By Robert Oates, CEO of leading UK ecology consultancy, Arbtech

Having spent the last few weeks providing responses to the Government’s Planning Reform working paper ‘Development and Nature Recovery’ both in writing and in person at the House of Lords, one opportunity we keep pressing is the need for greater knowledge sharing and the exploitation of technology to drive decision quality. Any new measures to assist the process of simplifying the ecology workstream for developers to speed up housing delivery will depend heavily on the readiness of accurate data, and AI certainly has a part to play.

Having worked with tens of thousands of developers around the UK for the past 20 years, we know that it’s not necessarily the requirement for ecological assessments that causes frustration, but rather the delays and uncertainty that often accompanies the processing of assessments once they have been submitted. In order for the right decisions to be made there has to be detailed baseline data across planning authorities so that the impacts of a particular development can be accurately assessed. 

Presently, Ministers are claiming that bats and newts are “blockers” to development, but there is a lack of clarity on where that information is coming from.

In the last five years there have been almost 2,000,000 planning applications made. That is a colossal amount of data, all in the public domain, that is completely untapped. This data could be used to help drive up the quality of decision making and speed up policy reform.

By having a model with all the data linked to particular planning applications, a ‘super baseline’ could be created to understand the matrix of species and habitats within each LPA, using the best available evidence. At Arbtech, we have existing proprietary data (taken from 12,000 planning applications in 2024 alone) that could be made available to speed up the creation of the new super-baseline understanding for decision makers; an essential pre-requisite for any change, let alone radical reforms.

This is where AI will be a game changer. For example, it could be mandated that all ecology reports contain a strictly formatted summary appendix that a machine learning tool could easily exploit the constant stream of fresh data as it is generated by the sector. This would greatly assist data collection. In fact, at Arbtech we are developing an AI application to translate all our data into actional insights for the public and private sectors in the hope that this will speed up the planning process and avoid preventable outcomes such as the irreversible decline of habitats and species.

Building, Design & Construction Magazine | The Choice of Industry Professionals