5 Considerations for the Forward-Thinking Company

October 19, 2020
Image of man working on a laptop.

The Future of Intelligent Automation and the Humans that Manage It.
It’s been called “a disruption.”

For leaders and business managers, disruptions sound like great investments when they happen in other industries and daunting problems when they occur in your own industry.  

KPMG’s white paper The Rise of Humans 2 is an excellent long-form look at the future of automation, work, and the people who manage automation at work. It takes the temperature of the industry, and we think it’s pretty helpful for anyone thinking about the role of intelligent automation in their organization moving forward.

Here’s some practical advice for intelligent automation (IA) and the people that manage it:

1. Think About AI in the Context of Larger Work Trends

You’re probably already thinking about the role of automation in a broader context of your business: the future of work. As the report points out, we can expect longer working lives, more workforce mobility, and a vibrant gig economy from the future of work.

Skills are becoming more and more volatile, as knowledge workers are becoming more broadly skilled and pursuing lifelong learning.

Companies that are positioned to succeed will think about AI in the context of these larger trends. By anticipating both human and non-human capabilities and limitations, the workforce can transform holistically.

2. Bots Will Disrupt Workforces, not “Jobs”

We’ve all got some amount of dystopian imagination. It’s nice to picture AI doing the work of an entire team in a day, but it’s just as easy to picture being asked to help provide input for a bot that will replace your job in 3 months.

It’s no doubt that the workforce is changing. But it’s best to think about AI as disrupting the workforce itself, not individual jobs.

As AI begins to shape your workforce, it also changes the kind of people that you’re looking to hire and the kind of skills that you need.  

Human skills like creativity, divergent thinking, and novel problem solving will become increasingly important. AI doesn’t replace workers, it replaces skills and tasks. The smart companies of the future will be the ones that can integrate powerful AI Digital Coworkers with creative human coworkers.

3. Shape Your Workforce with AI, Don’t Just Be Shaped by It

There’s a tendency to think about how AI can plug into your existing business structure to make things more effective and efficient. This is certainly a good use of AI, and can provide a huge value proposition for businesses in very specific lower-order ways, but it’s a small benefit in comparison to another way that you can think about AI.

What if automation could change your entire work structure? Instead of simply maximizing the existing structure, what if you allowed automation to change the structure itself?

4. Develop Adaptable Automation Plans

If automation is used properly, it should be able to completely transform the workflows and structures that a business relies on. Also, AI is still rapidly improving. Today’s machine learning is far and away beyond the machine learning of 5 years ago, and undoubtedly pales in comparison with the machine learning of 5 years in the future.

So what’s a business to do?

Some businesses decide to simply focus on the short-term results, ROI, and practicality of automation. Seems reasonable, but it’s also a great way to get left behind.
KPMG’s 2017 workshop revealed that companies utilizing automation often recommended starting small while thinking big. Simply put: you have to start somewhere. You won’t get the runaway results of established automation players on day one, but you’ll also never get to full integration without starting somewhere.

5. Make AI a Holistic Strategy

Companies too quickly turn AI into a stop-gap for convergent problem solving. Instead of thinking about the big picture of the company, they punt the AI question to the IT department where it gains limited reach. At KPMG’s 2017 conference, they found that a lot of companies recommended thinking about AI from a business perspective and governance perspective, not a simple IT perspective.

One of the problems with holistic thinking and problem solving is that it requires business leaders to venture into territory they might be unfamiliar with. But by choosing to delegate the AI disruption question, a business leader has already answered the question by limiting the importance of AI to an IT question instead of a systems and structural question.

See also: 4 things to know about ML - Understanding key automation technologies

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