As artificial intelligence reshapes the modern workplace, many organisations continue to focus on automating existing processes rather than fundamentally rethinking how work is designed. According to Julia Tan, Regional Vice President of Cloudera ASEAN, this approach risks limiting AI's transformative potential. She argues that the next phase of AI adoption will require organisations to redesign work models, rethink leadership and build cultures that prioritise collaboration over hierarchy.
In this conversation, Tan shares why leadership is evolving from directing tasks to enabling better decision-making across teams, and why inclusive leadership, diverse perspectives and cross-functional collaboration will become defining characteristics of AI-ready organisations.
Rethinking how work is designed and distributed as AI becomes a co-worker The biggest opportunity lies in redesigning work at the workflow level. Rather than automating individual tasks or adding AI onto existing workflows, leaders need to look at the entire sequence of work and decide where human judgement creates the greatest value and where technology can take greater ownership. To achieve this, companies must re-examine the division of labor between people and AI. Repeatable coordination, analytical tasks, and execution can be managed by AI, allowing employees to direct their efforts toward high-impact decisions that demand contextual understanding, creative problem-solving, relationship management, strategic judgement, and accountability. Consequently, leaders ought to structure roles and workflows focused on target outcomes, moving away from maintaining rigid legacy job frameworks with AI merely layered on top. Deloitte’s 2025 Global Human Capital Trends report found that six in ten workers already think of AI as a co-worker. At the same time, AI can reshape the employee experience in unintended ways, from reducing human interaction to limiting learning opportunities. The objective should therefore be to create a better system of work: one where technology extends people’s capacity while employees retain meaningful agency and accountability. A true “AI-ready” organisation from a people and leadership perspective AI readiness is fundamentally an organisational capability. An AI-ready organisation has clarity in four areas: where AI creates value, how people are expected to use it, what guardrails govern that use, and how roles and workflows will evolve as adoption scales. Employees should understand when they can rely on AI, when human intervention is required and how decisions remain accountable. There is currently a significant gap between adoption and organisational readiness. BCG’s AI at Work survey revealed that 78% of employees across Asia Pacific use AI at least weekly, yet only 57% say their organisations are redesigning workflows to accommodate that shift. It also found that 58% would use AI even if their employer did not formally provide it, highlighting how quickly employee behaviour can move ahead of governance, increasing risk for the organisation. That governance challenge is becoming increasingly tangible. The Great AI Re-Architecture survey by Cloudera demonstrated that 61% of APAC respondents say AI integration has made effective data governance more difficult, while 92% have delayed or cancelled at least one project in the past year due to data governance, compliance or regulatory issues. This shows that readiness is also about having the operating discipline to move from experimentation to responsible deployment at scale. Leaders therefore need visibility into how AI is being used, mechanisms for employees to share best practices in order to scale across the organisation, and governance that enables responsible experimentation. Employees, on the other hand, need a credible narrative about how AI will affect their work and how the organisation intends to invest in their capabilities through the transition. Leadership capabilities becoming more critical now AI will increase the premium on leadership capabilities that technology cannot easily replicate: judgement, empathy and the ability to navigate ambiguity. Judgement is imperative in deciding where AI should have autonomy, when human oversight is required, and how to balance speed with responsibility. This requires leaders to understand the technology well enough to ask the right questions, while keeping their teams accountable for outcomes. Empathy is equally critical. While data can help surface where organisations need to pay attention, it is listening, context and real conversations that help leaders understand why something is happening and how to respond. That becomes especially important as AI changes roles, job expectations and the employee experience. Adaptability will matter because AI is continuously reshaping how work gets done. Leaders need to be willing to refine workflows, develop new capabilities across their teams and evolve operating models as adoption matures, while keeping people connected to the purpose behind those changes. Preparing and reskilling the workforce for AI amid job displacement concerns Reskilling needs to begin with visibility. Employees are more likely to engage with AI when they understand how their roles are changing and can see a credible path for themselves within that change. Concerns around displacement should not be overlooked, especially across the region, where BCG found that 52% of APAC employees