For some people, the thought of AI-driven automation conjures up images of workspaces populated only by robotic or computerized workers; after all, the prefix ‘auto’ is Greek for ‘self,’ suggesting that an automated system can run effectively all on its own. However, machine learning engines and similar technologies cannot function fully autonomously. Humans are required to ensure they are delivering optimal results and to complete the tasks they aren’t well-suited to perform. Therefore, rather than fearing that your job will be eliminated entirely by automation, you can prepare yourself to adapt to a role in which you must co-work with artificial intelligence. The opportunities afforded to human workers by the introduction of AI-based automation technology can be loosely sorted into three categories: helping the AI function, filling gaps in its capabilities, and taking advantage of the possibilities that AI opens up.

Help the AI to Function Better

In order to function effectively, AI engines must analyze large and varied data sets. To meet this requirement, they need a human to serve as their eyes and ears, gathering data and training the model to output the desired results. Additionally, AI technology is not infallible, and it has a tendency to reproduce any biases that exist in the data being analyzed. Therefore, it is essential for human workers to monitor AI systems for problems, then determine where they come from and how the model's output is being affected. If you notice a model is making incorrect predictions, you can look through the data and correct the issue. You can also pass this information on to data scientists or programmers to prevent the problem from happening again. Without human employees monitoring the AI to detect and fix issues, companies won’t be able to derive the maximum benefit from this technology.

Fill Gaps in the AI’s Capabilities

When you imagine a business making decisions using artificial intelligence, it’s tempting to picture a machine delivering specific, clearly reasoned instructions that the human workers simply carry out. In reality, machines do not excel at generating specific, detailed action plans, and they possess almost no ability to explain themselves. AI engines can analyze data to generate insights, but the reports output by AI engines must be contextualized and explained by people. With your advanced domain expertise, you will be able to interpret their findings, making you an invaluable asset to your company.

Any workplace using AI will need employees that can clearly explain the findings and answer questions.

Additionally, since the goal of most AI engines is to identify trends in data sets and draw conclusions based off these findings, they are not well-equipped to handle edge cases. In the case of data that is anomalous, extreme, or otherwise exceptional, a machine learning model might experience difficulties executing its typical process. Therefore, the best course of action is to assign a human worker to deal with the relatively small number of edge cases that will arise. By specializing in these cases, you can continue to fill the role you played pre-automation, but with an added element of challenge.

Take on New Opportunities Afforded by the AI

With so much focus on the negative aspects of automation, it can be easy to lose sight of the exciting new possibilities that it allows. As discussed above, AI engines tend to take over the repetitive elements of a job, as well as tasks that require a lot of work but little human input or creativity. Once the system is implemented, workers can use their time more efficiently, prioritizing the tasks that the machine can’t do well and tackling a greater number of challenging problems than was previously practical. The time that was spent manually accomplishing the work now done by AI can be used to launch new initiatives.

It is also worth considering that, if effectively employed, automation can help a company attract more business and scale up. These changes are likely to generate additional work, though it may be of a different type than before. For example, if AI allows your company to expand in size, there will be a need for larger-scale maintenance planning and coordination between plants.

In conclusion, though artificial intelligence and machine learning may bring enormous change to modern workplaces, it’s misrepresentative to suggest that the result will be massive job loss in any field that implements it. People will still be needed to train models, correct errors, explain findings, process edge cases, handle new opportunities, and perform many other tasks that capitalize on their unique assets as humans. Therefore, rather than anticipating a world where jobs are dominated by either humans or AI, imagine an employment landscape in which humans and AI work together to achieve the best possible outcomes.