How can councils adopt artificial intelligence?

Artificial intelligence (AI) and machine learning are used across many industries to automate processes, increase efficiency, predict outcomes, and make better decisions. What does this mean for local government and the current systems in use? The technical capability is available and accessible, and there's a wealth of historical data, so how can local government take advantage of AI and machine learning?

How can AI be used by councils?

The use of virtual assistants is an exciting growth area. Councils can use them to support and enhance customer service, which saves time and effort in the future. In the short term, workforces can be made far more effective by connecting a customer with an AI-driven knowledge base which can provide the answers the customer needs. Customer service officers can still interact with the public, but as they do this, they can capture more information about questions asked and responses given and enhance the virtual assistant.

AI can provide the learning and prediction that can present the best responses and filter out lesser-used information. Learning from variable inputs ensures the virtual assistant can provide consistent and accurate outputs.

Without the use of AI and machine learning, we can't physically process the volume of data we capture. For example, if we want better predictability on processing an application within our service level agreements, it’s currently difficult to perform this in real time on every application received. We could produce reports and dashboards that give us the current state and analyse average processing times, but to be able to predict an accurate outcome that takes into account trends, busy periods, time of day, and personnel assigned becomes difficult because the variables are constantly changing.

This is where machine learning helps out. Vast amounts of historical information can be processed and we can then understand the variables. We can therefore attain a prediction with a percentage of certainty in real time.

Machine learning

So, how can councils apply machine learning to existing processes? One option is through automating regular approvals. If a manager consistently approves certain requests (for example, council facilities being booked), machine learning can recognise this and ask the manager if they would like to approve all these bookings automatically in the future. Only the exceptions to this rue then need to get approved by the manager. At any time, the manager can review these preferences and retake control.

What about when an application is received by council? We can apply machine learning to an application through its entire workflow process. Based on what history tells us about the type of application, or what information is provided by a customer service staff member, as more information is provided the predictions get more accurate.

Object recognition

AI can also be used alongside object recognition, which is available through cloud frameworks provided by the likes of Amazon, Google, and Microsoft. Periodic snapshots of CCTV footage can be analysed by AI to produce information, such as pedestrian counts, animal recognition, free parking spaces, or traffic volumes. The result of the data received can then be fed into machine learning to provide predictive capability around automated park maintenance scheduling guiding people to free car parks and predicting traffic congestion.

What benefits would councils experience from AI?

There are immediate benefits that AI-based technologies can bring to local government. Reducing backlogs, cutting costs, freeing staff from mundane repetitive tasks, improving the accuracy of forecasts, and injecting intelligence into processes and systems. AI can tackle the tasks humans can't do easily on our own, such as sifting through millions of documents.

Backlogs of applications, requests, and communications are a constant challenge in local government. By introducing robotic or cognitive automation we can reduce pain points by increasing the speed of data entry, enhancing the reach to communities, and reducing the cost to capture and process information. Repetitive tasks can be identified and automated using robotic process automation frameworks.

If we can become more efficient in the processes we perform today without looking to replace humans, we can provide better response times for the community and have confidence in the decisions we make.