Data-driven decision-making and analytical insight define the world of business in the modern era, which means that there has never been a greater demand for skilled and intuitive data analysts. Across all industries, data analysts work to harvest accurate data and perform in-depth analysis, providing business leaders and entrepreneurs with the actionable insights they need to make the best possible decisions.
But in the age of machine learning and artificial intelligence, it begs the question, will AI replace data analysts? It's a question that many aspiring data scientists are pondering today.
Who Are Data Analysts, and What Do They Do?
Data analysts are scientists who rely on advanced techniques and analytical tools to harvest data and subsequently analyze it. According to the United States Bureau of Labor Statistics (BLS), the job outlook for data analysts is positive, and the bureau anticipates that there will be a 36 percent job growth rate in this field. This is much faster than average when compared to all other occupations.
Key Responsibilities and Skills of Data Analysts
The BLS notes that the key responsibilities of data analysts include:
Collecting relevant and accurate data
Deciding which type of data is most useful and relevant to the project
Developing and updating algorithms designed for data collection
Analyzing the available data to create reports that can be presented to leadership
Data analysts must have a well-developed sense of business acumen as well as a background in science, and they will rely heavily on mathematical and analytical skills to complete their daily tasks.
The Evolution of Data Analysis in Software Development
The process of collecting and analyzing data emerged in the late 1950s and early 1960s, when the computing industry was in its infancy. Data processing and analytics has long played a pivotal role in software development, but today, the industry is driven largely by advanced algorithms and machine learning technology. As AI project management technology becomes more advanced, it's clear that there will be shifting roles for data analysts and project management professionals.
How Does Artificial Intelligence Affect Data Analysts?
Artificial intelligence is a broad type of technology that has the potential to redefine the entire field of data analysis. According to the International Institute of Business Analysts (IIBA), AI technology has the ability to process extremely high volumes of data at far faster speeds than humans can do, which is critically important in today's data-based business climate.
Automating Data Collection and Analysis Processes
Artificial intelligence and related technology can help automate the data collection and analysis process that formerly had to be performed manually by analysts, ultimately reducing the time and cost of collecting and analyzing data. Some of the tasks that can be automated by AI technology include:
Generating advanced code for analysts based on their own guidelines and parameters
Collecting and presenting data summaries for analysts to consider
Summarizing critical insights that can be used as part of the visual presentation
Enhancing Data Accuracy and Efficiency
By leveraging the power of AI technology, data analysts can improve the overall accuracy of the data collected. With minimal room for human error, AI is able to easily collect some of the most accurate and insightful data. In addition, AI project management tools have the ability to collect and analyze this data at a much faster rate, ultimately reducing the time and cost associated with data analysis.
AI’s Influence on the Demand for Data Analysts
On the surface, the advent of AI technology may leave you wondering, will AI replace data analysts? Fortunately, the answer is no. Data analysts are still expected to be in high demand, as AI technology is not used to replace analysts, but rather provides them with the assistance they need to do their job better.
The Growing Need for AI-Savvy Data Analysts
The demand for skilled and qualified data analysts is on the rise, but more importantly, aspiring data analysts need to become proficient in the latest AI technology to set themselves apart from qualified candidates. Data analysts who are experienced working with AI tools and comfortable with this type of advanced technology will be able to offer more value to an organization than those without this type of niche experience.
Changing Job Descriptions: The New Era of Data Analysts
The International Institute of Business Analysts emphasizes the fact that AI is not intended to replace human data analysts, but rather, these tools can be used to alleviate the burden of some of the most tedious job responsibilities that they have. In the age of AI, data analysts will shift from manual data collection and analysis to more strategic tasks. These include making data-driven decisions, communicating insights in line with the business culture, and upholding ethical practices in data analysis.
Upskilling for Data Analysts in the AI Era
Whether you are a data analyst with decades of professional experience or a college student looking to pursue a career as a data analyst, you will need to focus on advanced skill development in the AI era. Upskilling for data analysts in the AI era will require data scientists and business professionals to look beyond the technical skills of harvesting and analyzing data and focus primarily on soft skill development.
Future-Proofing Your Career as a Data Analyst
The World Economic Forum predicts that more than 375 million professionals worldwide will need to be reskilled as a direct result of the advent of AI technology. Data analysts are not exempt from this phenomenon, so it's important to begin future proofing your career now. For example, instead of learning how to write your own code, you will instead need to focus on the strategic analysis skills required to effectively update and improve code based on its overall value to the organization.
