Artificial intelligence is transforming industries at a pace few could have predicted even a decade ago. Once viewed primarily as a tool for automating repetitive work, AI is now augmenting human decision-making, enhancing customer engagement, and shaping entirely new business models. But as AI’s capabilities grow, so does the importance of distinctly human skills that technology cannot easily replicate.
Euvin Naidoo, distinguished professor of practice in global accounting, risk and agility at Thunderbird School of Global Management at Arizona State University, sees this shift firsthand in his flagship course AI, Chip Strategy, and the Future of Work. As part of the Master of Leadership and Management specialization in AI, Analytics and FinTech Innovation in Business, the course regularly fills to capacity within seconds of opening registration, underscoring the urgency professionals feel in mastering both AI’s opportunities and its challenges.
“AI strategy isn’t just about adopting new tools,” Naidoo says. “It’s about execution, agile practices, and a deep understanding of human factors like trust, governance, and continuous learning.”
Beyond AI and automation: Redefining value
One of AI’s most significant impacts has been its ability to automate predictable, routine tasks. While that has led to concerns about job displacement, Naidoo believes the reality is more nuanced.
“AI can surface insights or process data,” he explains, “but it’s up to humans to interpret results, weigh ethical considerations, and connect AI solutions to real-world business needs.”
In other words, the work left for humans may be more complex, requiring judgment, creativity, and critical thinking. Leaders will need to ask the right questions, anticipate unintended consequences, and design strategies that balance technology’s capabilities with thoughtful, responsible execution.
The ‘human-plus’ advantage
In a globalized economy, success often depends as much on relationships as it does on results. AI may translate languages instantly, but it cannot yet build trust, navigate cultural nuances, or adapt a business model to a specific local market.
“Context is key, and reading it has been the hallmark of what makes good leaders great,” says Naidoo. “In this world of ‘human-plus,’ where access to knowledge on tap is becoming a commodity, the output of AI needs to be the starting point, not the end.”
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At Thunderbird, this philosophy is reinforced through diverse, hands-on projects. Students work in multicultural teams to solve problems that require both technical insight and cultural fluency, which is a combination increasingly essential in a tech-driven, interconnected world.
While AI can simulate conversation or suggest solutions, it does not truly understand human emotions, motivations, or the subtleties of trust. This is where empathy becomes a differentiator.
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“Empathy allows professionals to design AI systems that genuinely meet human needs, rather than just optimize for efficiency,” Naidoo notes.
In Thunderbird’s design thinking programs, AI tools are integrated from the outset, but the emphasis remains on storytelling and human connection. Students practice presenting case studies not just to showcase technical capabilities, but to communicate their real-world impact in ways that resonate. Naidoo often reiterates a core principle: human collective intelligence trumps artificial intelligence, because context is key.
Thinking in systems
AI doesn’t operate in a vacuum. Its implementation influences operations, ethics, customer trust, and even global energy consumption. This makes systems thinking, the ability to see connections between disparate elements, a critical leadership skill.
“From governance models to the race for computer power, AI has ripple effects that touch nearly every aspect of business and society,” Naidoo explains. “Systems thinkers can spot these effects before they become problems and design for resilience, not just efficiency.”
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At Thunderbird, students explore AI’s broader ecosystem, learning to apply agile practices such as “test and learn” approaches, adaptive planning, and ongoing skill development to ensure AI strategies remain effective over time.
Making human skills a strategic priority
For organizations, the development of human skills should not be secondary to technical training. Naidoo advocates pairing AI education with immersive experiences in design thinking, agile methodologies, and strategic frameworks like Objectives and Key Results (OKRs).
“These aren’t ‘soft’ skills,” he emphasizes. “They’re critical success factors in the age of AI.”
By creating environments that nurture storytelling, critical thinking, and cross-functional collaboration, businesses can ensure their leaders are prepared not just to work with AI, but to guide its integration in ways that build trust and drive sustainable results.
Staying relevant in the AI era
For professionals entering the workforce, or anyone seeking to remain relevant, adaptability is paramount. Naidoo offers several recommendations:
Be curious and adaptable. The half-life of knowledge is shrinking, making lifelong learning essential.
Focus on problem-solving, not just tools. AI technologies will change, but the ability to frame problems and connect solutions will remain invaluable.
Build human connection. As automation and AI grow, skills like storytelling, empathy, and leadership become more important.
Understand AI’s context. Leadership happens at the intersection of technology, strategy, governance, and ethics.
This article has been reproduced with permission from Knowledge Network, the online thought leadership platform for Thunderbird School of Global Management https://thunderbird.asu.edu/knowledge-network/
