Using AI to improve manager effectiveness

The manager’s job today has become unmanageable, writes Jonathan Tabah.

Managers are in responsibility overload, leading to high levels of burnout. A recent Gartner survey found 26 per cent of managers regret taking on the role, citing relentless administrative burdens as a key reason.

On top of their core management responsibilities, they’re now responsible for helping employees adopt new AI-driven ways of working; supporting those whose roles and workflows have been disrupted by technology and AI; and incorporating new AI-enabled approaches into their own workflows.

At the same time, many organisations are undertaking significant transformation, which increases employees’ reliance on their managers.

When managers struggle, their teams suffer, leading to higher attrition and reductions in engagement and performance. Gartner research indicates poor manager quality, lack of respect, and ineffective people management are the top three reasons Australian employees are leaving their organisations.

AI is emerging as a critical lever to address these challenges, and many expect it to also empower managers to become more effective human leaders. Carefully deployed AI offers HR leaders a chance to remove some of the administrative tasks from the plates of managers. As a result, this will reduce burnout and increase effectiveness.

Beyond reduced administrative workload, AI-driven manager practices can offer more time for coaching and team development, as well as more personalised employee support as AI-powered analytics identify individual skill gaps and recommend targeted learning. While all of this sounds promising, the reality is more complicated.

AI can unlock higher levels of manager effectiveness, but few managers will realise these benefits without the right guidance from HR on how, where, and when to use AI. Unfortunately, many organisations in Australia aren’t supporting managers’ AI adoption, missing this significant opportunity to improve employee and organisational performance.

Most HR leaders don’t believe managers have the skills to use AI in their workflows, but aren’t currently offering them targeted solutions to help. A Gartner survey of HR leaders revealed scepticism around the impact of AI, with only 38 per cent expecting AI to improve manager effectiveness; just 14 per cent supporting managers in using AI in daily tasks; and only 8 per cent believing managers have the skills to use AI today.

To improve manager performance through AI, HR must support manager-specific workflows and recognise they aren’t a homogenous group. Tailored training must be provided that focuses on AI use cases specific to managers and their distinct AI readiness levels.

Manager role transformation

Employees still have human needs that AI can’t address, so the manager role can’t be fully automated. HR’s focus today should be on augmenting manager effectiveness by increasing the value of their work, instead of seeking efficiencies by increasing their span of control.

AI isn’t about replacing managers – it’s about transforming their role for greater impact. By automating routine tasks and guiding managers to leverage AI in ways specific to their workflows, HR leaders can help them deliver impact where it matters most: their people. This enables Australian organisations to boost employee engagement, strengthen performance, and build an AI-ready workforce.

HR leaders need to redesign the manager role, develop targeted training programs, and update talent management processes to encourage the adoption of AI in meaningful ways. General AI literacy programs won’t provide managers with what they need to leverage AI tools in their roles. Managers require additional training focused on handling these tools, as well as sensitive employee data.

Simply encouraging AI use doesn’t help managers integrate it into their work. They need guidance on how to shift administrative work to AI and reprioritise their time toward strategic goals. Managers are like other employees in one significant respect – they’ll have varying levels of experience and comfort with AI tools, necessitating an approach tailored to different adoption levels.

From quick wins to long-term effectiveness

Regardless of overall manager AI readiness, quick wins must be identified to build momentum, while also working toward a longer-term transformation to an AI-augmented manager role. Quick wins allow organisations to realise benefits early on, but long-term role transformation will only come after carefully redesigning manager workflows.

Prioritise piloting use cases for tasks that managers describe as frustrating or time-consuming and leverage tools the organisation has already invested in. Early use cases to build manager confidence with AI could include automated sentiment analysis from surveys, drafting and editing routine reports, and gathering and analysing direct report performance data.

Looking further ahead, AI transformations are typically more complex and require significant investment in data infrastructure and workflow improvements. These longer-term transformations will likely have greater efficiency gains on manager tasks than generic enterprise-wide AI tools.

More advanced solutions should be explored, such as AI-driven workforce planning analytics, dynamic internal talent marketplaces, recruiting agents, timed behavioural nudges, and predictive attrition models for managers.

A deliberate, phased journey

AI has the potential to alleviate manager burnout from administrative tasks and empower managers to become more human-centric leaders. With a tailored manager AI pilot, HR leaders can drive adoption among managers despite varied manager proficiency.

Successful managerial AI adoption is not a single event, but a deliberate, phased journey. Achieving quick wins through a manager AI pilot builds stakeholder buy-in and lays the groundwork for longer-term role redesign and manager transformation.

Jonathan Tabah is the director of advisory in the Gartner HR practice.