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Artificial intelligence is not taking over your job—it’s enhancing it


Mention artificial intelligence to a management executive and you may encounter some skepticism. New technologies need to be proven effective before managers and company leaders are comfortable using them. Bring up AI to workforce personnel and their eyes may either glaze over or betray a level of fear or anger at the idea of robots taking their jobs away.

The concerns regarding AI are understandable. According to the Brookings Institution, as many as 25% of Americans (35 million people) face high exposure to task disruption in the coming decades.[1] The McKinsey Global Institute forecasts that 39 million jobs will be displaced by automation by 2030.[2]

The problem is that management, workforce personnel and some media outlets often conflate AI with what they view as job-killing automation. Automation refers to machines that mimic repeatable human actions. A robotic process automation platform mechanizes manual, redundant or time-consuming tasks that don’t require a significant amount of decision-making. Interestingly, a recent RSM survey found that the vast majority of middle market companies investing in automation or information technology in response to staffing challenges pointed to increased efficiency (85%) as the reason compared to a substitute for labor (11%).

AI, on the other hand, organizes and analyzes data, drawing conclusions and offering recommendations based on information it receives. The tasks performed by systems using AI require forms of intelligence such as visual perception, speech recognition and decision-making, among others. But, importantly, they often also require hard-to-program human intervention as well.

What we mean when we say AI

Call it artificial intelligence, cognitive computing or machine learning, platforms in the field are designed to analyze data. The term artificial intelligence, first coined by American computer scientist John McCarthy in 1955, refers to “the capacity of a computer to perform operations analogous to learning and decision-making in humans,” according to one definition.

But AI is a technology that still requires human engagement. Architects, engineers, data scientists and other high-skilled roles will incorporate AI into their operations but not be replaced by it. Personnel in hands-on roles, such as health care providers, construction workers and many professionals, will be safe from any perceived threat to their jobs due to AI.

AI and the benefits to industry

AI will be used overwhelmingly for supply chain management and sales and marketing,[3] but additional uses will range from using customer data to personalize promotions to predictive maintenance. While AI and machine learning usage varies by industry, it combines the efficiency of technology with the analysis of workforce personnel:

  • Real estate companies leverage real-time data by combining internet of things and AI technologies to develop sophisticated interconnected systems for their properties. Sensors are available to read utility usages in items from smart HVAC systems, elevators and lights—even down to the faucet level. These smart buildings allow for predictive analysis, leading to better preventative maintenance, and thereby reducing costs and increasing tenant satisfaction. Real estate investors are using machine learning to expedite the initial deal due diligence period. When their algorithms find a deal that is favorable, it gets flagged for the analysts.
  • In health care, a doctor looks at eye tests and exams to see if a patient is exhibiting signs of glaucoma or other anomalies. With AI, human error is removed. The technology can review imagery and data and, potentially, catch something a physician might miss.
  • As inventory and supply chain management become increasingly important, retailers are turning to technology to look beyond historical analysis to anticipate changes in demand before they happen.
  • Financial institutions are leveraging AI to work with customers. Using machine learning, AI gathers consumer information—directly from individuals through chatbots as well as from those with similar needs—to accept loan applications or identify products and services. A banker validates the decisions made by the AI algorithm. The rise in cyber activity is driving the use of AI to spot potentially fraudulent behavior.
  • In the technology, media and telecommunications industry, app-based transportation platforms are able to enhance the customer experience by adjusting what they offer to the user. Ride-hailing services have embraced AI to offer different levels of service based on a consumer’s history, location and forecast of future activity.
  • In life sciences, AI’s automation and rapid assessment capabilities allow patients to be identified more efficiently, outcomes determined more quickly and trial costs to be minimized. What used to take an average of four months to identify trial candidates is now, with the help of AI, reduced to weeks. In addition, AI can simulate how synthetic proteins will fold before they’re even synthesized, resulting in dramatically reduced development lead time and costs of creating new drugs.
  • Among the many uses of AI in manufacturing, addressing quality and safety are among the most important. On a micro-level, machine vision tools can be used to spot defects in circuit boards, for example, that would go undetected by the human eye. Looking at the bigger picture, mobile and even stationary bots can be trained to avoid collisions with each other and their human counterparts.[4]

AI and the competitive edge

The disruptions caused by automation will make it rough for many workforce personnel: The most at-risk jobs by 2030 will be office support and other roles in predictable environments such as machinists and cooks. This may be offset, however, by approximately 15 million more new jobs that will be created within that same timeframe.[5]

Yet while automation is not artificial intelligence, many companies are reluctant to get on board the AI bandwagon without more validation. AI technology is being used in call centers and warehouses to optimize human behavior, track performance and provide feedback in real time. While managers may focus on the improvements that result from using AI, some employees find this “management by algorithm” to be a minor annoyance; others consider it overbearing.[6]

The time will come, however, when companies realize they need to retool their personnel—in IT, data governance, risk management and throughout the workforce—if they are to remain competitive.

As the Organisation for Economic Co-operation and Development noted, “people, especially youth, need to prepare for the jobs of the future by being equipped with the right mix of skills required to successfully navigate ever-changing, technology-rich work environments, [an effort that] increasingly involves lifelong learning.”[7]

1.  J.D. Ratliff, N. Arnosti, “A governor’s policy playbook to address disruptions from automation and artificial intelligence” (March 1, 2019) The Brookings Institution.
2.  “Jobs Lost, Jobs Gained: Workforce Transitions In a Time of Automation” (Dec. 2017) McKinsey Global Institute.
3.  M. Chui, N. Henke, M. Miremadi, “Most of AI’s Business Uses Will Be in Two Areas” (July 20, 2018) Harvard Business Review.
4.  P. Dorfman, “3 Advances Changing the Future of Artificial Intelligence in Manufacturing” (Jan. 3, 2018) Autodesk.com.
5.  “Jobs Lost, Jobs Gained,” McKinsey Global Institute.
6.  A. Roose, “A Machine May Not Take Your Job, but One Could Become Your Boss (June 23, 2019) The New York Times.
7. “Transformative Technologies and the Jobs of the Future,” (2018) Organisation for Economic Co-operation and Development.


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