AI, Data, and Digital Transformation

Progress in AI and Machine Learning: • Advancements toward General AI with enhanced large language models (LLMs) • Increased use of ML for specific, complex tasks such as automatic feature extraction tasks and efficient data management. Innovation in Data Infrastructure and Applications: • Development of high-throughput data management systems. • Organisations like Ordnance Survey (OS) are at the forefront of deploying Computer Vision (CV) and ML techniques to create national-scale datasets • Generative AI improving data accessibility through translating natural language into precise data queries, simplifying decision-making and problem-solving. Rapid Technological Growth: • Digital transformation remains essential for competitiveness. • Need to focus on employee retraining and upskilling, as well as preparing employees for the effects of AI and digital transformation. • Balancing technological adoption with phased implementation and human adaptability remains critical. Responsible AI and Secure Data Management: • Importance of ethical frameworks, such as OS’s Locus Charter for responsible AI use. • Ensuring secure, continuous monitoring when integrating AI technologies, with collaboration from cybersecurity and legal experts. • With cybersecurity threats being powered by AI and becoming more sophisticated - need well thought out strategies from where data is stored, to how it is structured and documented to allow for analysis and better decision making.