What Tasks Will Be Automated in Future Businesses?

In today’s technologically advancing world, artificial intelligence (AI) disrupts almost every sector, reimagining how business is conducted. The ubiquitous influence of AI is not only confined to digital marketing or legal analysis, but its tendrils are reaching into virtually every aspect of commerce. From automating accounting processes to streamlining sales outreach and even creating dynamic presentations, the integration of AI is revolutionizing the work landscape.

“I honestly can’t think of many areas of business that won’t be affected by AI at some point in the future,” says Craig Froehle, PhD, a professor of operations, business analytics, and information systems at the University of Cincinnati Lindner College of Business. “That said, I think a lot of jobs will have relatively subtle effects in the near future, whereas other jobs will be more overtly and broadly affected. Take agriculture, for example. AI is helping forecast weather conditions and markets to assist farmers with the task of deciding what to grow and when to plant. But the physical processes of preparing land, planting seeds, tending to crops, and harvesting have been less affected, at least in the short run. In contrast, artists and translators are two jobs where professionals are already today feeling the pressure that generative AI models have started to exert on their professions over the past year or two.”

The field of medicine is another place where AI and automation have had a significant impact. “The Mayo Clinic Platform integrates a large-scale repository of patient and care process data with a suite of AI tools and algorithms to help healthcare organizations provide better care. While Mayo Clinic is probably further down that road than most healthcare systems, Cincinnati Children’s Hospital Medical Center has the Artificial Intelligence Imaging Research Center, which develops new AI-based algorithms and tools to help radiologists and physicians make better use of the complex imaging data generated by advanced modalities,” shares Dr. Freohle.

Keep reading to learn more about what jobs and tasks will be automated, the benefits of automation, the challenges of these technological changes, and ethical considerations.

Meet the Expert: Craig Froehle, PhD

Dr. Craig Froehle is a professor of operations, business analytics, and information systems at the University of Cincinnati Lindner College of Business. He also holds a faculty appointment in the UC Department of Emergency Medicine.

After working in the engineering industry and founding a dot-com startup, he moved to academia to pursue his research and teaching passion: operations management, with a special focus on healthcare delivery and technology-enabled services.

Jobs and Tasks Most Likely To Be Automated

Several job roles and tasks show a high potential for automation as AI capabilities continue to evolve: “Jobs that rely heavily on routine have traditionally been the easiest to automate. Whereas a lot of automation in the past has been through procedural scripts and rule-based systems, new generations of AI models will help cover a wider range of tasks and functions,” says Dr. Froehle.

“Jobs that require some integration of various pieces of information in a fairly systematic way, such drafting up a standardized legal document or generating an operational dashboard, are relatively straightforward today and likely to be automated.”

While there are many jobs and tasks that are already automated, in the future, there will be many more, as well as a marked improvement in the ones that already exist: “Moving ahead, much better language models, such as those used for translation, transcription, and customer support, will increasingly replace some parts of some workers’ jobs. On the software engineering side, automatically documenting, and sometimes even fixing, code has already shown to be feasible at previously unattainable levels of quality and scale,” explains Dr. Froehle.

He continues, “Healthcare, customer service, and a lot of information industries have already embraced AI and started using it in impressive ways. Many hospitals have AI running in various capacities, either home-grown or off-the-shelf. Radiology, for example, has long been a hotbed of computer vision applications. Many online customer service and call center functions employ chatbots to help customers with routine questions, saving their human capacity for more complex or ambiguous situations. One of my doctoral students is researching how such chatbots might best be integrated into customer service systems to maximally help customers while taking as much strain as possible off the human agents.”

Some jobs will be much harder to automate. “On the contrary side, those tasks that are going to be least automatable involve significant amounts of critical thinking and innovation relative to highly technical or complex bodies of knowledge, training, or experience,” says Dr. Froehle. “It is truly hard to say what lies in store for us ten years from now.”

Impact on Workforce

The impacts of automation and AI on the workforce can be viewed through multiple lenses. On one hand, the implementation of AI can lead to job displacement. As noted earlier, roles involving routine tasks that can be automated, such as data entry clerks, manufacturing, and warehouse jobs, are at risk. A 2023 study from the McKinsey Global Institute found that by 2030, up to 30 percent of the hours currently worked in the United States could be automated.

