Two frameworks for balancing AI innovation and risk

The article "Two Frameworks for Balancing AI Innovation and Risk" by Faisal Hoque, published on March 7, 2025, discusses the importance of adopting a balanced approach to AI innovation. It introduces two complementary frameworks—OPEN and CARE—that help organisations harness AI's potential while managing its risks.

OPEN Framework:

Outline: Organisations should start by aligning AI initiatives with their core mission rather than focusing solely on the technology's capabilities. This ensures that AI projects deliver real value and avoid becoming tech-driven solutions in search of problems.

Partner: Successful AI implementation requires interdisciplinary collaboration within the organisation and external partnerships with specialised entities. The human-AI partnership is crucial, as it reshapes organisational culture and working relationships.

Experiment: Structured experimentation is key to moving from ideation to practical implementation. Organisations should design experiments to learn how AI can create value, scale, and integrate with human workflows, rather than just testing technical feasibility.

Navigate: Continuous learning and adaptation are essential. Organisations should maintain a steady flow of high-potential AI projects through an innovation pipeline, using objective metrics to prioritise and manage these projects.

CARE Framework:

Catastrophise: Identify potential risks across technical, operational, and strategic dimensions to create a comprehensive risk inventory.

Assess: Evaluate the likelihood and impact of identified risks, and the organisation's capacity to respond, to prioritise risks and allocate resources efficiently.

Regulate: Implement controls, monitoring systems, and governance structures to manage risks. This step translates risk analysis into actionable safeguards.

Exit: Develop clear protocols for risk response, including system shutdown procedures and continuity plans, to provide a safety net when preventive measures fail.

The article emphasises that a balanced approach, integrating both frameworks, enables organisations to drive AI innovation while safeguarding against potential pitfalls. This dual strategy ensures that AI's transformative power is harnessed effectively, leading to meaningful and resilient organisational change.