Small teams as change catalysts: harnessing AI for organisational transformation
Generative AI can strengthen small teams and facilitate the effective establishment of a learning organisation.
First published on apolitical.
The problem: Public sector leaders must balance legacy processes with new, adaptive approaches to keep up with the pace of technological and societal change and the expectations of the people they serve.
Why it matters: Without this balance, public organisations risk falling behind, becoming less effective, and failing to meet the needs of the people they serve.
The solution: Individuals and small teams are essential ‘shock absorbers’ during change, balancing continuity with progress. Learning and adaptation flourish in small groups. Augmented by generative AI, small teams can drive organisational transformation.
Questions about the speed, capacity, and capabilities needed to maintain the strategic edge of public services are often framed in terms of technology: generative AI, machine learning, and, on the horizon, quantum computing. However, the core of public service capability lies in the complex, vital, unpredictable, and fragile system at the heart of innovation—people.
People make choices, navigate uncertainty, strive to implement change, resist change, and sometimes achieve the impossible despite the obstacles.
As generative AI transforms the workplace, leaders must focus on small team contributions to drive organisational transformation.
Surveys of CEOs and executives indicate that adaptability is essential for future business success. For example, 90% of CEOs believe their companies must become more agile to thrive in the digital age, while 85% of executives consider an adaptable workforce crucial.
The desire for ‘adaptability’ and an ‘adaptable workforce’ raises the question: How do people and small teams contribute to organisational adaptability?
A revolution in transformation
The real challenge of change is not shaping the future but letting go of comfortable and familiar routines from the past.
Public service and business leaders who seek agility and adaptability are encouraged to focus on implementing the ‘new’ while discarding the ‘old’. However, as many change leaders have learned, the ‘old’ is not easily left behind.
However, if organisational change does not alter the underlying thought patterns that support today’s practice, those patterns will continue to repeat despite the new changes. Transformation and change agendas compete with our organisation’s human elements—history, legacy, culture, and behaviour.
Public service initiatives focused on transformation through the quick adoption and integration of generative AI must tackle behaviours, practices, and mindsets that conflict with this new technology.
One idea that AI-augmented workplaces will challenge is that senior leaders drive organisational transformation from the top down. Generative AI opens up the possibility of bottom-up, small-group transformation.
People as buffers of uncertainty
Within all organisations (public and private sector), individuals and teams serve as the shock absorbers of change, navigating the tension between adopting new technologies and ensuring operational continuity.
The workforce navigates the mismatches and confusion as tensions emerge between the advantages offered by new technologies and the ingrained routines of existing processes, practices, and protocols—the organisational culture.
Individuals and small groups serve as crucial buffers within organisations, navigating the divide between the potential of new technologies and existing management practices. The degree of adoption of any new technology is consistently shaped through social negotiation within and between these small groups.
Small groups experience the uncertainty of change most directly and are ideally suited to manage the balance between continuity and innovation.
Small teams enable the learning organisation
AI enhances the agility of small teams by providing tools that allow team members to easily access information that was once hard to find. This development has democratised the ability to identify trends, anticipate outcomes, and adjust strategies, enabling team leaders to attain the flexibility and responsiveness sought by senior executives.
The concept of a ‘learning organisation’ has been a long-standing goal for senior leaders. It is based on the belief that learning fosters the ability for ongoing transformation through both individual and organisational growth. However, in reality, it has turned into more of a metaphor than a tangible practice. However, the central idea remains that team learning capabilities are crucial to organisational performance.
Generative AI can strengthen small teams and facilitate the effective establishment of a learning organisation. By augmenting small teams’ ability to analyse and interpret information, AI empowers them to access new insights that enhance individual and collective performance. Additionally, generative AI allows for quick adaptation to organisation-wide governance and coordination changes by enabling efficient resource reallocation.
Generative AI's advantages are frequently highlighted, such as its ability to automate mundane tasks, allowing individuals to focus on creative and strategic pursuits. Nonetheless, a more profound benefit might lie in its ability to democratise learning. An often-overlooked advantage of generative AI is its potential to 'raise all the boats’, thereby enabling small teams to become central players in delivering organisational change.
Challenges for enterprise leaders
Bottom-up, small-group transformation empowered by generative AI poses problems for leaders who are accustomed to a planned and coordinated top-down approach. The leadership shift is from managing the activity to enabling the system.
Transformation and leadership should focus on removing barriers, such as constraints that can hinder the team's capacity to experiment with and implement AI solutions effectively.
Leaders should ensure that teams can acquire new skills and knowledge to use AI tools effectively.
AI’s reliance on large volumes of high-quality data suggests a focus on data quality and management.
Learning can be time-consuming. The need for upskilling can divert focus from other critical tasks, so leaders must pay attention to managing the speed of progress and workload prioritisation.
Integrating AI already disrupts established workflows and roles. Overcoming the new sources of organisational friction accompanying the adoption of AI will require reconfiguring organisational systems and practices.
History, legacy, culture, and behaviour remain constraints on the capacity of organisations to change. As always, leadership attention on fostering the emerging practices that are the foundation of the evolving culture will be a constant activity.
Small teams catalyse change
The rapid advancement of generative AI and machine learning technologies, which adopt a fundamentally different organisational philosophy, presents a challenge for the public sector. In response, public sector leaders are rapidly experimenting with technologies to find the best path forward.
People, technology, and organisations are co-evolving, raising the question: What facilitates swift organisational and social change to enhance the adoption and spread of these new technologies in ways that benefit the government and the community?
Small groups are the foundation for resolving contradictions, organisational transformation, and change. The exchange of information, attitudes, values, beliefs, and emotions is sharpest within and between small groups. Meaning is created in small groups and shared through their relationships and interactions. Thus, small groups are vehicles for maintaining stability in the face of change or agents for embracing change. Augmented by generative AI, they are the system from which culture and change emerge.
