Qualitest: Is AI The Driver for Efficiency Within Digital Transformation? #techUKDigitalPS
The UK public sector has undergone a significant transformation in recent years as digital technologies and agile ways of working have been increasingly adopted to improve efficiency, reduce costs and enhance service delivery and user experience. We are now at the cusp of bringing the next wave of transformational technological impact, the infusion of artificial intelligence (AI) technology, which is proving to be an enabler for efficiency and innovation.
Statistics from a report by TechUK estimate that the adoption of AI and machine learning in the public sector could result in cost savings of up to £17 billion by 2030. These cost savings could be achieved through increased efficiency, reduced staff costs and improved decision-making.
The Mechanics - AI/ML and its Applicability to Service Delivery
Artificial intelligence and machine learning have a range of potential uses in the public sector. These technologies can be used to streamline processes, identify trends and areas of focus, automate tasks and provide insights that enable informed decision-making. For example, AI can be used to analyse large amounts of data to identify patterns and trends that can be used to improve service delivery.
There are many examples of successful implementations of AI in the public sector. For instance, the NHS has implemented AI-powered chatbots to help patients manage their health and the Police have been using AI to predict crime patterns and deploy resources more effectively. These examples highlight the potential benefits of AI in improving service delivery and enhancing public safety.
AI is Only a Game Changer if it is Reliable and Safe
While AI has the potential to drive significant efficiencies, it is important that its use is sustainable and responsible. This means considering how AI insights and recommendations will be consumed by the end users or decision makers and how we can make sure that AI is correct and stable over time and helps us to make decisions as new data is introduced. Safety and reliability on AI can also be demonstrated by informing users that AI requires maintenance and its performance and accuracy have potentially degraded, as the new data suggest different actual results than predicted.
Equally important is ethical and robust training and deployment of AI. We need to ensure that AI systems are designed with ethical considerations in mind. This means ensuring that AI systems are transparent, explainable and fair, that training of algorithms is done on fair and unbiased data, e.g. avoiding gender as training data when training NLP and classification models to sift CV profiles.
Where to Take AI From Here?
As AI continues to become more widely adopted in the public sector, it is important to consider the future possibilities and potential challenges. Making sure we are protecting and assuring the quality and reliability of our AI models and AI-infused systems, will quickly translate to the adoption and acceleration of existing tedious and labour-intensive work that could free up a capable workforce to higher-value work and tasks.
Conclusion
A survey by Deloitte found that 67% of public sector organizations in the UK are planning to increase their spending on AI and automation technologies in the next year, let’s make sure we are doing it right from the get go.
This article was written by Aviram Shotten, Head of Technology, EMEA, Qualitest. Aviram Shotten is Chief Innovation Officer at Qualitest, the world’s leading AI-powered quality engineering company. He is an experienced C-suite executive with a global track record in the aerospace, defense, information technology, and services industries. His fields of expertise include business development, management consulting, project management, change management, and innovation management. To learn more about this author, please vsit their LinkedIn.
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