How can companies equip their employees with the digital skills for tomorrow's AI-powered workplace?

While our business environment has been scarred by the effects of economic and geopolitical uncertainty over the past few years, the current AI movement is a rocket ship to significant transformation that will accelerate new opportunities. It becomes.

Adding to this AI buzz is the exponential growth of data within every enterprise. According to research, the world's data creation volume is predicted to increase to more than 180 zettabytes by 2025. But in this age of intelligence, it's no longer a question of how much data one company can generate, but how it can be used to drive decision-making while improving the skills of its employees. is becoming important. Asking the right questions to get the right answers.

A recent Alteryx survey of 300 corporate board members from four countries, including Australia, echoed this fear, finding that the sudden rise of generative AI has surpassed the hype and become the focal point for businesses. It has been confirmed that there is. Among board members surveyed, 43% of Australians said generative AI is currently their “number one priority” and 39% are experimenting with generative AI on a specific project or department. is.

Whether you're a CFO looking to accelerate time to quarterly deadlines or a supply chain manager looking to optimize complex logistics, today's businesses are moving from traditional databases and applications to modern cloud data warehouses and platforms. , I am getting data from multiple input sources. This suggests that AI-driven automation will continue to be a key feature of future enterprises, and as more organizations seek to unlock the potential of these innovations, data and AI-related skills will be perfected. create a storm and reshape the roles and skill base needed for the workforce of the future. .

The World Economic Forum further underlines this in its Future of Work Report 2023, stating that the roles of “AI and machine learning specialists” and “data analysts and scientists” will be the most popular between 2023 and 2027. It emphasizes that it will be in the top 10 fastest growing jobs.

Whether greeted with excitement or trepidation, it's clear that AI is expected to transform the business landscape over the next three years. Alteryx's recent study on the enterprise of the future reveals that organizations in Australia, India, Japan and Singapore have a strong appetite for AI and automation. In fact, nearly nine in 10 (86%) say AI is already impacting what their organization can accomplish.

No matter what the future holds, successfully integrating generative AI into every aspect of an organization requires a business-wide approach to data-driven decision-making that empowers the entire workforce to get the most out of the technology. is. That's why business and technology leaders must build for the future now. By working with HR managers to develop a skills stack that supports the technology stack, organizations can leverage current and future AI capabilities, all powered by data.

Laying the foundation for an AI-powered future

Data is dirty, it's everywhere, and the amount of it is growing. Investing in the technology stack ecosystem alone will not be enough to turn this increasing volume and variety of data into business opportunities. Rather than facilitating the extraction of value from data at the speed and scale required for real-time intelligence, it silos processes to a select few. The inability to extract meaningful insights from data at scale impedes the ability to obtain the decision intelligence needed to meet evolving business objectives.

But the key is to recognize that every company has a large pool of untapped data talent that can reach its full potential.

While AI will shape future enterprise operations and performance, the current skills gap poses a significant barrier that will stall this effort if left unfilled. To prepare for this increasingly complex data-driven future, we need non-technical software that moves beyond the exclusive domain of traditional data analysts and enables a broader range of individuals to contribute to insightful decision-making. Emphasis should be placed on developing his skills.

Building a data literate workforce from within

As the use of AI and large language model (LLM) technologies accelerates across enterprises, it is important that the entire individual understands the art of using these advanced tools to extract valuable insights. According to Gartner's 2025 predictions, the most sought-after skills in the data and analytics talent market will be analytical skills and soft skills. Cultivating curiosity about data and analytical thinking are fundamental tools for developing the next generation of data science talent. However, transferable soft skills such as collaboration, curiosity, creative problem solving, and communication are equally vital.

For example, research from Alteryx found that 76% of Australian business leaders say it is important for employees to have multiple skills rather than specializing in one area. While hard skills in areas like AI and ML remain important, the right AI tools can help employees manage the increasing amount and variety of data and find the competitive edge your organization needs. Masu.

Employees with both technical expertise and soft skills can be extremely valuable to a company, even if that value is not immediately obvious. The target audience is mid-career professionals of all educational backgrounds and ages, those looking to improve their skills to advance their careers, and those aiming to return to work. Their unique understanding of the broader business landscape is their most valuable asset. This will enable you to demonstrate your ability to transform data into insights that inform critical business decisions, ask the right questions, implement effective data methodologies, and produce actionable results.

While this expertise may not fit into traditional thinking about a data scientist's skillset, it serves as the linchpin for unlocking valuable insights.

Shaping the workforce for tomorrow’s AI-powered workplace

So how can companies upskill their employees with the critical data literacy and expertise needed to deliver data-driven insights? Business leaders must engage and encourage their employees. , you should follow these steps to improve your skills.

1. Assess your current technical and soft skills. Creative problem solving is key. Align training to your employees' skill sets, giving them flexibility and time to learn.
2. Leverage the cloud to democratize data and analytics access. Simplify and enable access to data and tools to encourage more learning time.
3. Provide easy-to-use self-service tools and data access. Advances in no-code/low-code self-service analytics enable anyone, regardless of qualifications, to solve business challenges and provide decision intelligence.
4. Treat upskilling as an investment. Upskilling creates a more inclusive workplace and a culture where everyone can use data to make strategic decisions.
5. Let's have fun: Gamifying the learning experience and incorporating hands-on activities like datathons makes upskilling engaging and motivates team members to keep learning.

By following these steps, your employees will have the data and analytical skills they need to drive change within your company. If you ignore them, you risk falling behind the competition.

Humanity becomes more important in the world of AI