Kathy Gibson is at Gartner Symposium in Cape Town – Artificial intelligence (AI) will drive new ways of working, and we will see the emergence of a whole new AI-enabled workforce.
There will inevitably be job losses as this happens, but the experts tell us that AI will eventually result in more – albeit different – jobs.
IT and business leaders need to plan now for transition, according to Helen Poitevin, vice-president analyst at Gartner.
Already, many people are engaged with AI technologies on a daily basis, she points out. These include driving route suggestions, predictive text, virtual assistants and facial recognition in photographs.
“It is a reality of today – not necessarily just a projection on tomorrow.”
However, AI is set to evolve further and impact the world of work, Poitevin adds.
It’s been six years since the first studies indicated that billions of jobs would be lost to AI. Already, millions of workers are in jobs that can readily be automated.
“However frightening this might look, it can only study existing jobs – jobs that we have today. And we know that new jobs are always emerging.”
Gartner believes that in 2020 we will reach the turning point where AI will create more jobs than it destroys.
On the one hand, it is being used to automate existing jobs, so those tasks disappear and fewer people are required for that work.
“But AI is not used just to automate. Many companies use AI to deliver new services, add new value and create new job opportunities.”
And this is the true value of AI, Poitevin says – not to automate old jobs but to create new business.
“The idea that the jobs are going away is somewhat laughable.”
A massive 77% of people think that AI will decrease jobs – but only 16% report actual job decreases. Only 23% believe AI will drive new jobs growth, and 26% of people report job increases.
People’s attitudes to technology – and how they are changing – have to be taken into account.
More than half of survey respondents say they prefer to have AI as an assistant on demand; 32% want it as a proactive assistant; only 11% want AI as a co-worker; and just 9% see AI as having a place as the manager. Fifteen percent of people don’t want AI in any of those roles.
The younger people are, the more likely they are to accept AI as a boss or co-worker. Young people are less likely to want to ask for help from AI, expecting predictive responses rather.
Changing attitudes as children grow up and enter the workforce will drive more acceptance, says Poitevin.
Gartner predicts four different scenarios for the future of work, on a scale where machines move from weak or narrow capabilities to strong or broad capabilities; and where people reject the machines to where they embrace them.
Minibot proliferation
This involves many machines with limited capabilities – and people who like them.
In coming years, these minibots will accompany people all the time, measuring, monitoring and helping them through the day.
For the enterprise, this is easier said than done. As we introduce more and more little pieces that do limited things, it increases complexity.
There will be a need for more people doing bot support, and there will be a need for clever people who understand the complexity, and can do something with it.
Companies will have to have a clear focus on talent, enterprise purpose, bot support and security.
“In this scenario where machines have limited capabilities, there will be a lot of work for IT. But that work will change.
“So leaders in the workplace need to focus on who your people are, and knowing them. AI is an opportunity here: you can use AI technologies to mine data about where people are actually working, collaboration tools, project management tools, even measuring deliverables.
“You can mine that information to map out skills to understand which jobs will be most impacted by automation.”
Workers in roles that involve high predictability and low social-creative skills are most at risk, with low-predictability and high social-creative skills are associated with jobs that are least at risk – although their roles will change.
Enterprises can also use AI in internal talent marketplaces, applying agile thinking to move the thinking from jobs to work. “You are not hiring people for a job anymore, you are tapping into the people in the organisation for the work that needs to be done.”
Bots can’t drive
This is where there are dumb bots, surrounded by disdainful humans.
Poitevin says the attitude that AI will automatically eliminate jobs is real. And this is driving new regulation to restrict and control it.
“When you restrict and control it, humans have to be in the loop for everything.”
This means the enterprise needs to employ bot masters, and focus on areas like governance, risk management and ethics.
Digital is a useful way to guide this conversation, she says. CIOs can initiate a structure conversation around digital ethics.
This means the organisation needs to think through the consequences of actions as much as they can; monitor for unintended consequences; and take responsibility for these consequences. Through this process, it is important to learn and make the next iteration better.
Bots go bad
This is where bots get really smart, and people are afraid of them.
People respond to this by outsmarting the machines., through data, workflow, logic and morality.
“Bots go bad through scenarios none of us want to get into,” she says. The consequences can lead to conflict and even war, so this is not a desirable outcome at all.
I’d rather have a bot do it
This is where powerful bots do things we want them to do, and make our lives easier.
In this scenario, we continue to create a speed, which keeps going up. And competition keeps going up.
It needs to focus on creativity, competition, productivity optimisation and fast deals.
This is the scenario most people have a hard time imagining. This is where technology can really transform who we are, and will really change our lives.”
Digital dexterity is vital to create this scenario, Poitevin says. People have to have the ambition and ability to design and build
Human-centric design will result in technology that people enjoy, that solve real human problems.
“Attitude is important, and design is a way to ensure we get more positive attitudes.”
How to prepare
Leaders can prepare by focusing on people and skills. This means knowing who the people are, building digital dexterity; and using internal talent marketplaces.
The should focus on technology design, particularly in the areas of security, digital ethics and human-centric design.
The citizen is important if technology will be accepted, and people need to participate in the debate.
“We need to shape a future of work that we want.”