AI hesitancy needs to give way to leadership in the workplace

The rise of generative AI raises questions about the resilience and adaptability of the knowledge workforce, and many of these challenges go beyond mere technological adaptation. But the integration of AI also presents an opportunity for professionals to find greater meaning in work.

By delegating routine tasks to AI, knowledge workers can focus on what they find most rewarding in their jobs. In this rapidly changing landscape, experimentation and curiosity are paramount. Leaders who encourage experimentation and pioneer new ways of working alongside AI will equip their teams and organisations to thrive.

Amid the daily firehose of Generative AI announcements and speculation, there remains a surprisingly steady approach to knowledge work. Rapid developments in Generative AI highlight a latent complacency in leaders and knowledge workers about how work gets done.

Knowledge workers, who deal with the creation, distribution and application of knowledge, comprise more than half of the Australian workforce. They work in sectors including journalism, public service, higher education and management consulting. But many of their tasks – from email responses to data entry to basic number-crunching and research – are often seen as work productivity burdens.

As AI increasingly performs these tasks, human workers will be valued more for their uniquely human qualities: empathy, critical thinking, problem-solving, knowledge discovery and curation, active listening and the ability to engage in meaningful face-to-face interactions. Their competitive advantage will be in applying these human attributes and working productively in tandem with AI.

The integration of AI into knowledge work presents a generational opportunity for professionals to redefine their roles and find greater meaning in their work. By delegating routine tasks to AI, knowledge workers can focus on the most rewarding aspects of their jobs that capitalise on their human strengths.

Knowledge workers who fail to adapt and hone their skills are likely to face an awakening. As researcher Andy Matuschak has observed, unlike top-tier athletes or musicians, with their meticulous drills and scales, knowledge workers rarely engage in what he calls “deliberate practice”.

"Knowledge workers seem surprisingly unserious about honing fundamental skills," he has said, “[and] generally don’t seem to pursue a serious program of improving in those core skills”. The challenge posed by AI to such workers is not primarily a technological one, but rather one that raises questions about the resilience and adaptability of the knowledge workforce.

A workforce shift of this scale will not happen magically. A recent Essential Poll found that twice as many people believe the risks of AI outweigh the opportunities. Proactive and successful adoption of AI is a leadership challenge.

Those who most need to lead on AI (CEOs, executives and managers) are probably the least likely to do so. The status quo has served them well to this point, but the future requires them to adapt. They may not be able to do so by relying on delegation or prior experience.

A recent Harvard Business School study found that “juniors may fail to be a source of expertise in the use of emerging technologies for more senior professionals”. Leaders who encourage smart experimentation, reflection and adaptation will stand out by pioneering new ways of working. In doing so, they will equip their teams and organisations to thrive.

We are currently reimagining knowledge work across sectors that will change how we approach education, career management and professional development for knowledge workers.

Schools and universities will need to adapt their curricula to work with AI. Workplaces must redesign their systems and processes to enable employees to work alongside the technology. Together, these shifts will allow knowledge workers to develop meta-skills rooted in deep work, knowledge creation and management, and continuous learning.

Leaders who are curious and encourage “deliberate practice” will lead the way. It is their leadership that will help us navigate the risks of AI and towards knowledge industries that lift us up as individuals, organisations and as a society. The costliest mistake a leader can make is to perceive the rise of Generative AI as a technical problem, rather than an adaptive leadership challenge.