HR has often been positioned as a support function, called in to manage policies, resolve issues, or guide change already in motion. But as organisations become more distributed, dynamic, and employee expectations grow, that reactive model falls short. HR today is expected to shape culture, influence strategy, and stay embedded in the day-to-day experience of work.
GenAI has already started to change how HR teams work, speeding up tasks like drafting policies, analysing engagement data, and generating learning content. But to go further, HR needs systems that can sense what’s happening in real time, respond with context, and act proactively. That’s where Agentic AI comes in. It goes beyond assistance to autonomous action – routing queries, flagging risks, triggering nudges, or coordinating tasks across systems.
Together, GenAI and Agentic AI are shifting HR from supporting decisions to actively shaping them, and doing so at scale.
Scaling HR Impact with GenAI and Agentic AI
GenAI is changing how HR teams operate – accelerating everyday tasks like reviewing CVs, drafting job descriptions, or analysing employee performance reviews. It supports the creation of tailored policies, improves the quality and consistency of outreach, and helps surface insights from unstructured data. It also enables more targeted interview preparation and personalised learning journeys.
These capabilities have helped HR move towards a more responsive, employee-focused model. But GenAI still works within the limits of the prompts it receives. It enhances productivity, not decision-making. Agentic AI builds on this by introducing autonomous action – planning, adapting, and executing tasks in real time to support evolving workforce needs more intelligently and at scale.
Leading Use Cases of Agentic AI in HR
Agentic AI is redefining how HR operates; not by replacing people, but by giving teams a responsive, intelligent system that works behind the scenes to personalise, prioritise, and act. These capabilities help HR teams move from static workflows to living, adaptive systems that support employees in real time.
Onboarding Orchestration. Agentic AI coordinates onboarding journeys dynamically – scheduling meetings, nudging mentors, tracking task completion, and adapting the flow based on real-time feedback. If a new hire flags confusion or drops off mid-process, the system adjusts instantly, resends steps, or escalates support. The result is a personalised, seamless experience that sets the tone for inclusion and engagement from day one.
Attrition Prediction and Retention Planning. By monitoring signals like reduced engagement, sudden PTO, or changes in team behaviour, Agentic AI can identify at-risk employees before they resign. It then suggests targeted retention strategies based on context, such as recognition nudges, growth conversations, or team adjustments, allowing HR to intervene early and with precision.
HR Service Delivery at Scale. Agentic AI answers common employee queries about leave balances, policies, and benefits immediately and accurately, across channels like Slack or email. It reduces wait times, lowers HR workload, and ensures employees get consistent, policy-aligned answers. Complex or sensitive cases are routed to the right human stakeholder with full context for faster resolution.
Organisational Health Monitoring. Sentiment doesn’t live in surveys alone. Agentic AI aggregates data from exit interviews, Slack threads, survey responses, and internal communications to identify patterns – burnout risk, morale dips, misalignment – and surface them as real-time dashboards. This gives leaders continuous visibility into cultural health and the opportunity to act before small issues escalate.
When GenAI and Agentic AI Work Together, HR Moves Faster – and Smarter
The real power of AI in HR lies not in isolated tools but in the synergy between two complementary capabilities. GenAI provides content intelligence, efficiently drafting, summarising, and personalising at scale. Agentic AI adds a layer of orchestration, reasoning, planning, and acting in real time. Together, they move beyond simple task automation to fundamentally reshape how HR thinks, responds, and leads, turning reactive processes into predictive insights, shifting HR’s role from support to strategic partner, and transforming manual work into more meaningful, human-centred action.
Beyond Tasks: AI as a System-Level Enabler
While the figure highlights clear task-level gains, GenAI and Agentic AI also enable more advanced HR capabilities:
Workforce Modelling and Headcount Planning. Agentic AI evaluates business priorities, project demands, and team capacity to recommend hiring, restructuring, or upskilling strategies. GenAI supports this by synthesising these insights into clear headcount proposals, role rationales, and scenario narratives for leadership decision-making.
Policy Testing and Scenario Simulation. Whether trialling a hybrid work policy or reworking bonus schemes, Agentic AI can model their downstream effects on retention, productivity, and morale. GenAI helps HR teams communicate these implications through simulation reports and change briefings that bring potential outcomes to life.
Culture Mapping and Sentiment Analysis. Agentic AI continuously gathers and interprets signals across employee surveys, internal chat platforms, and exit interviews to track how organisational values are expressed and where they may be eroding. GenAI turns these inputs into thematic summaries, heatmaps, and action plans for cultural reinforcement.
