Making AI Work: The People-Centred Approach to Intelligence Transformation

Originally published on 11 July 2025

Too often, AI initiatives in intelligence settings fail—not because the technology is flawed, but because implementation overlooks the people and systems it’s meant to support.

True integration is not a technical project; it’s a strategic transformation. To embed AI successfully into intelligence workflows, organisations must focus on:

• Cultural Alignment - Analysts may fear being replaced or overruled by machines. Success begins with clear communication: AI is an enabler, not a threat. Early wins, visible champions, and analyst involvement in testing are essential to building trust.
• Training and Upskilling - Most intelligence professionals are not trained in data science. Yet they must understand model behaviour, interrogate AI outputs, and know when and how to apply analytic judgment. Training must bridge this gap.
• Workflow Integration - AI tools must work with, not around, existing systems. That means compatibility with current infrastructure, intuitive interfaces, and transparency in outputs—linking alerts to source data and enabling human review.
• Governance and Oversight - Organisations need clear internal frameworks defining who is accountable, how thresholds for action are set, and when human intervention is required. In both public and private settings, ethical and legal alignment is critical.

Ultimately, the goal is not to automate intelligence; it’s to enhance it. AI should extend human capability, not displace it.

Through thought leadership and sector-wide collaboration, the Institute for Intelligence Professionalisation advocates for AI adoption models that centre human judgment, ethical oversight, and strategic capability development.