Avinash Tripathi is an analytical evangelist, thought leader, and keynote speaker with over 20 years of experience in higher education.
As we approach the halfway point of 2024, we can look back and see that the last eighteen months have brought a massive shift in the field of data and analytics, particularly due to AI.
The substantial investments in AI startups and the global data analytics market are indicative of what is to come; venture capitalists have injected $42.5 billion in AI startups last year, according to CB Insights, cited by the The Financial Times.
This trend is corroborated by the Statista 2023 survey which shows that data and analytics as Sector of interest for business investment. In fact, the global data analytics market is expected to expand, with projections showing that it will grow from $61.44 billion in 2023 to $581.34 billion in 2033.
These substantial investments are leading to an increase in data job opportunities, and data roles are set to evolve. The outlook looks incredibly promising for careers in analytics and data science, driven by the growing volume of data and the critical need to derive insights from it.
Several data-related fields are expected to grow relative to general labor market trends. According to the U.S. Bureau of Labor Statistics, for example, there is a growth forecast of 1.5%. 35% increase in data scientist positions between 2022 and 2032. The need for professionals exceeds the workforce, and this trend does not appear likely to change.
The Human Advantage in the Age of AI: Why Analysts Will Thrive, Not Be Replaced
The future lies at the dynamic intersection of data analytics and AI. While AI will undoubtedly transform the way we analyze data, there will be no replacement for human interpretation, strategic thinking, and deep analysis.
Here are some key trends that will shape data science roles in the years to come.
Beyond Data Puppets: Analysts as Navigators, Not Processors
Analysts will remain essential in guiding businesses through an ever-growing ocean of data. Their role will evolve from that of data processor to that of data manager. data storytellersby uncovering valuable insights and making data-informed decisions. The key will be to avoid becoming overwhelmed by information and AI, focusing instead on critical thinking and communication.
The Rise of AI Collaboration: New Roles and a Human-AI Team
The growth of AI and machine learning (ML) will provide opportunities to automate tasks such as cleaning large datasets, managing data pipelines, provisioning, model training, and basic analytics. This will free up analysts and engineers to focus on higher-value activities such as problem formulation, feature selection, and model interpretation.
An increase in new positions designed to facilitate this partnership is likely, including AI trainers, AI operations specialists, and roles such as AI ethicists and data privacy experts who understand important compliance with data regulations.
Specialization is essential: the skills sought for the future
As specific tasks are automated, demand for analysts with specialized skills could skyrocket. With data becoming an integral part of every role, there could be a growing desire to use data strategically to solve industry-specific problems.
Analysts with deep expertise in areas such as healthcare, education or finance can be essential for exploring complex problems.
Emphasize the importance of communication and collaboration
As data careers evolve, success in these fields will be about more than just technical prowess. Effective communication and collaboration will be essential to navigate the rise of artificial intelligence (AI) in organizations, including at the executive level.
Algorithms, often complex “black boxes,” can be biased and favor their training data. Interpersonal and cross-functional collaboration can help mitigate these biases and reveal new possibilities. Storytelling, cultural sensitivity, virtual presence, and inclusive communication for potentially dispersed teams will be increasingly valued.
Champions of ethical and responsible data
As Data privacy laws are evolving And concerns about bias In growing AI systems, analytics professionals will be involved in advocating for proper data management.
The growing focus on data security, product development innovation, and AI governance will create opportunities for roles such as AI governance specialists and data security managers. As the focus on data protection and regulatory compliance grows, all analysts will need to have knowledge of data security and applicable laws.
Continuous learning: a key to success
The fields of data science and advanced analytics are constantly evolving, with new technologies emerging regularly.
To succeed in this environment, data professionals must adopt a growth mindset with an emphasis on continuous learning. This means constantly upskilling, staying abreast of emerging technologies, and adapting to industry changes.
Specialization is valuable, especially when it’s built on a solid foundation. While advanced courses in cloud computing, data mining, big data processing, and specific programming languages like R, Python, or Java can give you a competitive edge, a solid foundational education will allow you to specialize more effectively.
This training focuses on fundamental mathematics, statistics, data science, and business analytics. It provides the framework needed to understand complex algorithms and effectively interpret their results. Over the next 10 years, data analysts who can seamlessly combine a strong foundation with AI/ML expertise, excellent communication skills, and specific industry knowledge will likely be at the forefront of data-driven advancements.
The Future of Data is Human: Communication, Collaboration and Continuous Learning
Following last year’s “Great Resignation,” a study by the University of Phoenix Career Institute® found that we have reached “a moment of talent stagnation— for both employers and workers.” (Disclosure: I am the vice president of analytics at the University of Phoenix.) While workers are optimistic about their careers, they feel underappreciated and stuck.
Companies are struggling to find talent externally, but there’s a disconnect between the two: Employees say they lack opportunities for growth within their companies, contradicting employers’ claims that internal advancement opportunities are plentiful. The solution? Invest in your current workforce: It’s cheaper and more effective than external recruiting in the long run.
For data professionals, developing skills in using AI tools and leveraging their capabilities to increase their expertise will be essential. The future of work requires a focus on upskilling and complementing human capabilities with AI, fostering a partnership that drives innovation and growth in a data-driven economy.
Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs, and technology leaders. Am I eligible?
