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.