An AI-integrated organisation is one where people no longer think of AI as a tool, special project, or function. The shift in AI-integrated organisations produces a different level of transformation where teams move forward with speed and clarity. Oliver Sam, CHRO, VDart Inc, explains exclusively to Rajneesh De, Group Editor, CXO Media & APAC Media, how in a truly AI-integrated organisation, HR will need to architect the redesigning of roles around tasks, integrate continuous learning into workflows, and establish processes that are predictive and mitigative to stay ahead of the curve.
As we move toward the 2026 workforce inflection point, what major signals should organisations watch for to understand how AI and GenAI will reshape work, roles, and talent models?
The clearest signal of the 2026 workforce inflection point will be when AI becomes a default or assumed layer in everyday tasks and not one that is a special tool or capability used by specific teams.
We are already witnessing that transition happening and 3 shifts indicate this: First, AI will quietly embed itself into operational decision-making, where job descriptions, performance metrics, and workflow expectations begin to presume AI partnership as a baseline. Data-backed research and surveys from the World Economic Forum and other significant organisations have shown that over 70% of leaders expect roles to be redesigned around AI-assisted tasks by 2026.
We have seen this shift in VDart and in our own client environments. The second shift is organisations moving from experimental AI tools and platforms to fully integrated systems across functions such as customer operations, talent acquisition, finance, etc., which is accelerated when Boards adopt comprehensive policies on AI governance, ethics, regulatory compliance, risk management, etc.
Third, we are seeing a clear rise in roles that blend multiple skills like data, engineering, and product into a single hybrid role. Roles like MLOps, model orchestration, and model stewardship are growing rapidly. Organisations are valuing people who can manage AI end-to-end rather than just the basics. For us, this means moving from AI literacy to deep, practical expertise that shapes how work gets done.
At VDart, we have seen the evolution of AI integration from empowerment to responsible adoption and enablement without compromising on innovation. Our skills evaluation mirrors this evolution. It has moved beyond the volume of AI adoption to how work gets done with AI.
As these indicators converge across industries, organisations will need to shift from technology adoption to full-scale work redesign, ensuring that talent models, capability-building, and governance mature at the same pace as the tools themselves.
Many enterprises in APAC are accelerating AI and cloud adoption, but still face widening skill gaps. What structural or systemic factors are causing this talent lag, and how can organisations realistically bridge it at scale?
There is no denying that our existing systems are still evolving to match the pace of rapid technological change. Across APAC, studies have indicated nearly 70 per cent of companies continue to cite talent attraction as a key barrier to transformation. In many regions, digital fluency and the pace of upskilling have been taking time to catch up with the demands of AI and cloud.
Educational institutions are working to refresh and modernise curricula and infrastructure to sync with the demands, but this would naturally take time. With organisation, many still view skills development as periodic training rather than an integrated capability strategy. Together, this has created a lag between investments in AI and cloud, and the people readiness needed to fully leverage them.A multi-layered approach at the systemic level is required to bridge this gap. Firstly, deep partnerships between industry and academia to co‑design AI and cloud curricula; Secondly, company‑led talent academies that offer tiered learning paths from basic literacy to advanced specialisation; and thirdly, modifying hiring and deployment models that recognise adjacent skills and practical potential, not just formal degree skills. WEF and other industry research show that companies adopting these integrated, system-level strategies are far more likely to sustain talent pipelines than those relying on short-term programs.
VDart has been closely collaborating at the leadership level with some of the regions’ best technology and business institutions, as well as with our local community schools and colleges, in connecting learning and career paths. For the past few years, we have also been directly involved with the student communities in assessing the academic-skill requirement gaps and creating and delivering in-person learning modules.
In the long-run, organisations that connect education, hiring, learning, and career paths will be best positioned to close the gap at scale, create enduring capabilities, and realise the full potential of their AI and cloud investments.
AI is not only automating tasks but also augmenting roles. What emerging job categories and hybrid-role compositions do you foresee becoming mainstream in APAC over the next 18–24 months?
What we expect in APAC over the next 1- 2 years is the quiet reshaping of existing roles around AI. Yes, there will be new job titles with modified or expanded roles and responsibilities to include AI skills, and we are already seeing this in fields like banking, healthcare, customer experience, and digital services. We already see planners, risk specialists, and customer experience professionals using AI to enhance decision-making, anticipate demand, or personalise service at scale.
We’re also seeing new hybrid roles emerge that blend domain expertise with AI fluency. For example, traditional recruiters are becoming AI-enabled sourcing strategists and talent intelligence analysts to improve hiring quality, map workforce potential, and predict attrition. Similarly, cloud- and data-governance specialists are becoming essential, where they are bridging infrastructure and compliance with ethical stewardship of AI-generated outputs, particularly in regulated industries.
