The AI influence gap: Why missing voices put workplaces at risk

While organisations rush to adopt AI tools, a quieter problem is emerging: the “AI influence gap”.

This gap isn’t just about who uses AI. It’s about who gets a say in how AI is chosen, designed, implemented, and governed – and who is left out.

For HR leaders, this is now a core people, culture, and risk issue.

So, what is the AI Influence Gap? It refers to the disconnect between who is affected by AI at work, and who actually influences how AI is used.

In many organisations, AI decisions are driven by a narrow group – typically technical teams, vendors, and a small number of senior leaders. Missing from the table are:

• HR and people leaders
• Employee representatives and frontline staff
• Diversity, equity and inclusion (DEI) practitioners
• Legal, risk, ethics and governance experts
• Professionals from different disciplines (e.g. health, finance, operations)

When these voices are missing, AI systems are deployed that don’t reflect the organisation’s people, values, or legal and social obligations.

As TechDiversity Foundation’s executive director Luli Adeyemo put it: “The people shaping governance decisions are still too narrow a group… When those voices are missing, we get blind spots, flawed systems, and missed opportunities.”

Why HR should care

AI is increasingly embedded in the employee experience, even if it’s not always labelled as “AI”:

• Recruitment and selection tools that rank CVs or score interviews
• Performance management systems that analyse productivity or engagement
• Learning platforms that personalise development pathways
• Workforce planning and rostering systems that optimise staffing
• Wellbeing and EAP chatbots assisting employees in vulnerable moments

If HR does not have meaningful influence over the design, procurement, and governance of these systems, then:

• Bias can be embedded and scaled (e.g. gender, race, age, disability)
• Employee trust can be damaged if tools feel opaque or unfair
• Psychological safety can be undermined, especially in wellbeing or performance contexts
• Organisations can face legal, reputational, and financial risk

According to Adeyemo, these harms are not hypothetical. Around the world, she has witnessed a UK council using AI to help deny care to women, amplifying discrimination.

Australia’s Robodebt scandal, where automated decision-making about welfare repayments caused profound harm, contributed to deaths, and led to one of the largest government payouts in history.

Chatbots deployed in mental health settings without adequate safeguards, risking serious harm to vulnerable people.

These are not “tech glitches”. As AI governance expert Dr Kobi Leins noted, they are governance failures – failures of oversight, accountability, and inclusive decision-making.

One of the most dangerous myths about AI is that it is purely a technical issue. According to Adeyemo, AI is socio-technical.

Data is selected by people, models are configured by people, systems are deployed in human organisations, and impacts are felt by employees, customers, and communities.

Leins emphasised that "governance requires all voices at the table, legal, technical, philosophical, ethical. The moment you have people asking hard questions from different angles, you catch what single perspectives miss. That's where real accountability happens."

For HR, this reframes AI from being “an IT project” to:

• A workforce and capability issue
• A culture and ethics issue
• A safety, wellbeing, and compliance issue

The Australian context

Australia’s AI landscape is maturing quickly. The Australian Public Service AI 2025 Plan emphasises three pillars: Trust, people, and tools.

For HR leaders, this offers a useful framing:

• Trust: Employees and candidates must trust that AI systems affecting them are fair, transparent, and accountable
• People: AI needs to augment people, not sideline or harm them. This includes upskilling, redeployment, and inclusion
• Tools: AI tools must be assessed not just for functionality, but for their governance, compliance, and social impact

However, even as these frameworks emerge, the influence gap remains: who actually gets to shape how AI is implemented in your organisation?

Closing the gap: What HR leaders can do

To help alleviate the issues the AI influence gap presents, there are six key actions HR teams can make:

1. Claim a seat at the AI governance table
2. Build AI literacy across HR and people leaders
3. Embed diversity and inclusion into AI design and review
4. Create clear policies on AI use in people decisions
5. Monitor real-world impacts, not just technical metrics
6. Invest in cross-disciplinary governance capability

The AI influence gap is not inevitable. It’s the result of choices – often unexamined – about who is invited into AI conversations and who is not.

By stepping into AI governance with confidence, curiosity, and a commitment to inclusion, HR can help ensure that AI at work is not something that happens to people, but something shaped with them.