How to be a data influencer and close the AI trust deficit
How to be a data influencer and close the AI trust deficit
Many organisations face an AI trust deficit. AI tools and data-rich dashboards are being deployed, but teams still rely on familiar manual reporting because they do not trust algorithmic outputs. Using an air-traffic-control radar analogy, the discussion frames AI as a decision-support signal that only becomes valuable when interpreted by people who understand both the data and the operational context. It proposes a shift from being a data presenter to becoming a data influencer, defined as someone who translates data into timely decisions while maintaining human agency. Drawing on research into digital transformation and AI in project environments, the post identifies three core capabilities; applying critical thinking to interrogate data provenance, processing, and alignment with project goals; recognising what algorithms cannot see, including contextual and human factors that shape outcomes; and curating information ruthlessly to manage cognitive load, attention, and reporting cadence. The discussion concludes that closing the AI trust deficit requires developing these interpretive and judgement-based capabilities alongside technical adoption, so that trust is built not only in data outputs but also in the human decisions.
Digital transformation, Artificial intelligence, Project management, Agile methodologies, Data governance, Digital competencies, Strategic leadership, Public-private sector
Association for Project Management
Dacre, Nicholas
90ea8d3e-d0b1-4a5a-bead-f95ab32afbd1
20 February 2026
Dacre, Nicholas
90ea8d3e-d0b1-4a5a-bead-f95ab32afbd1
Nicholas Dacre (Author)
(2026)
How to be a data influencer and close the AI trust deficit
Association for Project Management
Abstract
Many organisations face an AI trust deficit. AI tools and data-rich dashboards are being deployed, but teams still rely on familiar manual reporting because they do not trust algorithmic outputs. Using an air-traffic-control radar analogy, the discussion frames AI as a decision-support signal that only becomes valuable when interpreted by people who understand both the data and the operational context. It proposes a shift from being a data presenter to becoming a data influencer, defined as someone who translates data into timely decisions while maintaining human agency. Drawing on research into digital transformation and AI in project environments, the post identifies three core capabilities; applying critical thinking to interrogate data provenance, processing, and alignment with project goals; recognising what algorithms cannot see, including contextual and human factors that shape outcomes; and curating information ruthlessly to manage cognitive load, attention, and reporting cadence. The discussion concludes that closing the AI trust deficit requires developing these interpretive and judgement-based capabilities alongside technical adoption, so that trust is built not only in data outputs but also in the human decisions.
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Dacre_2026_How-to-be-a-data-influencer-and-close-the-AI-trust-deficit
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Published date: 20 February 2026
Keywords:
Digital transformation, Artificial intelligence, Project management, Agile methodologies, Data governance, Digital competencies, Strategic leadership, Public-private sector
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Local EPrints ID: 510215
URI: http://eprints.soton.ac.uk/id/eprint/510215
PURE UUID: 045d5e1b-6dcd-43cf-b609-7e7318f72567
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Date deposited: 23 Mar 2026 17:38
Last modified: 24 Mar 2026 03:01
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