Lisa Morgan's Official Site

Strategic Insights and Clickworthy Content Development

Category: RPA

How to Prepare for the Machine-Aided Future

Intelligent automation is going to impact companies and individuals in profound ways, some of which are not yet foreseeable. Unlike traditional automation, which lacks an AI element, intelligent automation will automate more kinds of tasks in an organization, at all levels within an organization.

As history has shown, rote, repetitive tasks are ripe for automation. Machines can do them faster and more accurately than humans 24/7/365 without getting bored, distracted or fatigued.

When AI and automation are combined for intelligent automation, the picture changes dramatically. With AI, automated systems are not just capable of doing things; they’re also capable of making decisions. Unlike manufacturing automation which replaced factory-floor workers with robots, intelligent automation can impact highly-skilled, highly-educated specialists as well as their less-skilled, less-educated counterparts.

Intelligent automation will affect everyone

The non-linear impact of intelligent automation should serve as a wakeup call to everyone in an organization from the C-suite down. Here’s why: If the impact of intelligent automation were linear, then the tasks requiring the least skill and education would be automated first and tasks requiring the most skill and education would be automated last. Business leaders could easily understand the trajectory and plan for it accordingly.

However, intelligent automation is impacting industries in a non-linear fashion. For example, legal AI platform provider LawGeex conducted an experiment that was vetted by professors from Duke University School of Law, Stanford University and an independent attorney to determine which could review contracts more accurately: AI or lawyers. In the experiment, 20 lawyers took an average of 92 minutes to review five non-disclosure agreements (NDAs) in which there were 30 legal issues to spot. The average accuracy rating was 85%. The AI completed the same task in 26 seconds with a 94% accuracy level. Similar results were achieved in a study conducted by researchers at the University of California, San Francisco (UCSF). That experiment involved board-certified echocardiographers. In both cases, AI was better than trained experts at pattern recognition.

Interestingly, most jobs involve some rote, repetitive tasks and pattern recognition. CEOs may consider themselves exempt from intelligent automation but Jack Ma, billionaire founder and CEO of ecommerce platform Alibaba disagrees. “AI remembers better than you, it counts faster than you, and it won’t be angry with competitors.”

What the C-Suite Should Consider

Intelligent automation isn’t something that will only affect other people. It will affect you directly and indirectly. How you handle the intelligently automated future will matter to your career and the health of your organization.

You can approach the matter tactically if you choose. If you take this path, you’ll probably set a goal of using automation to reduce the workforce by XX%.

A strategic approach considers the bigger picture, including the potential competitive effects, the economic impact of a divided labor workforce, what “optimized” business processes might look like, and the ramifications for human capital (e.g., job reassignment, new roles, reimagined roles, upskilling).

The latter approach is more constructive because work automation is not an end it itself. The reason business leaders need to think about intelligent automation now is underscored by a recent McKinsey study. It suggested that 30% of the tasks performed in 6 out of 10 jobs could be automated today.

Tomorrow, there will be even more opportunities for intelligent automation as the technology advances, so business leaders should consider its potential impacts on their organizations.

For argument’s sake, if 30% of every job in your organization could be automated today, what tasks do you consider ripe for automation? If those tasks were automated, how would it affect the organization’s structure, operations and value proposition? How would intelligent automation impact specific roles and departments? How might you lead the workforce differently and how might your expectations of the workforce change? What ongoing training are you prepared to provide so your workforce can adapt as more types of tasks are automated?

Granted, business leaders have little spare time to ponder what-if questions, but these aren’t what-if questions, they’re what-when questions. You can either anticipate the impact, observe and adjust or ignore the trend and react after the fact.

The latter strategy didn’t work so well for brick-and-mortar retailers when the ecommerce tidal wave hit…

What Managers Should Consider

The C-suite should set the tone for what the intelligently automated future looks like for the company and its people. Your job will be to manage the day-to-day aspects of the transition.

As a manager, you’re constantly dealing with people issues. In this case, some people will regard automation as a threat even if the C-suite is approaching it responsibly and with compassion. Others will naturally evolve as the people-machine partnership evolves.

The question for managers is how might automation impact their teams? How might the division of labor shift? What parts of which jobs do you think are ripe for automation? If those tasks were automated, how would peoples’ roles change? How would your group change? Likely, new roles would be created, but what would they be? What sort of training would your people need to succeed in their new positions?

You likely haven’t taken the time to ponder these and related questions, perhaps because they haven’t occurred to you yet. As a team leader, you owe it to yourself and your team to think about how the various scenarios might play out, as well as the recommendations you’d have for your people and the C-suite.

