The Future of Digital AI Workers and Automation.

The Future of Automation and Digital AI Workers.

The speed at which artificial intelligence (AI) and automation technologies are advancing is drastically disrupting the global workforce. Digital AI workers (AI workers) are beginning to be integrated into many industries that were previously based entirely on human work (e.g. customer service chatbots, self-driving cars). The adoption of digital AI worker prompts critical questions about the future of work, the economy, and society as a whole.

Emergence of Digital AI workers.

Digital AI workers are cognitive systems created using software code to conduct cognitive work historically undertaken by humans. Digital AI worker technologies include, for example, AI-powered chatbots, or virtual assistants, robotic process automation (RPA) applications, and machine learning algorithms that can process data, arrive at decisions, and learn from experience. Digital AI workers differ from physical robots who perform manual labour, as digital AI workers exist only in software and operate solely in a virtual environment.

AI workers are helping to revolutionize common work tasks in industries such as finance, healthcare, education, retail, and manufacturing. For example, banks are employing AIs to process loan applications, and banks use AI to detect potential fraud. Healthcare systems utilize AI to assist with diagnostics and monitoring of patients. Similarly, retail companies are optimizing customer experiences in every step of the purchasing journey through AI by processing past purchasing behaviours and preferences.

Automation and the Evolving Job Market.

Automation of tasks through AI will affect the workplace. A McKinsey Global Institute report determined that 30% of tasks in 60% of occupations could be automated right now using existing technology. This does not mean that 30% of people will lose their jobs; it does mean that each occupation will look different.

Repetitive and routine tasks are the most susceptible to automation. Examples of these tasks include data input, bookkeeping, and even simple customer service, which companies will replace with their own digital systems. Other tasks, such as therapy, strategic planning, and leadership, require emotional intelligence, creativity, and more complex decision-making. These tasks are less likely to be automated.

This shift is also creating new jobs. There is high demand for jobs that manage, program, or maintain AI. There is also increasing need for overseeing the ethical considerations and regulatory compliance of using AI within business practices and companies creating positions to oversee AI ethics and regulations and policy.

The Advantages of AI and Automation.

There are many advantages to having AI workers and automation. The organization experiences the benefits of automation in terms of increasing productivity, efficiencies while reducing human error and costs of operations. Digital workers can work 24 hours a day, process and react to user queries instantly, and processes are much faster in a fast paced business environment.

In addition, AI can enhance human productivity rather than replacing it. For example, a doctor using AI diagnostic tools will be able to achieve better results, or a teacher using AI learning platforms can better educate their students (with tailoring the education to individual learning models).

From an economic perspective, automation can provide an engine for growth through output expansion and chances to provide improvements and innovations to businesses. Automation will also solve various labor shortages the aging population contemplates, especially in markets with large population scaling constraints, and free human labor to create meaningful work with larger impact in the world.

Challenges and Ethical Considerations.

However, there are significant challenges related to the incorporation of digital AI workers. Job displacement is a major issue for low-skilled workers who may not easily be able to switch occupations. Without reskilling and retraining educational programs, workers who gain equitable access to learn and take advantage of AI technologies could end up with significant economic gains, while other workers may fall further and further behind after losing their jobs, thereby creating inequities in access to work opportunities or jobs as a whole.

Another important challenge is data privacy and security. AI systems require large datasets to allow improvements to the underlying models used by AI systems, and these datasets sometimes include sensitive personal information. Data privacy and security will be critical in ensuring that people have no concern that AI systems are being developed in a secure and transparent manner and ethically.

AI bias is also a growing area of concern. Most AI systems use data based on past performance in creating models that are used to bias behavior. If AI systems use biased data, the successful AI system could create and continue discrimination while conducting work within hiring, lending, law enforcement, and any other critical social justice issues. To mitigate bias in AI, teams of diverse developers with a commitment to inclusion, oversight of development, testing and deployment, and ongoing monitoring conducted by diverse teams will be needed.

Preparing for the Future.

To prepare for the future of work, governments, businesses, and individuals must all act. Policymakers can develop education and training programs that ensure workers have the digital skills needed for an AI economy, both in terms of technical training and the soft skills for adaptability, critical thinking and working together.

 Businesses need to ensure they are responsibly adopting AI with an environment of transparency, inclusivity, and human oversight. Businesses must also think in terms of hybrid worker models where humans and AI work together, and where the strengths of humans and AI are utilized.

 And for individuals, you must think in terms of being a lifelong learner. Technology is changing so rapidly that relevant knowledge is only a margin away from being irrelevant, and upgrading your skills and adapting to change are paramount to staying relevant in a world of change.

Final thoughts.

The future for digital AI workers and automation is both thrilling and uncertain. While these advances entail the ability to generate, communicate, and implement improved efficiencies and new innovations, an emphasis on how these systems will function together in an equitable society is essential. Through careful cross collaboration, the vision of humans and machines working together effectively aligning ethical and social considerations, a future of automation and progress can be achieved.