However, on the other hand, AI and automation also have the potential to create new job categories and amplify human capabilities. For instance, AI can take over mundane tasks, allowing employees to focus on higher-level, more strategic responsibilities. This can lead to increased job satisfaction, productivity, and innovation.

“Like any large-scale technology-induced shift, jobs will change. They changed when steam power enabled at-scale manufacturing. They changed when electrification allowed factories to run 24/7. They changed when computerization eliminated repetitive, mundane information tasks and calculations,” shares Dr. Froehle.

“What is harder to predict is how jobs will change because AI tools are evolving so rapidly right now. Last spring, I prepared a new curriculum for a course that was to happen in August and September. By July, some of what I had prepared was already obsolete. That rate of change makes forecasting much into the future extremely difficult, if not impossible. Today’s workers should be prepared to upgrade their skill sets faster and more frequently than any generation of workers before them. And short of AI replacing the vast majority of workers entirely, something I truly do not expect, I don’t see that trend slowing down.”

Ethical Considerations of Business Automation

One of the most significant issues with AI and business automation is the ethical problem of algorithmic bias, where AI systems may inadvertently reinforce existing prejudices due to flawed data or programming. This can lead to unfair outcomes in hiring, lending, or law enforcement: “How will we ensure that unjust biases that exist in historical data don’t infect future models? If they do, then the decisions made by those models will be no better or fairer than the decisions we’ve made in the past,” warns Dr. Froehle. “They’ll just be faster and cheaper. While that’s a big advantage, not straining out those biases whenever possible would be a huge missed opportunity to use technology for real and necessary good.”

Aside from baked-in biases, there are other ethical considerations with AI-created work. “Another issue is the intellectual property rights of those who generated the data we’re using to train these large AI models. While some can be trained exclusively on operational data, that is to say, data that is generated simply by executing business processes, a lot of training requires the use of either data scraped off the internet, which is actually owned by someone, or data labeled by workers who may not be paid a living wage. It’s similar to raw materials in a supply chain from questionable or problematic sources,” explains Dr. Froehle.

Benefits of Business Automation

The automation of business operations through AI and other methods presents a multitude of benefits: “The primary benefits are first faster/cheaper outputs, and second, insights that human-based analysis likely would not generate alone,” shares Dr. Froehle.

“Automating a decision-making process, such as discriminating between conforming and faulty parts on a production line, makes them cheaper than when they’re done one-by-one by people. Labor is just really expensive, largely because it’s typically not very scalable and also partly because humans make lots of mistakes, get bored, get sick, etc.”

He continues, “Another benefit is less about saving money and more about creating competitive advantage. Suppose your AI-based protein-folding model can generate new pharmaceutical formulas better than your competitors’ products. In that case, that’s really powerful, and doubly so if it can do it faster than their scientists can.”

Another benefit of automation is the ability to scale operations. As businesses grow, the tasks that need to be performed also multiply. Automation allows companies to handle this increased volume without a proportional rise in costs or staffing.

Automation can also lead to more consistency in business operations. Automated tasks are performed the same way each time, ensuring uniformity and reducing the probability of errors. It can also provide valuable data for businesses, which they can collect, organize, and analyze, leading to better decision-making.

Challenges of AI and Business Automation

While the advantages of AI and automation in business are apparent, implementing these technologies is not without its hurdles. “There are lots of challenges. One is the rapid rate of change. Businesses are already finding it hard to hire and retain AI talent. Keeping a stable regiment of AI scientists and engineers available to tweak existing models and develop new ones is an ongoing challenge,” says Dr. Froehle.

Implementing AI and automation requires a significant investment not just financially but also in terms of time and resources for staff training. This is especially true for small and medium-sized enterprises that may lack the necessary resources: “Companies have to figure out how to maximize their return on investment. These systems can be quite costly to implement, and determining where in the company’s many processes and functions these models can justify themselves quickly can be hard. I expect companies that focus on how a specific system might add value will generally outperform those businesses that are constantly chasing the latest tech,” says Dr. Froehle. “Both these challenges are made worse by that rapid rate of change we’re seeing.”

Another challenge that businesses will face with automation and AI is the issue of data privacy. As AI systems become more prevalent in commerce, they collect vast amounts of personal data, raising questions about how this information is stored, used, and protected. This has led to the emergence of regulations such as the General Data Protection Regulation (GDPR) in Europe, adding a new layer of complexity for businesses utilizing AI.