Best Practices for Integrating AI Into Data Analysis
These are some of the best practices for integrating AI into data analysis:
Utilize AI to address specific and defined issues that exist within an organization
Integrate AI technology into existing data analysis structures, rather than trying to reinvent the wheel
Provide data analysts with advanced training and support so that they can develop the skills needed for the AI era
Be transparent about your use of AI to all business stakeholders and begin to implement it on a smaller scale to best understand and utilize this advanced technology
Project Management and AI: A New Paradigm
Project management has long been critical to the success of any organization, regardless of its industry, but according to statistics, only about 35 percent of projects initiated by organizations are successful. Recent research notes that AI technology could improve that success rate by more than 25 percent, highlighting the power of this transformative technology.
The Impact on Project Management Within Software Development
Project management, when performed effectively and efficiently, can streamline the software development process, ensuring that professionals across all industries have access to the tools and software they need to do their jobs more efficiently. By harnessing the power of AI in project management, project managers can develop software at a faster rate than ever before.
How AI Tools Are Revolutionizing Project Management Tasks
Similar to the data analysis field, AI tools are eliminating the need for project managers to complete tedious, administrative tasks while they are working. Rather, they can focus on the strategic and creative aspects of their job that they did not previously have time for on a regular basis.
Ethical Considerations and Challenges
It's easy to get caught up in the excitement and newness of AI technology, but there are ethical considerations and challenges that both data analysts and project managers should be aware of.
Navigating the Ethical Landscape of AI in Data Analysis
The International Association of Business Analytics Certification (IABAC) notes that the ethical landscape of using AI in data analysis is complex and nuanced, requiring data analysts to have ongoing conversations about the moral implications of AI technology. As data analysts and project managers begin to integrate AI technology into their daily processes, it's important to keep ethics at the forefront and have those discussions on a regular basis.
Addressing Bias and Privacy Concerns in AI-Driven Projects
Bias and privacy are two of the top ethical challenges faced by AI-driven projects. The IABAC notes that machine learning models have been shown to perpetuate bias in their algorithms, which can compromise the integrity of the data collected and the subsequent analysis. This is particularly true with predictive analytics, which relies on historic data to make data-driven insights about the future. In addition, data analysts have to prioritize individual privacy, particularly when using AI to collect sensitive data.
The Future Landscape: AI, Data Analysts, and Beyond
AI technology is no longer the technology of the future — it's here, and it's here to stay. Recognizing the powerful role that AI technology will continue to play in data analysis and project management will allow you to effectively navigate the ever-evolving landscape.
Predictions for AI’s Role in Software Development
Experts anticipate that AI will continue to play a fundamental role in software development. This highlights the need for aspiring data analysts and project managers to begin preparing now for the new responsibilities that they will take on as professionals.
Preparing for the Future: Strategies for Data Analysts and Project Managers
Data analysts and project managers can prepare for the future by:
Becoming proficient in the latest AI tools and technology
Prioritizing soft skill development, such as creativity, analysis, and collaboration
Understanding the ethical concerns that surround AI technology, and developing approaches that reduce bias and improve privacy
Learn More About the Role of AI in Project Management at Champlain College Online
Understanding the emerging AI project management trends will be critical for aspiring data analysts looking to launch their careers. At Champlain College Online, we offer a Master of Science in Business Analytics that takes a future-forward approach to this dynamic industry. Our skills-based curriculum allows students to learn how to balance the fundamentals of data science with the most advanced AI technology.
Request more information about our graduate degree programs today.
Frequently Asked Questions
Even in the age of AI technology, data analysts will play a pivotal role in the business landscape in the years ahead. Data analysts can remain relevant by prioritizing soft skill development, ensuring that they can make intuitive and insightful data-driven decisions for their organizations.
Artificial intelligence is revolutionary technology, particularly for data analysts who work in software development. The leading AI tools of today can automate some of the most time-consuming administrative tasks that data analysts are currently responsible for. This then allows them to focus on making high-level decisions and developing strategic insights for their organization.
No, data analysts will not be replaced by AI technology. Value-based decision-making, contextual communication, and creative approaches to project management are still required, even in the age of AI technology.
Artificial intelligence and other forms of machine learning technology are already impacting data analyst jobs today. However, AI is not replacing data analysts. Rather, this technology is being used to reduce the time that data analysts spend on manually collecting and analyzing data, giving them more time to focus on creativity, innovation, and collaboration. AI technology is intended to be a supplemental tool, and it is not designed to replace the skilled and intuitive human data analysts who focus on project management and business development.