Manager Coaching and Engagement Support. Based on indicators like rising absenteeism or declining engagement, Agentic AI nudges managers to take early action, whether that’s scheduling a one-on-one, shifting team priorities or offering recognition. GenAI adds value by generating tailored messaging and coaching templates to support those interventions.
Together, GenAI and Agentic AI don’t just optimise HR; they help it lead with greater clarity, care, and conviction.
Human-Centred HR, Powered by AI
GenAI streamlines routine work, while Agentic AI enables HR to anticipate needs, adapt quickly, and lead with insight.
This shift goes beyond efficiency; it’s about reimagining how HR supports people, culture, and performance. Rather than reducing the human element, AI frees HR professionals to focus on meaningful connections, coaching, and fostering inclusive workplaces. Agentic AI doesn’t replace empathy; it strengthens and extends it.
AI adoption is no longer a question of if, but how fast and how well. Most organisations are exploring AI in some form, but they’re moving at very different speeds.
The ones seeing the most value share a few traits: cross-functional collaboration, strong leadership sponsorship, and tight alignment between business and tech. That’s how they sharpen focus, deploy critical skills where it matters, and accelerate from idea to outcome.
But the gap between ambition and execution is real. As one executive put it, “We’ve seen digital natives do in 24 hours what takes our industry six months.” The risks of getting it wrong are just as real; think of Zillow’s USD 500M loss from overreliance on flawed AI models.
When done right, AI benefits every part of the organisation; not just data teams.
“Our AI-powered screening for insurance agents fast-tracks candidate selection by analysing resumes and applications to pinpoint top talent.” – HR Leader
“Conversational AI delivers 24/7 customer engagement, instantly resolving queries, easing team workload, and boosting CX.” – CX Leader
“AI transforms work by streamlining workflows and optimising transport routes, making operations faster and smarter.” – Operations Leader
“Using AI to streamline our sales pipeline has cut down the time it takes to qualify leads, enabling our team to focus on closing more deals with greater precision.” – Sales Leader
“We’re unlocking data value: AI agents personalise customer support at scale, while AI-driven network optimisation ensures seamless IT operations.” – Data Science Leader
In the short term, most businesses are focusing on operational efficiency, but the real wins will be in longer-term innovation and financial value.
For tech teams, this means delivering robust, scalable AI systems while supporting responsible experimentation by business teams – all in a fast-moving, high-stakes environment.
However, that’s not easy.
• High Costs. AI requires substantial upfront and operational spend. Without measurable outcomes, it’s hard to justify scaling.
• Security & Governance Risks. AI heightens exposure to bias, misuse, and compliance gaps. Most organisations lack mature guardrails to manage this.
• Regulatory Uncertainty. Shifting global policies make it difficult to design AI systems that are both future-proof and compliant.
• Skills Shortage. There’s a growing gap in AI and data expertise. Without the right talent, even promising use cases falter.
• Data Challenges. AI needs vast, high-quality data, but many organisations struggle with silos, poor lineage, and inconsistent standards.
Yet the toughest obstacles aren’t technical.
• Limited AI Fluency at the Top. Many leaders lack a practical understanding of AI’s capabilities and constraints, slowing decisions and making cross-functional alignment difficult.
• No Clear Ownership or Strategy. Without clear ownership, AI efforts remain scattered across IT, innovation, and business teams, leading to fragmentation, misalignment, and stalled progress.
• Unclear ROI and Benefits. AI’s value isn’t always immediate or financial. Without clear metrics for success, it’s hard to prioritise initiatives or secure sustained investment.
• Short-Term Pressure. The push for quick wins and fast ROI often comes at the expense of long-term thinking and foundational investments in AI capabilities.
• Rigid Business Models. AI demands adaptability in processes, structures, and mindsets. But legacy workflows, technical debt, and organisational silos frequently stand in the way.
• Change Management is an Afterthought. Many AI efforts are tech-first, people-later. Without early engagement and capability building, adoption struggles to gain traction.
Bridging the Innovation-AI Gap: The Power of Ecosystems
Bridging this gap between AI ambitions and success requires more than technology; it needs a coordinated ecosystem of vendors, enterprises, startups, investors, and regulators working together to turn innovation into real-world impact.
Public-private partnerships are key. In Singapore, initiatives like IMDA’s Spark and Accreditation programmes tackle this head-on by spotting high-potential startups, rigorously validating solutions, and opening doors to enterprise and government procurement. This approach de-risks adoption and speeds impact.
• For Enterprises. It means quicker access to trusted, local solutions that meet strict performance and compliance standards.
• For Startups. It unlocks scale, credibility, and funding.