Leadership roles are also evolving. Productivity Co-Pilot Managers, for instance, use AI to monitor team workflow, identify skill gaps, and allocate resources efficiently, enabling leaders to focus more on strategic coaching and mentorship.
For HR, the implications are profound. It means traditional job descriptions are giving way to skills-based frameworks that reflect how capabilities are evolving, rather than sticking to fixed titles. Career paths are becoming more like portfolios, combining deep domain knowledge with AI and data skills, and encouraging rotations or hybrid experiences that build both technical and strategic strengths.
Traditional upskilling models are proving insufficient for rapid AI-driven workplace transformation. How should organisations rethink their approach—from upskilling to full-fledged talent re-engineering?
Traditional upskilling assumes that jobs stay the same and that people just need to learn new skills. But AI is changing the nature of work itself, and that requires a different approach, which is Talent Re-engineering, a continuous process that links skills, roles, and workflows directly to business outcomes and our purpose.
Conventional upskilling models have assumed that jobs remain the same and that people need to just learn new skills. But when AI is changing the nature of work itself, talent re-engineering becomes imperative- starting one step earlier than traditional upskilling by looking at the work itself. We deconstruct roles into tasks, identify which can be automated, augmented, or best left to humans, and then redesign not just the skills, but the work, team structures, and career paths around that future state.
To put this into perspective, it can begin with a time-bound business goal, such as growing a Digital Product Engineering vertical, and then working backwards to identify the skills, tools, and experiences and people required to achieve it. This helps us see where gaps exist and plan learning and deployment in a structured, long-term way.
Besides skilling itself, we have also focused on a more inclusive and responsible approach to how we attain this. Our commitment to the ESG principles and alignment with the UN SDGs ensures that AI augmentation does not leave anyone behind.
The outcome of such an approach is beyond just creating people who are trained with new skills. It is more about becoming organisations that develop talent that are agile, integrate AI responsibly and grow capabilities in a meaningful way.
APAC markets have unique workforce characteristics—young, diverse, and tech-aspirational. How can leaders harness this demographic advantage to build AI-, cloud-, and data-ready talent pipelines sustainably?
APAC’s workforce is one of the youngest and most diverse in the world, and we see this as a unique strategic advantage in the age of AI. They are a demographic that is digitally literate and adept at swiftly acquiring tech and AI-enabled skills. But harnessing this demographic strength requires more than just training programs. Again, a strategic, purpose-driven approach is required to turn their ambition and aspirations into sustainable capability.
At VDart, we focus on what we call a Purpose-Driven Pipeline. We frame careers not merely as jobs, but as opportunities to contribute to societal impact, aligning with UN SDGs like Quality Education and Decent Work. This resonates strongly with Gen Z talent, who are looking for meaning and purpose alongside professional growth. We spot potential talent even before their potential fully shows up, aligning them with trusted mentors and providing them with the right sponsorship.
Leaders and organisations can champion training programs that reflect a similar approach for young talent. What this does is build deep technical expertise in AI, cloud, and emerging technologies, while intentionally sourcing talent from diverse, first-generation and underrepresented backgrounds.
Another under-represented group is experienced talent, often women professionals, returning after a career break. What is traditionally seen as a gap can be converted into a strength by bringing in acquired soft skills, domain knowledge, and resilience into the AI-augmented workforce. Addressing technical skill gaps can transform this talent pool into AI-ready strategic talent pipelines.
Organisations need to initiate and strengthen early partnerships with universities and educational institutions, mobile-first vernacular platforms and deliberate inclusion of underrepresented groups. These initiatives will ensure that APAC develops Cloud and AI-ready talent pools that are deep, diverse and sustainable, aligned with business objectives and regional development.
From an HR leadership perspective, what does an AI-integrated organisation look like in practice? What are the foundational shifts needed in culture, leadership, and capability-building?
At its core, an AI-integrated organisation is one where people no longer think of AI as a tool or a special project or function. AI becomes the definition of work- how work gets done every day, whether reviewing information, planning task assignments, or decoding customer needs. But the genesis here is transparent AI governance. This is absolutely essential. It establishes trust, clarifies how AI is used, and aligns with ESG and ethics.
At scale, the shift in AI-integrated organisations produces a different level of transformation where teams move forward with speed and clarity. Then again, to achieve this, I believe there needs to be a cultural shift throughout the organisation, with its ripple effect being seen across functions and levels of leadership and management.
The culture factor is usually the most challenging, as this would not be about just introducing new tools and related policies that do lip service. It would mean dealing with resistance to change, tackling apprehensions, and encouraging experimentation, while having systems or guardrails to ensure responsible behaviour and the like.
Organisations need to nurture a culture of people being hyper-aware yet empowered to create and explore what suits them best and what serves the best interests of all the stakeholders. People also need enough data literacy to understand what AI is telling them and not just consume without thought application. There also has to be a healthy acceptance that job identities will keep evolving. That an AI-integrated organisation is highly likely to have fluid roles should be normalised. People will need to be coached to develop a task-first mindset rather than rigidly focusing on roles and titles alone.