What Employees Should Consider

Everyone should consider how automation might affect their jobs, including managers and members of the C-suite, because everyone will be impacted by it somehow.

In this case, think about your current position and allow yourself to imagine what part of your job could be automated. Start with the boring routine stuff you do over and over, the kinds of things you wish you didn’t have to do. Likely, those things could be automated.

Next, consider the parts of your job that require pattern recognition. If your job entails contract review and contract review is automated, what would you do in addition to overseeing the automated system’s work? As the LawGeex experiment showed, AI is highly accurate, but it isn’t perfect.

Your choice is fight or flight. You can give into the fear that you may be automated out of existence and act accordingly, which will likely result in a self-fulling prophecy. Alternatively, consider what parts of your job could be automated and reimagine your future. If you no longer had to do X, what would Y be?  What might your job title be and what your scope responsibilities be?

If you consider how intelligent automation may impact your career, you’ll be in a better position to evolve as things change and you’ll be better prepared to discuss the matter with your superiors.

The Bottom Line

The intelligently automated future is already taking shape. While the future impacts aren’t entirely clear yet, business leaders, managers and professionals can help shape their own future and the future of their companies by understanding what’s possible and how that might affect the business, departments and individual careers. Everyone will have to work together to make intelligent automation work well for the company and its people.

The worst course of action is to ignore it, because it isn’t going away.

Are You Really Ready for Intelligent Automation?

If you haven’t considered how intelligent automation will impact your industry and company, start now. Automation is going to impact every industry and every business in some way, first as a competitive differentiator and later as a matter of economic necessity.

The average consumer has been interacting with bots online and on the phone for years. However, bots are now reviewing contracts faster than lawyers can and solving scientific problems that have taken scientists decades to solve.

Some vendors already claim that their software can replace salespeople or data scientists, although management and technology consultants tend view automation as “assistive” because humans and machines excel at different things. The manufacturing industry has proven that machines are better at rote, repetitive tasks than humans because they can do the same thing a bazillion times without getting tired or bored, or needing a break. However, machines are also better at pattern recognition than humans, which describes one of the core things researchers, consultants and even journalists do.

Perhaps intelligent automation would be easier to understand if its growth path were linear, meaning that it would replace tasks that don’t require a lot of intelligence or skill first, and then move up over time to tasks that require increasing levels of skill and knowledge.

That isn’t the way things are shaping up, however.

“Outsourcing and offshore manufacturing affected certain categories of jobs and there was job creation in other areas and that played out over a decade,” said Todd Lohr, a principal within  KPMG’s Technology Enabled Transformation practice. “The problem here is this is going to happen faster than other transformation. It’s non-linear, and it’s going to affect all job categories.”

The business view

Lohr thinks automation will become the new corporate responsibility trend, like “green” which has been fashionable for the last three decades.

“The C-suite is enamored with technology. They have Alexa, they’re using Siri, they’re seeing it in their own lives. They’re buying Teslas and seeing self-driving cars are happening,” said Lohr. “This will impact them as leaders. What is their responsibility to their workforce and society?  It’s not just a cost/benefit analysis, so I think there’s going to be another paradigm for them to make those decisions.”

Business leaders need to consider how intelligent automation will impact their business model, goods and services, or they may find themselves disrupted. Similarly, a disruptor who understands the technology but fails to consider cost may find itself disrupted by a company that can deliver the same result at a lower cost.

“We’ve been talking about AI forever and nothing has happened, but people don’t recognize that the last 20 years was the very slow part of [the] exponential growth curve,” said Lohr. “Organizations need to think about how they handle this today because it’s going to happen faster than they think. They have to think about what it means to their organizations and the societies in which they work.”

Technology implementation matters

Intelligent automation, like any other technology, needs to be considered in the context of the existing infrastructure and how well it will scale. As always, what works well for a proof of concept may not scale well enough for a large enterprise implementation.

“You need to think about design in terms of what is going to be done digitally. You also have to think about governance,” said Sanjay Srivastava, chief digital officer at global professional services firm, Genpact. “If 50 employees failed to come to work in a 250-person firm, you’d have policies around that and visual clues. If 50 robots stopped working because of a password change, it might not be immediately obvious.”

Srivastava raises a good point: The policies that apply to people today need to be revisited in light of digital transformation and intelligent automation. Srivastava recommends business leaders and IT consider how the existing architecture and IT infrastructure need to evolve so any automation can align with what a company is trying to achieve and can change as needed.

