For years, companies have talked about digital transformation as something largely driven by technology departments. Artificial intelligence is changing that. It is no longer simply a technology question; it is beginning to reshape how companies organise themselves, how decisions are made and what they expect from their people.

For Madelynn Loo, Chief Executive Officer of Singapore-headquartered La Royale Group, that shift represents one of the most exciting changes taking place in business today.

Before joining La Royale Group in 2025, Madelynn spent much of her career at technology companies including Uber and TikTok, working across strategy, operations and customer experience in Europe and Asia-Pacific. She believes some of the operating principles that defined the last generation of technology companies are now moving far beyond the technology sector.

“Technology companies taught a generation of leaders to think differently about scale,” Madelynn says. “You learn to operate with speed, test rather than debate endlessly, use data to challenge assumptions and constantly ask what can be simplified or automated. AI is accelerating that way of working.”

From technology adoption to operating-model change 

The biggest opportunity from AI, Madelynn argues, is not simply replacing individual tasks. It is allowing companies to reconsider how work is organised in the first place.

Functions that once required significant administrative capacity can increasingly be supported by AI. Analysis can happen faster, small teams can process far more information and employees can automate repetitive work giving them more time for decisions, relationships and creative problem-solving.

For established businesses, that creates an opportunity to adopt some of the characteristics historically associated with high-growth technology companies: smaller teams, faster execution, greater individual ownership and more direct access to information.

“The interesting question for CEOs is not how many tasks AI can perform,” Madelynn says. “It is what your organisation could look like if people were no longer spending so much of their time performing those tasks.”

Adding AI tools to an existing organisation may create incremental productivity. Redesigning workflows around what people and machines each do best can create something fundamentally different. Madelynn sees this increasingly affecting businesses outside the traditional technology sector.

“We are going to see more leaders with technology backgrounds moving into traditional industries and bringing those operating principles with them,” she says. “Not because every company needs to behave like a Silicon Valley startup, but because speed, adaptability and intelligent use of technology are becoming competitive advantages in almost every industry.”

The human factor becomes more important, not less 

However, there is another side to that transition. Many of the tasks AI performs particularly well are also tasks historically given to people at the beginning of their careers: basic analysis, first drafts, research, coordination, customer support and administrative work.

Removing repetitive work is positive, but companies also need to consider what those jobs were doing beyond producing an output. They were giving young people exposure.

“Early in your career, you learn by being close to the work,” Madelynn says. “You see customers, you make mistakes, you watch how experienced people make decisions and eventually you develop your own judgement. If AI removes some of those traditional entry points, we need to be much more deliberate about how the next generation gets that exposure.”

For Madelynn, this is not an argument for protecting jobs that technology can perform more effectively. It is an argument for redesigning how companies develop people.

Graduates entering the workforce today may spend less time producing basic reports or manually processing information. In return, companies can give them earlier exposure to problem-solving, customers and decisions, supported by technology that dramatically increases what an individual can accomplish.

That could ultimately accelerate careers rather than restrict them.

“A graduate working effectively with AI potentially has capabilities that would have required a much more experienced team not very long ago,” Madelynn says. “That is incredibly exciting. But access to information is not the same as judgement. We still have to teach people how to think, challenge, communicate and make decisions.”

A different kind of graduate workforce 

That means the definition of entry-level talent may also need to change. Technical proficiency will matter, but so will capabilities that are harder to automate: curiosity, judgement, communication, creativity, adaptability and the ability to understand people.

The responsibility cannot sit entirely with universities or graduates themselves. Employers that expect young people to arrive “AI-ready” while simultaneously removing the environments in which they traditionally learned risk creating their own talent shortage.

Instead, Madelynn believes companies should treat talent development as part of their AI strategy.

“If AI gives us productivity, some of that productivity should allow us to give younger people better experiences,” she says. “Give them meaningful problems earlier. Let them sit in important discussions. Let them understand why a decision was made rather than simply asking them to execute it.”

This approach is particularly visible in smaller businesses, where employees often have broader responsibilities by necessity. At La Royale Group, which both invests in businesses and builds new ventures, Madelynn says small teams have reinforced her belief that responsibility can accelerate development.

“When teams are lean, people cannot spend two years observing from the sidelines,” she says. “They contribute earlier. AI can give them leverage, but the accountability still belongs to the person.”

Building the next generation of companies – and leaders 

The workforce debate around artificial intelligence is often framed around a single question: which jobs will disappear? Madelynn believes that framing is too narrow.

The more consequential question may be what new organisations emerge when technology allows people to work differently. Some companies will use AI primarily to reduce cost. Others will use it to build faster, flatter and more capable organisations. The distinction may become increasingly important as technology-led operating practices spread into industries that historically changed more slowly.

But whichever model emerges, businesses will continue to depend on people.

“AI will become extraordinarily capable, but businesses are still ultimately built around human needs,” Madelynn says. “Customers are human. Teams are human. Leadership is human. Judgement, trust, creativity and relationships still matter.”

The opportunity, therefore, is not to choose between technology and people. It is to build organisations where technology allows people to contribute at a higher level and to make sure the next generation is equipped to lead them.

“The companies that get this right will not just become more efficient,” Madelynn says. “They will develop a generation of people who understand how to combine technology with judgement. I think that will be one of the defining leadership capabilities of the next decade.”

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