Today, artificial intelligence solutions are being adopted in an increasing number of organizations and functions. These solutions are automating routine tasks, algorithms are learning from data at rapid speeds and machines are gaining the ability to understand natural human speech with greater accuracy. Increased adoption of AI is enabling businesses to take a new look at their operations and see areas where humans can be replaced with automation. As a result, we’re seeing a growing number of organizations that have started using AI to augment their employees rather than replace them. The rise of this AI-augmented workforce is the future of work in the age of artificial intelligence.
What is an AI Augmented Workforce?
An AI augmented workforce is a mix of humans, machines and algorithms that work together to increase productivity, reduce costs and improve the quality of service. An AI-augmented workforce leverages the power of both humans and machines by combining algorithms, AI-driven automation and human expertise to create better outcomes. An AI augmented workforce is not just about the use of AI in business processes or single tasks. It’s about changing the way organizations operate by bringing together people, machines and algorithms to create a more powerful and efficient workforce. An AI augmented workforce is a mix of humans and machines that work together to create better outcomes.
How does an AI-augmented workforce differ from a traditional workforce?
In a traditional workforce, people are responsible for all of the decision making. They are vital to the operation of the business and are the only ones who have the knowledge and expertise to drive the organization forward. In a traditional workforce, machines are used to support humans by automating repetitive tasks and algorithms only provide the rules that govern the machines. In an AI augmented workforce, humans are still in the driver’s seat. They’re responsible for the strategic direction of the organization. Machines support the humans by automating repetitive and predictable tasks, and algorithms drive the machines. A core difference between the two workforces is that the machines in an AI augmented workforce are empowered with algorithms that enable them to learn from data and improve over time. They’re no longer just executing the rules provided to them by their human operators. Instead, they’re actively learning from data, making decisions and improving their performance over time. The algorithms in an AI augmented workforce are responsible for the strategic direction of the organization.
Benefits of an AI-augmented workforce
- Increased Efficiency – AI-powered machines can execute tasks with greater speed and accuracy, freeing up humans to focus on strategic tasks.
- Algorithm-Driven Machines – Machines are not required to be 100% accurate to be beneficial. Algorithms can provide machine operators with a certain degree of error that can be tolerated. This way machines can still produce acceptable results even when they’re not perfect.
- Reduced Defects – Machines are programmed to be consistent and accurate which means they rarely make mistakes. Algorithms can also be programmed to identify and fix defects as they happen.
- Improved Collaboration – Humans and machines working together can achieve more than either working on their own. This can be achieved by using collaboration tools and connecting humans to artificial intelligence algorithms.
- More Accountability – Humans and machines working together can lead to greater accountability. This is particularly true when machines are empowered with algorithms that can learn from data and improve over time.
Drawbacks of an AI-augmented workforce
- Loss of Control – Humans have always been in charge of the direction of organizations and the work that gets done. Now, machines and algorithms are actively driving the organization using data to make decisions and improve over time.
- Loss of Expertise – Workers who are responsible for managing machines and algorithms may struggle to adapt if their algorithms need to be updated or if their machines break down. When this happens, these workers may not have the expertise to troubleshoot the issues that arise.
- Lack of Creativity – Machines and algorithms are programmed to be consistent and consistent is not always creative. This can pose a challenge for organizations that rely on creativity to create unique and valuable products and services.
- Lack of Accountability – Machines and algorithms are programmed to be consistent and accurate which means they rarely make mistakes. This can lead to a lack of accountability among decision-makers as no one is responsible for mistakes made by machines and algorithms.
Which tasks will be performed by humans and which by machines?
The key to successfully adopting an AI augmented workforce is to identify tasks that can be automated using algorithms, machines and AI. This will help you streamline your business operations and free up time and resources that can be spent on generating greater value. Once you’ve identified all the processes and tasks that can be automated, you can identify which ones should be performed by humans and which can be done by machines. This will depend on the accuracy, complexity and value of each task. More accurate, simple and high-value tasks can be performed by machines whereas high-complexity, low-accuracy and less valuable tasks can be performed by humans. The best way to determine which tasks will be performed by humans and which by machines is to create a table that outlines each task and the values associated with it. Once you’ve completed this table, you can determine which tasks should be performed by humans and which by machines.
Concluding Words
The rise of AI is transforming business operations by automating tasks and enabling organizations to scale up with limited resources. Organizations that want to remain relevant and competitive in today’s digital landscape must embrace AI and use it to augment their workforce. An AI augmented workforce is the future of work in the age of artificial intelligence.
