Dad, this is how AI is revolutionising workforces

Poco has taken a bottom-up approach to review and reorganisation.

The only ‘spending review’ carried out was that of the across-the-board cuts mandated by law , i.e. implemented using a formal, one-size-fits-all approach, without any assessment.

But once the media attention had died down, whilst everyone’s attention was elsewhere, recruitment resumed indiscriminately, or offices and management positions were multiplied as if simplification, efficiency and reorganisation were topics confined to academic literature and conferences. Artificial intelligence can present a great opportunity to simplify and be efficient and transparent.

For this reason, it cannot merely be the starting point for updating regulations – an area in which we have always been unrivalled – but must lead to a genuine overhaul of the way in which “public administration is carried out”. Otherwise, it simply becomes yet another way of digitising the status quo.

In the public sector , there is no high ‘ethical’ risk thanks to the numerous regulations governing processes and staff, low levels of digital literacy and limited data sharing. Nor is there a risk of dismissal on objective grounds or due to redundancy, thanks to the protective regulatory framework and the protective stance towards public sector workers that underpins the legal system.

What is needed, instead, is high-quality recruitment focused on new skills, capable of handling data collection, analysis and processing.

In the current climate, at best we turn to external public or private organisations. We do not have training specifically designed to support retraining and upskilling processes, or to modernise job profiles and roles.

When used effectively, administrative data can improve the quality of information and thus enable the development of better intervention models and measures, as well as ensuring transparency in decision-making.

Our public policies and our welfare state need artificial intelligence and data analysis to support responsible decision-making and improve the timing of policy implementation.

Priorities regarding recruitment will have to change, with a focus on pooling expertise and consolidating departments. In the public sector, the number of departments has grown irrationally, contributing, amongst other things, to the fragmentation of processes and effectively hindering data governance through open, interoperable datasets and infrastructure.

As already mentioned, over the years we will gradually need fewer administrative staff and more economists, IT specialists and statisticians. Otherwise, we will produce regulations and guidelines but bring about no change.

But at the heart of it all, there probably needs to be a clear and shared desire to seek knowledge in order to make decisions – something that seems to be lacking today.