new ways to apply AI technologies and convincing your colleagues requires an understanding of both AI capabilities and of your business. This is a bridging job, what Mckinsey call an “Analytics Translator” – the bridge between data science and everything else in the firm.

Here, your powers of Intuition will feed off a wide understanding of your business context, and your Creativity will serendipitously steal from your seemingly unrelated past experiences. Experiences in and out of your work life.

You can develop those powers by understanding more of your business, this is your training data. Talk to colleagues, customers and suppliers. Try job swapping, be a customer for a day and hang around with your suppliers. Develop your personal networks and try to “stand in their shoes and look through their eyes”.

Aim to understand not only your contacts’ points of view but how they think and what they value. For example, what’s the first reaction of a B2B customer when confronted with a product upgrade? Would they be pleased, or would they think “higher prices and now I need to retrain my staff”?

What sort of upgrade would they design if they were in charge? And turn it around, what would they really hate and why? How can you stay clear of that?

Job 2: Checking that your AI solution fits, before you fasten it in place

This job is about carefully questioning the “how” as well as the “what” of designing and implementing AI solutions in your business.

AI and other digital data technologies will revolutionise most jobs and virtually every industry. But there is no point in improving some part of your firm if the reason for improving it is going to go away.

The tricky thing is that AI technologies are revolutionary at every level of business. Starting at the top with (a) business processes; then (b) the business models which support them; then below that, (c) the industry sectors which are the niches for these business models; and finally, down to (d) the new business ecosystems which are transforming industry sectors. Changing any one level means changing all the levels above it.

So, yes, you can improve the business processes in an assembly line. But you can also reengineer your business model to make your current assembly line obsolete.

Here’s another example. What if you change from selling standard products – chosen by one-time customers – to renting products to subscription customers, which are suggested by an algorithm.  Business models trump business processes. Change the business model and you must change all the processes which enact it.

Equally, you can link up with new partners to acquire new capabilities and turn your supply chains into a business ecosystem. For example, you can get new AI capabilities from partners like Amazon’s Alexa, Apple’s Siri, Microsoft’s Cortana, IBM’s Watson and Google’s Google Assistant.

There are lots of potential partners with capabilities to draw on. Like cloud infrastructure (MS Azure, AWS), saas software applications (Zoho), drop shipping (AliExpress), drop services (Fiverr, People Per Hour), even data (Kantar, Experian, Equifax) and many more.

But this opens the door to competition between business ecosystems, and it invites competition from outside your industry sector. Look how Tesco used a deep understanding of its retail customers to enter the banking sector.

The problem is that powerful capabilities like AI alter the sensitive dependencies between (a) the business processes which use this capability, (b) your business model, (c) your industrial sector and (d) the ecosystem partners that you work with. Change one part and all the other parts might need to change.

For example, if you use AI and your current customer data to understand a much more lucrative and targeted set of their needs, then you might want to engage a whole group of new partners to help you to service these needs.

Or if you change your business model from selling products to renting IoT products then you might want to redesign your products for refurbishment and for recording the user experience. Which means a lot of new business processes.

So, where do you start? What should you do now? What is a good route map? Here you need to use Critical Thinking to help you check and evaluate how your ideas will actually work.

Critical Thinking is thinking about your thinking, always self-checking as a reflex and with no need for a prompt. Critical Thinking evaluates the thinking process, judges it and makes useful recommendations to improve it. You can exercise and develop your powers of Critical Thinking.

Choosing how to use AI technologies is complicated. Checking “how” you choose the solution and “how” you design the implementation is just as important as “what” you choose.

Job 3: Making AI capabilities sustainable, making them stick

This job is about helping to nurture and grow the use of AI capabilities in your business. Not just doing a successful pilot project and not just using AI once. It is about making innovation the “new normal”.

For example, we’ve all worked in a firm that implements new software that nobody likes or uses, because nobody was consulted to see if it is actually useful. Mentioning no names, but I’ve seen this happen lots of times with software, machines, business process and quality procedures.

Before I was an academic, I ran business process change management projects for Motorola, Coca-Cola, Danone and other firms. I learnt very quickly that users need to be part of the design project, not just the implementation project. The people in a business process have the best ideas, they will spot problems a million miles off and they must know that they are being listened to.

Users can be customers or internal staff; they will either be with you or against you. And the best way to get them on your side is to use empathy. 

Empathy helps you to find the right people and to connect with them. It helps you to ask the right questions in the right way, and to put people at ease so they will give useful answers.

Empathy gets you more help than just information. You need people to be project advocates not just information sources. 

Successful change management projects need to generate trust, especially with revolutionary and emotive change drivers like AI. Your empathy and an emotional connection will help you to generate that trust.

Empathy helps you to find the specific “burning platform” that will drive change and stimulate consensus in your firm. Something everyone can support as a unifying change driver. For example, it could be saving the company or removing specific dangers and annoyances. Then, when you deliver on that first project, you can use news of this first success to keep the momentum going and as a base for new projects.

Daugherty and Wilson of Accenture call these “Sustaining” jobs. Jobs that keep AI systems functioning properly after they are first set up and start working.

AI systems can continuously optimise and change pricing, ordering and other characteristics of business processes in real-time. So, “sustaining” jobs include keeping things up to date as well as dealing with the implications of the initial AI project. For example, up to date trainings datasets, solving ethical problems and resolving data privacy implications.

You can develop your powers of Empathy by reflecting on what it will really feel like to be a user of your new AI system. Ask lots of questions and think deeply about what it would feel like to change how you work. What are the pain points and irritations? What are the concerns as well as the benefits? What do users and customers really value and how does this AI project personally help them to get that?

Don’t forget that Empathy is the ability to understand and share the feelings others. It is highly subjective, so ask a lot of people and be famous for asking.

Human Intuition, Creativity, Critical Thinking and Empathy intermingle in these jobs just as they do in life. But if you can feed these abilities then you will help your firm to take advantage of AI technology and help your career at the same time.

Duncan is a lecturer at Nottingham University Business School. He also advises organisations on creating value with digital data and he writes in his own blog.

Connect with me on LinkedIn at www.linkedin.com/in/duncan-r-shaw-7717538.