Page 27 - Policy benchmarks for digital transformation of people-centred cities

5 Conclusion

At a time when digital transformation is reshaping urban landscapes, the Dynamic Policy Maturity
Benchmark Model represents a crucial step forward in the governance of smart, sustainable cities.
This model addresses the inherent challenge of keeping policy frameworks relevant and effective
amidst rapid technological advancements. By adopting a dynamic, iterative approach to policy
benchmarking, it ensures that policies evolve continuously to meet the needs of citizens and the
environment.

The model's emphasis on leveraging Key Performance Indicators (KPIs) provides a structured
mechanism for assessing and adjusting policies, ensuring they remain aligned with the goals of
economic, environmental, and social sustainability. The five levels of policy maturity defined within
the model offer a clear roadmap for policy evolution, from existing policies to those that are fully
sustainable and responsive to the needs of people-centred cities.

The case study involving the introduction of AI in smart city services underscores the model's
practical applicability. It demonstrates how dynamic benchmarking can identify gaps in existing
policies and trigger iterative adjustments to align with the city's values and objectives. This not
only enhances the sustainability and inclusivity of urban development but also positions cities to
leverage emerging technologies for the greater good.

In conclusion, the Dynamic Policy Maturity Benchmark Model provides a robust framework for
the continuous evolution of policies in the context of digital transformation. By fostering a culture
of continuous policy improvement and stakeholder engagement, it ensures that policies remain
relevant and effective, ultimately contributing to the development of smart, sustainable cities that
prioritize the well-being and inclusivity of their residents.

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