How it is Impacting Decision Making in the Workplace
The world of work is constantly being moulded by new technologies and changing demands from employees and employers. Artificial Intelligence is one of the latest and possibly, most impactful technologies shifting the global landscape.
As AI systems become increasingly more common in production lines, offices, prediction models and workplace decisions, it is critical to explore how adopting AI will impact economic activity and professional lives.
Defining Artificial Intelligence
You no longer need to be a data scientist to engage with complex data. The term applied AI is everywhere, and it can be easy to forget what it encompasses with all the new rhetoric we’re encountering.
As such, this article should define the term used throughout the piece. Applied AI involves all the activities that underlie AI’s operationalisation from experimentation to production, including enabling computers and computer-controlled robots to execute tasks. What is most interesting for business leaders and employees is how AI will be used at work and the impact on human labour and human workers.
Artificial Intelligence in the Workplace
A recent global survey by McKinsey found that more than half of the respondents were beginning to implement AI in at least one of their business units. In that same study, nearly two-thirds of respondents expected their organisations to increase investments in AI over the next few years.
Applied AI is a powerful tool for organisations to improve their business practices. One of the more apparent areas for businesses to begin integrating AI in the workplace is using it to aid decision-making.
Applied Artificial Intelligence for Decision Making
Organisations have largely left the decision-making to the judgement of management judgement. However, in recent years, organisations have been increasingly interested in implementing data to aid decision-making.
Still, AI allows leaders and decision-makers to reimagine how they manage processes, how to use AI for talent acquisition, and organisational structures, but how is it reshaping how organisations operate?
Five Ways that Applied Artificial Intelligence is Reshaping Decision Making
Enhanced Data Analysis:
- One of the primary ways applied AI transforms decision-making is by enhancing an organisation’s data analysis capabilities. With the ever-growing data available to businesses, traditional data processing and analysis methods have become inadequate. In an earlier HR analytics article this year, we examined how organisations impacted employee experiences. Still, as we have seen, the development of AI redefine what business can do with the large amounts of data they have.
- With human assistance, applied AI algorithms and artificial intelligence tools can swiftly analyse vast amounts of data, extracting valuable patterns, key business metrics, trends, and correlations that would be difficult or time-consuming for humans to identify. It also removes some of the natural human biases and human errors found during analyses. It empowers decision-makers with comprehensive and accurate insights, enabling them to make informed choices backed by data-driven evidence.
Automation and Efficiency
- Decision-making often involves repetitive tasks that consume valuable time and resources. Applied AI offers automation capabilities that streamline these processes, freeing human resources for more strategic and creative endeavours as complex data becomes easier to understand. AI-powered systems can handle routine tasks precisely and quickly, from data and information security to data collection and analysis to generate reports and recommendations.
- AI’s big data insights improve overall efficiency and reduce the margin for human error, ensuring more reliable and consistent decision-making. It also allows human intelligence to support making decisions more efficiently as AI takes on the more mundane tasks.
Predictive Analysis
- Applied AI empowers decision-makers with predictive analytics, enabling them to anticipate future outcomes and make proactive decisions. By leveraging historical data and machine learning algorithms, businesses can predict employee and customer behaviour, market trends, and potential risks. This capability allows organisations to stay ahead of the curve, adapt to changing circumstances, and capitalise on emerging opportunities. Predictive analytics supported by applied AI brings a competitive advantage by reducing uncertainty and enabling agile decision-making.
Risk Management and Compliance
- Applied AI is also making significant strides in risk management and compliance. By analysing substantial amounts of data and identifying patterns, AI systems can flag potential risks, anomalies, or compliance violations. This proactive approach mitigates risks and ensures that organisations adhere to regulations and ethical standards. AI-powered tools can continuously monitor and assess data, providing decision-makers with real-time insights and alerts to support risk mitigation strategies.
Personalised Decision Support
- Every decision-maker has unique preferences, biases, and decision-making styles. Applied AI can provide personalised decision support by understanding individual patterns and adapting to specific needs. AI-powered systems can learn from previous decisions and tailor recommendations to align with the decision-makers objectives and constraints. This level of personalisation empowers individuals to make decisions that align with their strategic vision while considering a broader range of relevant factors.
Considerations Organisations Need to Make as they Implement Artificial intelligence in the Workplace
Artificial intelligence in the workplace can provide big data insights for organisations. In contrast, the integration of artificial intelligence in decision-making processes has the potential to revolutionise how organisations operate and achieve their business objectives. Applied AI offers powerful tools and capabilities to enhance efficiency, improve accuracy, and unlock valuable insights. However, as organisations embrace this transformative technology, it is crucial to consider certain factors to ensure successful implementation and maximise the benefits.
These considerations include, but are not limited to:
Clearly Define Objectives
- Before integrating applied AI into decision-making processes, organisations must clearly define their objectives, and this involves identifying the specific challenges or areas where AI can provide the most value. Whether optimising supply chain operations, improving customer experience, or enhancing risk management, organisations must align AI initiatives with their strategic goals. Defining clear objectives will enable focused implementation and ensure that AI solutions address the most critical decision-making needs.
Ethical and Legal Considerations
- AI applications raise important ethical and legal considerations that organisations must carefully address. Decision-makers must ensure that the data used for training AI tools and AI technologies are obtained ethically and that privacy rights and data protection regulations are respected. Additionally, organisations must consider the potential biases and unintended consequences that AI algorithms might introduce into decision-making processes. Regular monitoring and evaluation of AI systems can help identify and mitigate biases or discriminatory outcomes, ensuring fairness and transparency in decision-making.
Human and Artificial Intelligence Collaboration
- Applied AI is not meant to replace human decision-makers but augment their capabilities. Organisations should establish a framework for effective human-AI collaboration to leverage both strengths. It is essential to foster an organisational culture that encourages employees to embrace AI as a valuable tool and provides the necessary training to understand and work alongside AI systems. Clear communication channels and well-defined roles between humans and AI will enable seamless collaboration and ensure that AI-driven insights are effectively integrated into decision-making.
Continuous Monitoring and Evaluation
- Integrating applied AI in decision-making is an ongoing process that requires continuous monitoring and evaluation. Organisations should establish mechanisms to assess the performance and effectiveness of AI systems regularly. This involves monitoring key metrics, evaluating the impact of AI-driven decisions, and gathering user feedback. Continuous improvement and adaptation based on real-world feedback will help refine AI models and generative AI tools to enhance decision-making outcomes and uncover opportunities for further optimisation.
Scalability and Flexibility
- Organisations should consider the scalability and flexibility of AI solutions when incorporating them into decision-making processes. As the needs of the business evolve, the applied AI infrastructure should be able to adapt and accommodate new requirements. One example may involve selecting AI technologies that can easily integrate with existing systems or investing in scalable cloud-based solutions.
Final Thoughts
Applied artificial intelligence is revolutionising decision-making in the workplace by augmenting human capabilities, enhancing data analysis, enabling predictive analytics, streamlining processes, and offering personalised support. In addition, artificial intelligence in the workplace can be used to turn complex data into something that a larger group of people can understand.
The implementation of artificial intelligence does not mean the elimination of human workers, human intelligence, or human creativity. On the contrary, if used correctly, artificial intelligence should provide valuable insights, minimise repetitive tasks, assist in an employee’s personal development and, with evidence-based reasoning uncovered, make work more efficient. As a result, organisations that carefully embrace AI tools have the opportunity to create a new modern workforce without making employees fearful of machine learning causing job losses.