are concerned about losing their jobs because of AI, rising to 53% among frontline employees, compared with 36% of frontline workers globally. Organisations should therefore move beyond broad “AI literacy” programmes and build learning around actual work. This starts with identifying which activities within each role are likely to be automated, augmented or newly created. Training can then focus on the capabilities employees will need in that redesigned role, such as AI supervision, critical evaluation, data literacy, customer judgement and domain expertise. At the same time, leaders must be transparent about how roles may evolve. Blanket assurances that every role will remain unchanged can undermine trust. A stronger message is that work will change, the organisation will communicate those changes clearly, and employees will be given meaningful opportunities to build the capabilities required for emerging roles. Confidence grows when people have agency. Reskilling should give employees a role in shaping how AI changes their work, rather than leaving them waiting to find out what happens to them. Ensuring AI does not widen gender gaps and creates equitable opportunities for women The first step is to make sure AI does not simply reproduce the inequalities that already exist in the workplace. Organisations need to be deliberate about who has access to AI tools, who is being trained to use them, and who has opportunities to shape how these technologies are deployed. This is particularly important as AI creates new roles and changes the skills that are valued. If women are concentrated in roles that are more exposed to automation but have less access to technical training, leadership opportunities or AI-related projects, existing gaps could widen. Organisations should therefore ensure that reskilling and career development programmes are accessible across the workforce, while creating pathways for women to move into emerging areas of technology and leadership. There is also an important cultural dimension. Inclusion is not just about representation, but also about ensuring people feel they have the opportunity to contribute and progress. At Cloudera, being recognised as a top-five Best Place to Work in Tech by Great Place to Work is a reflection of the culture we are building around collaboration, innovation and enabling people to do their best work. As AI reshapes the workplace, maintaining that sense of inclusion and opportunity will be just as important as the technology itself. Moving beyond representation to greater influence and decision-making power Representation is an important starting point, but it is not the end goal. The real question is whether women have a meaningful voice in the decisions that shape the organisation, particularly decisions around technology, investment, talent and the future of work. That means looking beyond how many women are in the room and examining who has the opportunity to lead important initiatives, influence strategy and own outcomes. Organisations should create avenues for women to take on high-impact roles, sponsor emerging female leaders and ensure that opportunities to work on transformative projects are distributed equitably. This is also where leadership culture matters. Creating an environment where people can challenge assumptions, bring different perspectives and take calculated risks is essential. Technology organisations, in particular, benefit when diverse perspectives are involved early in the process of deciding not just how technology is built, but what problems it should solve and how it should be used. The goal, therefore, should be to move from representation to participation, and from participation to influence. Women should not simply have a seat at the table; they should have the authority and confidence to help determine where the organisation goes next. Turning AI adoption into meaningful business and people outcomes The organisations that succeed will be those that treat AI as an organisational transformation rather than a technology implementation. The differentiator will not be how many AI tools an organisation has deployed, but whether it has redesigned work, developed the capabilities of its people and established the governance needed to use AI responsibly at scale. That requires leaders to connect three things: business strategy, technology and people. AI investments need to be tied to clear business outcomes, while employees need to understand how their roles will evolve and have opportunities to build the capabilities required for that future. Organisations also need to maintain strong data governance and accountability as AI becomes more deeply embedded in decision-making. This is why conversations around the future of work need to go beyond adoption. At EVOLVE26, Cloudera’s annual flagship event, the focus is on how organisations can navigate this next stage of transformation and turn emerging technologies into meaningful outcomes. The organisations that come out ahead will be those that can connect innovation with trust, governance and human capability. If there is one bold commitment HR leaders should make now, it is this: make every major AI investment a people investment as well. For every significant workflow or role being transformed by AI, organisations should have a corresponding plan for how people will be reskilled, supported and given opportunities to contribute to the new model of work.