Human + AI: The new equation for digital workforce transformation

In an era of technological advancement, a surprising shift has emerged in how organizations approach analytical skills development. 

Drawing from data analysis of 25,975 learners across 194 companies, Lepaya's The State of Skills 2025 report revealed a significant decline in analytical thinking training—dropping from 15,748 hours in 2023 to 11,813 hours in 2024, a 25% decrease that pushed it from third to fifth place among the most trained skills.

This shift seems contradictory at first glance to current workplace priorities. According to the Evolution of Skills report, HR leaders and employees identified digital transformation as the biggest catalyst for change last year, yet organizations are simultaneously reducing their investment in analytical training. Why?

The truth is that this decline doesn't signal the diminished importance of analytical thinking. Rather, it reflects a transformation in how these skills are developed and applied in today's workplace. As AI tools rapidly evolve, organizations are reconsidering which analytical capabilities remain uniquely human—and which can be augmented or even replaced by technology.

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Digital workforce transformation: When machines think faster

The analytical landscape has undergone a dramatic shift in recent years. When ChatGPT burst onto the scene in late 2022, most businesses were still figuring out how to incorporate this powerful technology into their workflows. Fast forward to 2024, and the transformation is striking—71% of global companies now use generative AI regularly for various tasks.

This rapid adoption is changing how organizations approach analytical challenges. Modern AI training and machine learning tools can now process massive datasets, identify complex patterns, and generate insights with greater speed and often higher accuracy than humans.

Tasks that once required specialized skills—like data visualization, trend identification, or statistical analysis—are increasingly being automated. This frees human analysts from routine work while raising important questions about which skills remain essential.

From gradual shifts to rapid transformation

This evolution isn't entirely new.

Throughout history, technological advancements have always reshaped which skills we value and develop. For example, when calculators emerged, we didn't abandon mathematical thinking—we elevated it to focus on problem formulation rather than computation. Similarly, AI isn't eliminating analytical thinking but redefining which aspects deserve our attention and development resources.

The difference lies in the pace of change. While previous technological transitions unfolded over decades, allowing gradual adaptation of educational and training systems, AI is transforming analytical work in just a few years. This requires organizations to rapidly redefine their employee development priorities and digital readiness strategies.

For organizations navigating this shift, the challenge isn't whether to embrace AI—that ship has already sailed. The real strategic question is how to invest in analytical capabilities that remain distinctly human while leveraging AI's power.

This balance explains why companies have reduced analytical training hours despite digital transformation being the top catalyst for workplace change. They aren't abandoning analytical thinking—they're evolving their approach to reflect a new reality where humans and AI must complement each other to achieve outcomes neither could reach alone.

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AI training for tomorrow: Developing a hybrid mindset

"To keep up with future workplace changes, training in Analytical Thinking should evolve towards promoting a hybrid mindset—where humans collaborate effectively with AI to drive business decisions," explains Simon Brown, Training Project Manager at Mirakl. "Emphasis should be placed on how to use AI tools effectively, interpret AI's conclusions, and challenge assumptions that may be embedded in the data or AI models."

This hybrid mindset represents a shift in what it means to be analytically skilled in 2025 and beyond.

While AI excels at processing enormous datasets and identifying patterns with incredible precision, it still lacks the contextual understanding, ethical judgment, and creative insight that humans naturally bring to analytical challenges.

Thus, today's analytical professionals must form a strategic partnership with AI, knowing exactly when to let algorithms take the lead and when human judgment must prevail.

Balancing AI and human skills

In practice, this approach means analytical thinking training is less about teaching people to create spreadsheets or run statistical models (tasks AI excels at) and more about developing uniquely human capabilities that complement AI's strengths.

The modern analytical thinker must excel at:

• Framing problems in ways that AI can effectively address
• Identifying potential ethical concerns or biases in automated analyses
• Translating technical findings into meaningful business actions
• Understanding which decisions should remain in human hands

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Building digital readiness for 2025 and beyond

The path forward isn't about choosing between human analysts or AI—it's about creating powerful synergies between them. To do this, companies need to reshape how they develop their analytical teams by:

• Determining which tasks require human expertise versus AI automation, and reshaping roles to leverage the strengths of both. Let machines handle data processing while humans focus on defining problems, providing ethical guidance, and applying insights creatively.
• Integrating AI training into learning programs, teaching employees to use these systems as extensions of their skills rather than treating humans and AI as separate domains.
• Developing clear guidelines for when algorithms should lead analysis versus when human oversight is needed, especially for high-stakes decisions.

The future belongs to those who strike the right balance—neither trying to compete with AI at tasks where it excels nor becoming too dependent on technology without proper oversight. By focusing on uniquely human abilities while leveraging AI's strengths, companies can turn the current technological disruption into a future competitive advantage.

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