Here, leaders play an evolved and hugely influential role. Instead of being the people who have all the answers, they will need to become coaches who help teams work with AI safely and confidently. They will need to nurture the psychological safety people need to learn, try and adapt, while clearly communicating the guardrails in place, which advocate integrity and ethics. Managing a team will mean managing a blend of people, data, and AI tools, and doing so with empathy and accountability.
For HR, the work becomes even more strategic, since it sits at the centre of these shifts, ensuring that the organisation has the right skills, structures and roles it needs to become a truly AI-integrated organisation. HR will need to architect the redesign of roles around tasks, integrate continuous learning into workflows, and establish processes that are predictive and mitigative rather than reactive to stay ahead of the curve. That includes redesigning roles around tasks, building continuous learning into workflows, and ensuring that AI is used in ways that strengthen and not diminish human contribution.
So, in practice, an AI-integrated organisation will not be defined by its tools but by how its people use those tools, how they grow with them, and how leaders create the cultural conditions for that growth to happen.
Cloud, AI, and data talent often follow global demand cycles. How can APAC organisations compete for, retain, and grow this talent amid aggressive global hiring and rising mobility?
Cloud, AI, and data professionals today have the freedom to work for almost any market from wherever they are, which means APAC companies aren’t just competing with their neighbours anymore; they’re competing globally. And while salaries are a crucial factor in having an excellent talent force, it’s rarely the only thing that keeps this group anchored. The striking differentiator in any organisation is the mix of meaningful work, a chance to be seen, heard and grow fast, and a workplace that treats people with respect.
This is where I see APAC employers gaining an edge. The ones who do well are very deliberate about balancing what they buy from the available talent market with what they build from within. They run in-house training centres to move adjacent talent into cloud, AI, or data roles. They create technical paths that actually elevate careers. And they listen closely to what their specialists need and are aligned with data, trends and ground reality, with managers, through real conversations.
They are also companies that can create exposure and opportunities to work with international clients without uprooting them. An engineer in India getting to lead a cloud migration for a US client or a data specialist in Malaysia working on a European product build creates the kind of exposure that rivals anything offered by global tech hubs.
On our side, a few things have worked consistently. One is anchoring our talent strategy in purpose and ESG. Several studies conducted by consultancy and research centres have consistently reported that a lot of young engineers, especially Gen Z, want to work for companies that are value and purpose aligned. Our sustainability commitments, community programs, and the fact that so many of our people are first-generation professionals genuinely matter to them.
And growth has to feel personal. Our mentorship and sponsorship models have been critical for retaining high-potential talent who might otherwise leave for faster visibility elsewhere.
In short, APAC organisations will win this race when they stop thinking only in terms of salaries and start designing an environment where talent can see a future- one that is purposeful, global, inclusive, and genuinely invested in their advancement.
As CHRO and Talent Partner to the CEO, what frameworks or playbooks has VDart implemented to prepare its global workforce—and what can APAC enterprises learn from your approach?
As a global digital talent and solutions partner to several Fortune 500 companies, VDart has had a front‑row seat to how AI and cloud are reshaping workforce needs across industries and regions. However, preparing a global workforce for AI, cloud, and data isn’t about one-off initiatives or programs. It’s about creating an intentional environment where people can learn, experiment, and grow, while having clear guardrails that protect data, privacy, and compliance.
At VDart, everything sits on a purpose-driven culture that impacts both our clients and our people. That’s probably the part that has shaped our workforce strategy the most. Our ESG commitments, our focus on first-generation talent, our investment in gender inclusion through GWLI, and our work with communities have all greatly influenced who chooses to work with us, who chooses to stay, and what they expect from leadership. When people feel that their work is meaningful, capability-building becomes much easier because then you have created culturally aligned people who consider learning as progress and not pressure.
We have been very fortunate and grateful to be mentored by great companies like Accenture and Delta Airlines, which have immensely helped us in creating our business strategy and putting it into action, that have produced phenomenal growth for us. We have incrementally taken steps to align ourselves with global standards and frameworks, taking sustainability and responsible data management seriously. VDart has maintained ISO certifications consecutively since 2021, including ISO 14001 for environmental management, and we have earned an EcoVadis Silver Medal, reflecting our structured ESG and sustainability practices. These recognitions testify to how we operate every day, from environmental impact to ethical data stewardship.
For APAC enterprises, we are uniquely positioned because of the demographic advantage and cultural values. Ambition and courage go hand-in-hand with responsibility- be aware, leverage the power of data, empower people to explore and learn, make sure there are strong ethical and sustainability standards, and design systems that grow capability while protecting trust. AI, cloud, and data tools can transform work, but only when people feel confident and supported in using them responsibly.
