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 the way in which 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 yes, management consulting. But many of the tasks they undertake – from responding to emails to data entry to basic number-crunching and research – are considered by many of them to be burdens on their work productivity.

As AI increasingly performs such tasks, human workers will increasingly be valued 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 to bring these human attributes to their work and work 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 aspects of their jobs that they find most rewarding and that capitalise on their human strengths.

Knowledge workers who fail to see this opportunity and neglect 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 than the converse. Proactive and successful adoption of AI is a leadership challenge.

Those that most need to lead on AI (CEOs, executives, managers) are probably the least likely to do so. The status quo has served them well to this point. However, the future requires them to adapt, and 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”. It is the leaders who encourage smart experimentation, reflection and adaptation that will stand out because they will pioneer new ways of working. In doing so, they will equip their teams and organisations to thrive.

Across sectors, we are amid a reimagining of knowledge work that will change how we think about 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 to move through the risks of AI and towards knowledge industries that lifts 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.

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Connect with David Diviny and Sophie O'Connor on LinkedIn.