As industries across the globe accelerate their digital transformation, the technology skills gap continues to widen. Particularly in the fields of data analytics and AI development. Businesses increasingly rely on data-driven decision-making. Yet many employees lack the technical skills required to interpret complex datasets, identify insights, and act on them effectively. To address this challenge, Amazon Web Services (AWS) has introduced Amazon Q in QuickSight. A new generative AI platform that empowers non-technical users to perform sophisticated data analysis simply by asking questions in natural language.
Amazon Q is designed to democratise data access across organisations. Rather than relying solely on data scientists or analysts to extract insights. Employees at any level can now query company data conversationally — no code, SQL, or dashboard-building experience required.
“We’re at the beginning of a workplace transformation powered by AI agents,” said Dilip Kumar, VP of Amazon Q Business at AWS. “With Amazon Q in QuickSight, we’re removing technical barriers and enabling any employee to explore data deeply, unlock insights, and make better decisions — faster than ever before.”
The platform’s “scenarios” capability uses a generative AI agent to guide users through common analytical tasks, such as identifying operational bottlenecks or forecasting trends. This opens the door for employees with zero background in analytics to contribute to strategic decision-making processes. Reducing dependency on specialist teams and increasing organisational agility.
One company already reaping the benefits is BMW. Previously, the automotive giant relied on manual dashboards and spreadsheets to investigate vehicle stock delays and supply chain inefficiencies. That process has been transformed by Amazon Q in QuickSight.
Now, BMW employees can use natural language queries to manage inventory across thousands of vehicles, significantly accelerating data workflows.
“We integrated QuickSight into our Cloud Data Hub to improve transparency and share insights more effectively,” explained Ruben Simon, Head of Product Management, Cloud Data Hub at BMW.
Following early success, BMW is exploring ways to roll out Amazon Q across other departments to further streamline operations and enhance company-wide decision-making.
While Amazon Q in QuickSight is a powerful solution, it also highlights a bigger trend. AI is becoming a key enabler of upskilling in the modern workplace.
From automating repetitive tasks to breaking down complex analysis into manageable steps, AI tools are helping employees build confidence with data, even if they’ve never worked in technical roles before.
According to DataCamp’s 2024 State of Data & AI Literacy Report, 62% of business leaders say AI literacy is now essential to their teams’ daily responsibilities. Four of the seven fastest-growing job skills are directly linked to data and AI proficiency, the report found.
This transformation has caught the attention of global thought leaders.
Speaking at the World Economic Forum in Davos, Igor Tulchinsky, CEO of quantitative investment firm WorldQuant, emphasised the need to reskill workers for an AI-powered future.
“As AI adoption increases, humans are essential to guiding how we use these technologies,” Tulchinsky said. “We have an obligation to reskill our talent so they can succeed in today’s rapidly evolving environment.”
Tulchinsky estimates that up to 40% of today’s workforce may need reskilling in the next three years due to AI and automation. Yet he views this not as a threat, but as an opportunity to create new pathways into high-value, skills-based jobs.
He proposes a strategic, three-pronged approach:
- Invest in human capital
- Integrate reskilling into change management efforts
- Use AI tools to power personalised education and training
“Giving employees the chance to reskill will allow them to better leverage AI,” he said. “This drives business value, enhances efficiency, and shapes the future of work.”
