The Boston Consulting Group Interview: Mastering AI at Work with Thoughtful Leadership

As artificial intelligence continues to reshape industries, one truth is becoming clear: AI won’t replace humans, but those who effectively harness AI will outshine those who don’t. The gap between using AI as a tool and allowing it to dominate workflows is what separates high-performing teams from others.

A revealing experiment by the Boston Consulting Group (BCG) put this into perspective. Conducted with 480 consultants, the study showed a remarkable 49% improvement in tackling complex, unfamiliar tasks when AI tools were leveraged. The message is clear: AI isn’t just a technology—it’s a game-changer for workplace productivity.

In a conversation with Vladimir Lukic, Managing Director and Senior Partner at BCG, we explore how generative AI is revolutionizing the workforce. Lukic sheds light on how non-experts are performing sophisticated tasks, how seasoned professionals are leveling up with AI, and the importance of maintaining critical thinking in AI-enhanced workflows.

Key Insights from the Interview:

AI amplifies productivity but relies on human oversight to deliver optimal results.

The “exoskeleton effect” enables both novices and experts to achieve outcomes that neither could accomplish alone.

AI tools can compress complex tasks from days to minutes, but judgment and nuance still require human input.

Leaders must engage directly with AI to truly understand its capabilities and limitations.

The ‘Exoskeleton Effect’ of AI: Empowering Workers

Vladimir Lukic, Managing Director & Senior Partner at BCG

Lukic introduces the concept of the “exoskeleton effect,” where generative AI (GenAI) acts as a supportive framework, enabling workers to achieve more than they ever could alone. This analogy perfectly captures the transformative potential of AI.

“Think of GenAI as an exoskeleton,” Lukic explains. “It allows a non-coder to write functional code. But the moment the tool is removed, that person cannot replicate the task independently because they haven’t truly learned to code.”

This duality was evident in BCG’s study. Consultants with no coding experience could generate advanced scripts using GenAI. However, their reliance on the tool meant their newfound proficiency disappeared once AI was taken out of the equation.

Interestingly, even seasoned professionals experienced significant improvements. For experts, GenAI didn’t just level the playing field; it boosted their performance to new heights. Lukic shares, 

“Our experienced data scientists became even better when using these tools. Novices saw major gains, but skilled individuals also reached higher levels of efficiency and creativity.”

Reducing Friction with AI: A Double-Edged Sword

One of GenAI’s strengths lies in its ability to interpret natural language and deliver actionable results. For instance, a user can describe a task in plain English, and the tool might generate 30 lines of Python code in seconds.

But there’s a catch. Lukic emphasizes that without a basic understanding of coding, users may struggle to validate the outputs. “AI can hand you a ready-made script, but if you don’t know how to assess its correctness, you’ll be stuck when it doesn’t work as expected.”

This highlights a core challenge: relying entirely on AI can hinder critical thinking and problem-solving skills.

The Risk of Outsourcing Everything to AI

Leaning too heavily on AI may erode fundamental skills over time. According to Lukic, organizations need to adopt workflows that integrate purposeful human involvement to counterbalance this risk.

“We advise clients not to automate everything,” he says. 

“Introduce purposeful steps where employees must engage critically with AI outputs. For example, junior staff might need to break down AI-generated code or seek managerial review before finalizing tasks. This approach nurtures intuition and ensures skills don’t atrophy.”

AI can generate a broad overview of data, but humans remain essential for interpreting subtle nuances and drawing creative connections. Lukic gives an example: “When summarizing 50 interviews, AI provided a more comprehensive initial list of themes than any single analyst. But it still took a human to catch the nuances it missed.”

Why Processes Matter as Much as Technology

The BCG experiment underscores a crucial lesson: leveraging AI isn’t just about adopting the latest tools. It requires rethinking job roles, workflows, and performance metrics.

Lukic suggests that leaders need to focus on creating “AI synergy.” This means hiring individuals who can effectively collaborate with AI rather than relying solely on traditional skillsets. “It’s not just about how many coders you hire—it’s about finding people who can maximize AI’s potential,” he explains.

He also warns against pairing modern tools with outdated processes. 

“We’ve seen tasks that used to take ten days shrink to two minutes with AI. But if you maintain the same approvals and committees, you’re back to a ten-day process. That’s wasted potential.”

The Role of Leadership in AI Adoption

For AI to truly transform an organization, top leaders must take a hands-on approach. Lukic stresses, 

“Executives can’t just issue directives like ‘use AI’ without trying it themselves. Whether it’s drafting a board memo or analyzing data, leaders need firsthand experience to understand AI’s strengths and limitations.”

However, leadership must also address two significant risks:

1. Over-reliance on AI: Employees may lose critical skills that AI handles, which could weaken the workforce over time.

2. Unregulated AI use: If organizations don’t provide safe, responsible tools, employees may turn to public platforms, risking data breaches and compliance issues.

The Bigger Picture: A New Definition of Skill

Lukic’s insights reveal a paradigm shift in how we define workplace skills. Generative AI expands what individuals can achieve, but it also exposes a gap between short-term capability gains and long-term skill development.

By designing thoughtful processes, fostering collaboration between humans and AI, and prioritizing hands-on leadership, organizations can unlock the full potential of AI—while ensuring the human element remains at the core.

Conclusion:

Generative AI is far more than a productivity tool; it’s a catalyst for redefining work itself. But as organizations embrace this technology, they must also safeguard creativity, intuition, and critical thinking. By balancing automation with human oversight, leaders can create a future where AI and human ingenuity thrive together.