The operating model also needs to be considered, and that includes the functions being automated, the role of that function in the enterprise and end-to end-processes. Finally, governance will be necessary to avoid or reduce the risks of errant bots and biased AI.

“You have to look at end-to-end processes in terms of integration and visibility,” said Srivastava. “If it’s designed right, it works well.”

Stop and think

Business leaders need to consider how automation will affect their operations, workforce, technology stack and offerings. Importantly, they should ponder what they want to (or would want to) achieve with automation, such as efficiency gains or cost reduction.

Ignoring the situation is unwise given the rapid pace innovation. Some will disrupt. Others will be disrupted.

Why Automation and AI are Cool, Until They’re Not

Every day, there’s more news about automation, machine learning and AI. Already, some vendors are touting their ability to replace salespeople and even data scientists. Interestingly, the very people promoting these technologies aren’t necessarily considering the impact on their own jobs.

In the past, knowledge jobs were exempt from automation, but with the rise of machine learning and AI, that’s no longer true. In the near future, machines will be able to do even more tasks that have historically been done by humans.

Somewhere between doomsday predictions and automated utopia is a very real world of people, businesses and entire industries that need to adapt or risk obsolescence.

History isn’t simply repeating itself

One difference between yesterday’s automation and today’s automation (besides the level of machine intelligence) is the pace of change. Automating manufacturing was a very slow process because it required major capital investments and significant amounts of time to implement. In today’s software-driven world, change occurs very quickly and the pace of change is accelerating.

The burning existential question is whether organizations and their employees can adapt to change fast enough this time. Will autonomous “things” and bots cause the staggering unemployment levels some foresee a decade from now, or will the number of new jobs compensate for the decline of traditional jobs?

“I think there will be stages where we have the 10 percent digital workforce in the next two years and 20 percent in three to four years,” said Martin Fiore, Americas tax talent leader at professional services firm EY. “Some will say, ‘Wow, that’s scary.’ Others will say, ‘I see the light I’m going to upscale my capabilities.”

Businesses and individuals each need to change the way they think.

Angela Zutavern, VP at management consulting firm Booz Allen Hamilton and co-author of the forthcoming book, The Mathematical Corporation views intelligent automation as a new form of leadership and strategy as opposed to just technology.

“Companies who understand this and get on board with it will be way ahead and I believe that companies who either ignore it or don’t believe it’s real may go out of business,” she said. “I think it’s better to know about it, understand it, and be a part of making the change happen rather than getting caught off-guard and have it happen to you.”

An old company pioneers new tricks

Despite its 100-year history, EY is actively facilitating the adoption of Robotics Process Automation (RPA) and AI within its own four walls and among its customers.

Its RPA group employs a global team of 1,000 robotic engineers and analysts who are creating new applications. In past 18 months, more than 200 bots have been rolled out in tax operations, which includes work for clients. EY is also using RPA processes internally in core business functions to improve quality and performance while enabling a new sense of purpose among its employees.

“RPA helps us increase our ability to handle high levels of transaction volume (e.g.,tax returns), accelerate on-time delivery and improve accuracy,” said Fiore. “Over time, there will be a positive impact on our workforce model, and we’re planning for that now.”

Similarly, an EY innovation lab recently experimented to see if AI could help to analyze contracts faster and better than people.

“We thought we’d make headway and great progress in a year or two, but in the first 90 days [the machines were] three times more effective in the process,” said Jeff Wong, global chief innovation officer at EY. “You’ll see us increasing our efforts there radically in the next 12 to 18 months.”

Last year, EY “hired” 350 bots, although company spends about a half a billion dollars annually on employee training. Job rotation is also common at EY because the company wants to “teach people to learn how to learn.”

Education will change

Young people entering the workforce already need different skills than their predecessors, and the trend will continue. Param Singh, associate professor of business technologies at Carnegie Mellon University expects grade schools to teach fundamental programming skills and high schools to teach machine learning.

“Typically, managers [had] person management jobs. Increasingly those jobs will have to be good on the technology side,” said Singh. “Few people are good at deep learning, probably less than 5,000. We’ll needs hundreds of thousands when we see major adoption happening.”

Meanwhile, working professionals and their employers should not be complacent. As the levels of intelligent automation increase, individuals and companies will need to understand which jobs will be displaced and which jobs will be created, none of which is static.

“Cloud computers, data lakes and in the future, quantum computing are things that every leader should be conversant about or anyone who aspires to a leadership role in this machine learning age,” said Booz Allen Hamilton’s Zutavern. “People should understand what the possibilities are and know when to pull in the deep experts.”