Automation will drive the Third Industrial Revolution. However, this revolution will not actually be industrial in nature; rather it will be a service revolution in the workplace. Automation will change not only who does the work but how we solve problems.

The revolution has already started and will reach full force in just a few years—86 percent of companies say they will hit the breaking point by 2020 when they will require greater automation just to keep up with the pace of work.

There are three areas where enterprises need to prepare now for automation’s impact: our people, processes and licensing models. All of these will change on a level the likes of which we have not seen since virtualization flipped data centers on their heads.

Not Binary: Automation and job creation

We’re all wondering how life and work will change as machines do more of the tasks that we’ve handled ourselves up to this point. There’s this assumption that it’s going to be people or robots, all or nothing. But it’s not binary. It’s more nuanced than that. Forrester sees that through 2027, automation will create 14.9 million new jobs that wouldn’t exist at all otherwise. What automation will really do for our jobs is make us more productive and happier.

Most of us look at a job we’ve had and can say there are portions of it that we truly enjoy. If we only had to do the parts of the job we like, it might even qualify as a hobby. On the other side, there are parts of the job that we only put up with because we are being paid. If we could apply greater automation to this portion of our jobs, we could create an entirely new level of worker satisfaction. It’s estimated that about 60 percent of occupations could have 30 percent or more of their activities automated with technology that already exists today.

Before intelligent automation, machines were built and deployed to support people doing the work. Now, machines will do the work and make decisions allowing people to maintain, manage and supervise the technology. Recurring, rule-driven business tasks and processes that are high volume, span multiple systems, pull together data from various sources or involve data entry are certain candidates for automation.

Just look at this example from a recent McKinsey report: Take mortgage origination. We estimate automation could cut the current process time in the United States from an average 37 days to less than 1, which not only cuts costs but eliminates errors, reduces defaults, raises customer satisfaction, and lowers drop-out rates.

Software automation will allow workers to complete tasks more quickly, with fewer errors and in some cases more safely. And that productivity creates growth, which creates new kinds of work. It is a virtuous cycle.

Executives stand to gain back two workdays a week that they spend on manual administrative tasks. For people whose jobs are primarily administrative, we can expect the bulk of their duties will be automated. These workers will be the frontrunners to be redeployed as managers of the automation. They will acquire new skillsets to diagnose if the bots are running correctly, doing the most impactful tasks and achieving success.

The jobs that bots leave for us will be those that require knowledge and thought. Dull, repetitive tasks will become obsolete, and critical thinking will be in demand. Traits such as communication, problem solving and strategic decision-making will become more valuable than ever. Foreseeably, our jobs will require more skills but will be more rewarding.

Education needs to realign to developing those skills. Never has it been more important for worker education to be continuous. The questions become: Who will foot the bill for educating and retraining workers? How will curriculum in colleges and vocational schools adapt to this revolution? It will likely take a combination of companies and public institutions working together to reform education as automation gains a stronger foothold in businesses.

Process Considerations for Automation in the Workplace

As a percentage of our work shifts to bots, our roles and processes must change. New job groups and rules need to be created, and we need to consider where we will source the people for these roles. Will they come from operations, administrative roles or somewhere else?

Before virtualization came into the data center, there were software roles and infrastructure roles. The infrastructure workers handled the physical side of the data center. They pulled in hardware to the network, and handled cooling and electricity. The software workers didn’t care about that. Suddenly, the infrastructure is software and everything had to change. The infrastructure workers had to learn software or the software workers had to learn infrastructure. A new role emerged: infrastructure developer.

A similar transition will happen as bots are increasingly used to automate business processes.

Beyond our roles in the business process, the checks and balances we’re accustomed to with humans need to be reinvented. In general, we understand what is needed to hold people accountable for their decisions. But what about bots? Bots are not subject to the same constraints as humans.

Our processes for training and managing bots need to keep up. Looking at this simplistically: Who will create the rules the bots must learn? How will we ensure compliance? Will each bot do one job forever or will they get more work over time? How will we plan for retirement of a bot?

The impact of intelligent automation on business processes sparks more questions than answers so far.

But, we should not just look at automation as a means to speed business processes or run processes 24x7. Certainly, bots don’t have work hours. They can work faster. That’s all great.

However, if the only reason to initiate intelligent automation is to codify our repetitive work, then we’re missing the bigger picture. We need to ask: How can we pair a bot with a human to solve something that was impossible before? That’s when the true revolution will happen.

Licensing Called into Question

We’re so focused on what can be done and where we’ll redeploy people that we’re possibly overlooking the disruption that intelligent automation will bring to contract and licensing models.

Many large companies are already exploring the opportunities to apply machine learning to the execution of simple to moderately complex business decisions. Data flows through these bots down to a series of software systems, and a decision is presented, made and recorded in a software system of record. When we plug a bot into where a person used to be, legacy software interacts with a bot instead of a person.

The industry will need to consider how do you license for the flow of data from licensed systems to other systems that use the data but don’t necessarily use the functionality of the data-generating software.

Historically, there have been similar contract issues in most major technology transitions, such as virtualization on the hosting business. This required rethinking key software contract terms and conditions to account for a new way to monetize the work. No one wanted to reopen those contracts prematurely because so much effort went into negotiating them in the first place, but it was necessary.

The industry has just scratched the surface on how using legacy software with bots should be valued and priced. Companies and vendors need to tackle this issue sooner than later because a licensing perfect storm is on the horizon and most companies can’t afford the potential liabilities for software license costs.

The Third Industrial Revolution is more than a redistribution of unskilled jobs to other sectors, it is a paradigm shift that will impact workers in every industry. We need to prepare our people, processes and contracts for the inevitability of greater automation in the enterprise.

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