• For the Economy. It creates a future-ready digital ecosystem where innovation moves beyond the lab to drive national competitiveness and growth.
AI is set to transform the workplace – enhancing productivity and reshaping roles. HR isn’t just a bystander; it’s key to ensuring employees benefit while managing AI’s uncertainties. It’s time HR had a bigger seat at the table.
Here’s where AI adoption in HR stands today.
The Asia Pacific region is rapidly emerging as a global economic powerhouse, with AI playing a key role in driving this growth. The AI market in the region is projected to reach USD 244B by 2025, and organisations must adapt and scale AI effectively to thrive. The question is no longer whether to adopt AI, but how to do so responsibly and effectively for long-term success.
The APAC AI Outlook 2025 highlights how Asia Pacific enterprises are moving beyond experimentation to maximise the impact of their AI investments.
Here are 5 key trends that will impact the AI landscape in 2025.
Click here to download “The Future of AI-Powered Business: 5 Trends to Watch” as a PDF.
1. Strategic AI Deployment
AI is no longer a buzzword, but Asia Pacific’s transformation engine. It’s reshaping industries and fuelling growth. Initially, high costs and complex ROI pushed leaders toward quick wins. Now, the game has changed. As AI adoption matures, the focus is shifting from short-term gains to long-term, innovation-driven strategies.
GenAI is is at the heart of this shift, moving beyond the periphery to power core business functions and deliver competitive advantage.
Organisations are rethinking AI investments, looking beyond pure financials to consider the impact on jobs, governance, and data readiness. The AI journey is about balancing ambition with practicality.
2. Optimising AI: Tailored Open-Source Models
Smaller, open-source, and specialised AI models will gain momentum as organisations seek efficiency, flexibility, and sustainability in their AI strategies.
Unlike LLMs, which require high computational power, smaller, task-specific models offer comparable performance while being more resource-efficient. This makes them ideal for organisations working with proprietary data or limited computational resources.
Beyond cost and performance, these models are more energy-efficient, addressing growing concerns about AI’s environmental impact.
3. Centralised Tools for Responsible Innovation
Navigating the increasingly complex AI landscape demands unified management and governance. Organisations will prioritise centralised frameworks to tame the chaos of diverse AI solutions, ensuring compliance (think EU AI Act) while boosting transparency and security.
Automated AI lifecycle management tools will streamline oversight, providing real-time tracking of model performance, usage, and issues like drift.
By using flexible developer toolkits and vendor-agnostic strategies, organisations can accelerate innovation while maintaining adaptability, as the technology evolves.
4. Supercharging Workflows With Agentic AI
Organisations will embrace Agentic AI to automate complex workflows and drive business value. Traditional automation tools struggle with real-world dynamism, but AI-powered agents offer a flexible solution. They empower autonomous task execution, intelligent decision-making, and adaptability to changing circumstances.
These agents, often using GenAI, understand complex instructions and learn from experience. They collaborate with humans, boosting efficiency, and adapt to disruptions, unlike rigid traditional automation.
Agentic workflows are key to redefining work, enabling agility and innovation.
5. From Productivity to People
The focus of AI conversations will shift from simply boosting productivity to using AI for human-centric innovation that transforms both employee roles and customer experiences.
For employees, AI will handle routine tasks, enabling them to focus on creativity and innovation. Education and training will be crucial for a smooth transition to AI-powered workflows.
For customers, AI is evolving to offer more empathetic, personalised interactions by understanding individual emotions, motivations, and preferences. Organisations are recognising the need for transparent, explainable AI to build trust, tailor solutions, and deepen engagement.
Hit or miss AI experiments have leaders demanding results. In this breakneck AI landscape, strategy and realism are your survival tools. A pragmatic approach? High-impact, achievable goals. Know your capabilities, prioritise manageable projects, and stay flexible. The AI winners will be those who champion human-AI collaboration, bake in ethics, and never stop researching.
AI is redefining HR – are you ready?
Here’s some data-backed guide to advancing AI in HR for 2025. It’s no longer just about recruitment; AI is reshaping everything from employee experience to strategic decision-making.
To stay ahead, focus on:
• Setting clear goals with HR-specific KPIs
• Prioritising ethics & transparency in AI use
• Embedding Human-AI collaboration into HR practices
• Taking a seat at the table in AI strategy discussions
Listen to part 2 of the conversation between Sash Mukherjee, VP Content & Industry Research, Ecosystm and Kathryn Finch, Head of HR – Yum Digital & Technology, Yum! Brands.
