Your employees want to work with AI. Here’s how to make it happen.
Talk of AI has been around since the 1970s but, over the last 12 months, "Strong AI" or Artificial General Intelligence, which can do more human-like tasks, is really starting to change the conversation on what it means to the workforce.
When Accenture recently launched a major piece of research at the World Economic Forum—surveying 14,000 employees and 1,200 executives—I was very surprised to read that business leaders massively underestimate workers’ eagerness to work with AI. Despite the doom and gloom of ‘automation anxiety’ touted by the media, this survey found most workers are actually impatient about AI coming in to help them do their jobs more efficiently, take over repetitive and mundane tasks and free them up to do higher order activities.
And they’re right.
Around the world, leading companies are using AI to make employees’ work more interesting, while also increasing the value they are delivering to the business. Often this involves using digital technologies to create innovative customer experiences that extend the value of workers’ expertise and allow them to focus on truly adding value.
Across the board, AI will reconfigure jobs. Generalists will become specialists. Technologists will become creatives. Operational jobs will become insight-driven roles. In an Adidas SPEEDFACTORY, customised shoes are being completed in mere days by using people and robots working collaboratively in a series of overlapping production steps.
Teach me how to work with AI
Not surprisingly, two-thirds of workers think it’s important to develop their skills to work with intelligent machines.
But, astonishingly, business leaders don’t appear to share this sentiment. A massive 97 percent of business leaders say they will use automation and AI to augment worker capabilities in the next three years. Yet only 3 percent of executives plan to significantly increase investment in skills development programs in the same period.
Houston—we have a problem!
It’s a great example of where, although leaders recognise the “why” of AI, they’ve yet to get their heads around the “how.”
New priorities for people leaders
As intelligent technology meets human ingenuity, people leaders have an exciting opportunity to create their future workforce by:
Scaling up new skilling – If technology is changing every three to six months, your skills development programs need to follow suit. Training is no longer for "high performers." It’s for everyone, and it’s ongoing. Using new tech, like VR and AR, to accelerate the speed and scale of training also helps keep it interesting, allows you to attract new talent and democratises learning across your business. Assess different levels of skills and willingness to learn—and create customised learning paths to cater to the individuals’ needs. And don’t forget the value that humans bring to the equation: Make sure your training programs balance technical, judgement and social skills.
Shift from automating tasks to re-mapping roles – Rather than just assessing tasks that can be done by machines, take a look at what happens to the roles in your organisation as repetitive or simple tasks get automated. Some tasks and activities can be completely taken over by technology. Others can be enhanced by it. Others are uniquely human. Now you can reconfigure jobs to elevate people’s capabilities and use excess capacity as you automate their low-value tasks to perform more creative tasks. For example:
Pivot to a new agile Operating Model – Over the last few years, organisations have looked to centralise, rationalise and standardise capabilities. But, although centralisation has been great for governance and cost reduction, it has also become a bottleneck for speed to market, restricting flexibility and stifling innovation.
The answer is to look to strike a balance between autonomy and standardisation, using: platforms, enterprise controls and shared services to retain efficiency; and autonomy at the team and individual level to free people up to experiment and think freely. You also need to give parts of the business the freedom to try out new ideas. This means actively encouraging experimentation and skilling up employees in Agile and Lean practices.
A prime example of this has been the move from Centres of Excellence (CoEs) to Communities of Practice (CoPs). While CoEs have helped establish governance and standardisation, they are often too tied to a particular technology and can be a draining cost overhead—because you still need to fund them even if there’s no work. Moving to CoPs allows you to transition away from centralised delivery functions to decentralised autonomous teams where experimentation becomes the norm but best practices can still be shared.
Businesses that fully commit to investing in the transition to AI—helping their workforce pivot to work collaboratively with machines—are more likely to survive the coming upheaval across the markets and industries. And, most importantly, they will also have happier employees.
It’s time to make friends with AI and help your employees embrace the change.