AI projects succeed or fail based on stakeholder dynamics. This framework identifies who matters, what they care about, and how to build the coalition for approval.
The classic Power-Interest Matrix plots stakeholders on two dimensions: their ability to influence project outcomes (Power) and their level of concern about the project (Interest). This creates four categories requiring different engagement strategies.
High Power, High Interest: Key players—manage closely. High Power, Low Interest: Keep satisfied—meet their needs without overwhelming with detail. Low Power, High Interest: Keep informed—valuable advocates. Low Power, Low Interest: Monitor—minimal effort required.
For AI and automation projects, the framework extends to include technology attitude (enthusiast to sceptic) and change capacity (high to limited). These additional dimensions inform messaging and risk management.
List everyone affected by or influential over the project. Include sponsors, users, IT, finance, operations, and external parties. Cast the net wide initially.
Rate each stakeholder's ability to impact project decisions and outcomes. Consider formal authority, budget control, political capital, and veto power.
Assess how much each stakeholder cares about this project. High interest can be positive (champion) or negative (opponent). Note the direction.
Rate each stakeholder's disposition toward AI and automation. Enthusiasts need different handling than sceptics. Past experiences shape current attitudes.
Define approach for each stakeholder based on their position. High-power sceptics need risk mitigation messaging. Low-power enthusiasts can be mobilised as advocates.
Stakeholder positions shift over time. Monitor changes and adjust engagement. Early opponents can become champions with the right approach.
Starting any project requiring broad organisational buy-in
Previous projects have failed due to stakeholder resistance
Multiple departments or business units are affected
Budget approval requires multiple sign-offs
Significant change management is required
Political dynamics are complex or unclear
Mapping only formal hierarchy, ignoring informal influence networks
Assuming technical stakeholders don't care about business outcomes
Treating all high-power stakeholders the same regardless of interest
Creating the map once and never updating it
Ignoring low-power stakeholders who can become blockers if mobilised
Focusing only on executives, missing operational influencers
Auditic captures stakeholder information during discovery interviews and provides analysis tools to understand influence dynamics across your engagement.
Interview-linked profiles: Stakeholder information from interviews feeds into profile records. Concerns, priorities, and quotes are captured in context.
Influence analysis: AI identifies stakeholder relationships and influence patterns from interview content. Who defers to whom? Who has veto power?
Engagement tracking: Log interactions, track sentiment changes, and monitor stakeholder positions over time. See the coalition building or eroding.
See how Auditic applies Stakeholder Mapping Framework automatically.