Listen to Kathryn’s views on the continued impact of the Great Resignation, and the need to evolve people strategies to promote employee retention. Kathryn also talks about how HR leaders and tech teams can come together to create a positive work environment.
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In this episode of EcosystmPodcast, Sash Mukherjee, VP Content & Industry Research, Ecosystm is in conversation with Kathryn Finch, Head of HR – Yum Digital & Technology, Yum! Brands.
Hear Kathryn’s views on:
- The ways to build global, borderless organisations
- The relevance of a unified corporate culture in today’s world
- The role of leadership in shaping People & Culture strategies
In part 2 of the conversation, Kathryn talks about the ways to build HR-Tech synergy.
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The first impact of the pandemic and the disruption it caused, was organisations scrambling to empower their remote employees. Over the last 2 years, significant investments have been made on collaboration platforms and tools. Now organisations are having to work towards making these workplaces truly hybrid where organisations have to ensure that all employees get the same experience, irrespective of where they choose to work from.
In 2022, organisations will continue to invest in building the Digital Workplace and address the associated technology, people, and process challenges.
Read on to find out what Ecosystm Analysts, Audrey William, Tim Sheedy and Venu Reddy think will be the key trends for the Digital Workplace in 2022.
Click here to download Ecosystm Predicts: The Top 5 Trends for the Digital Workplace in 2022 as PDF
Digital and IT organisations are going through some dramatic changes as they adopt cloud and as-a-service capabilities. In this post, I want to write about two of these – one that is very much a consequence of the other.
Contract Numbers are Exploding
We’re seeing an explosion in the number of IT suppliers to a typical organisation.
Pre-cloud, the typical organisation probably had five to ten contracts that covered most of the external services that were in use. With suppliers increasingly providing niche functionality and the increased use of credit cards to buy external services, it is often difficult to determine exactly how many contracts are in place. Or, indeed, have a clear understanding of the terms and conditions of each of these contracts.
Where once an organisation might have had contracts for an on-premises ERP and CRM system, a typical organisation will still have those contracts as well as a supply chain forecasting service, a marketing email management tool, not to mention online spreadsheets and task management capabilities.
So with many more contracts in place, the complexity of managing these contracts and understanding the technical, legal and business risks encapsulated in these contracts has become dramatically more difficult.
I’ll return to this point in a later post, as most organisations struggle with this increasing complexity.
What Is Happening to Your People?
The existence of these contracts means that you are increasingly becoming dependent on the people employed by these external organisations. But when you sign up for these contracts, do you investigate how these suppliers develop their talent?
The New Zealand Herald recently carried an interesting article on one organisation that has developed a paid intern program. Something very rare in the industry.
The article prompted me to think through some of the implications of using cloud services. Tech buyer organisations will have less need for technical capabilities as increasingly these are delivered by the cloud suppliers.
But the growth in demand for digital and IT skills just continues to increase as more and more industries digitalise. In the past, tech buyer organisations would have invested (at least the good employers did!) in the development of their people. The cloud suppliers are increasingly doing this talent development.
Most contract negotiations are based on cost, quality and customer service. A significant proportion of cloud contracts are now boilerplate – you pay with a credit card for a monthly service and have little or no ability to negotiate terms and conditions.
The trade-off is required to get a short commitment term and a variable cost profile. No tech vendor can afford to negotiate bespoke contracts for this type of commercial arrangement.
This situation leaves the question of how tech buyers can influence tech vendors to develop their people’s talent appropriately. Some would say that the tech vendors will do this as a matter of course, but the statistics, as highlighted in the Ecosystm research data in Figure 1, show that we are not bringing people in at the rate the industry requires.
Advice for Tech Buyers
I recommend you look closely at using two tactics with the tech vendors that you are working with:
- First, look to consolidate as much workload as practical under a single contract with the supplier. This is not a new recommendation for contracts – but with the increasing use of boilerplate contracts, it is one of the few ways an organisation can increase its value and importance to a tech vendor.
- Second, start finding those tech vendors that are developing new and existing talent in practical ways and favour these organisations in any purchase decision.
Most organisations, individually, do not have the commercial power to dictate terms to the cloud providers. Still, if enough tech buyers adopt this critical criterion, the cloud providers may see the value in investing in the industry’s talent development in meaningful ways.
The downside? Talent development does not come free. Tech buyers may need to pay a higher fee to encourage the suppliers but paying a low-cost provider who does not develop their talent sounds like a recipe for poor quality service.
If you would like to discuss any of these thoughts or issues further, please feel free to reach out and contact me. This is an industry issue and one for our broader society, so I would be interested in hearing how your organisations are addressing this challenge.
