HR Technology
AI-ready or just change-ready? Oracle’s Yvette Cameron explains the difference
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It’s about having the right mindset and having the human option always present, and importantly, having leadership who’s ready to kick-start the process.
The workplace cannot function without Artificial Intelligence (AI). Not only for personal productivity, but at the organisational level. However, People Matters SHRPA 2025 research found that only 24% of leaders are using AI—despite 86% claiming they’re ready for change. What is happening here?
To unpack this disconnect, People Matters CEO Pushkar Bidwai joined Yvette Cameron, Senior Vice President, Global HCM Product Strategy, Oracle Corporation, for a deep-diving conversation where Yvette drew on her long experience with business and technology to explain the concerns that people in leadership express. As Asia's largest community and media platform for HR and Talent leaders, People Matters is delighted to bring the key takeaways from this discussion.
“While AI adoption in our personal lives feels natural, enterprises, especially in HR, often face greater hesitation,” said Yvette. For instance, she pointed out that leaders worry about how AI makes decisions, whether its recommendations are trustworthy, clear, explainable, and transparent. They question if the technology will ‘hallucinate,’ whether they have the right skills to work with AI effectively, and how to frame the right questions.
Yvette stressed that concerns also extend to implementation, keeping data secure, integrating across disparate systems, and managing change. These fundamental barriers, she said, can slow HR leaders from embracing AI. And to overcome them, it’s important to understand that the needs and solutions are different for every organisation.
“At Oracle, we work to address these concerns head-on, helping organisations step back to identify their specific barriers and explore options to overcome them—because not all AI is the same, and our approach is uniquely designed to build trust and deliver value,” she added.
Change readiness vs AI readiness
People Matters research shows that while 86% of the CHROs in the Asia-Pacific are change-ready, just 29% of them are AI-ready. As Pushkar pointed out, this is a curious data point; and Yvette had a good metaphor ready for it.
"It’s interesting to see HR leaders say they’re generally change-ready but not necessarily AI-ready. It’s like saying you’re ready to drive a car, but there’s no fuel in it—because today, especially in HR, the future is driven by AI. You can’t truly be change-ready if you’re not AI-ready.”
In other words, she explained that change readiness is about the willingness and ability to adapt processes, policies, and structures we’ve known for years.
“But when leaders hear ‘AI readiness,’ they often think they’re not there yet, or they focus on concerns like data governance and security. The truth is, AI readiness doesn’t require perfection—it requires a starting point and the right mindset.”
For Yvette, being AI-ready means being willing to start, and from the perspective of a facilitator like Oracle, starting involves helping organisations overcome the common barriers: protecting data, ensuring embedded AI follows the same security model and access controls, eliminating integration headaches, and enabling the use of both internal and external data.
“Once organisations see what’s possible, they realise they’re not just change ready, they’re AI ready too," she said.
Interestingly, just a small increase in AI readiness may lead to a much larger increase in implementation. Across the board, Yvette said, AI adoption has grown significantly from last year to this year. She has heard from multiple customers who once said, “We’re not ready; we need governance in place—” and who are now actively using various AI tools across regions.
In India’s context, IT services, manufacturing, and shared service centres are prime for AI-powered augmentation, she noted. The greatest areas of opportunity are high-frequency, high-volume, and high-impact processes like onboarding, recruiting, payroll, help desk support, and compliance. “The aim isn’t just automation, it’s about adding personalisation, context, and speed to deliver better support at scale and with cost efficiency.”
Compliance in particular, she said, is a great example. India’s frequent regulatory changes and complex labor laws make Q&A agents incredibly valuable, because they can be instantly updated with new policies, filings, or regulations, which ensures accurate, contextual answers for employees and managers. This is vital for industries with high hiring and turnover rates.
“We’re seeing customers deploy AI-powered Q&A agents to quickly answer employee or manager queries on hiring, leave policies, benefits, payroll, and more,” Yvette said.
She pointed out that these agents can be instantly updated with new company policies or regulations, ensuring accurate, contextually relevant responses. For organisations with high turnover and frequent policy changes, this means faster support, better accuracy, and a more empowered workforce.
The agentic AI revolution
When we talk about agentic AI, said Yvette, we mean AI that goes beyond summarising information or creating content; it can answer questions in context, reason, make recommendations, and even coordinate multiple agents to handle complex, multi-step processes autonomously. Think scheduling interviews, recommending compensation changes, or kicking off hiring offers.
The key is trust, she argues. “We’ve designed our agents so humans can stay in the loop at any stage, approving data access, reviewing recommendations, and controlling when actions are taken. Over time, as accuracy is proven, you can shift from full oversight to final approval.”
For Yvette, this is more than embedding generative AI into existing workflows. “Agentic AI can analyse data, evaluate hiring vs. internal mobility, assess timing, identify training needs, and prepare actions, all while leaving you in control of every step.”
She emphasised that data security is paramount, and HR leaders are right to ask about ethics, bias control, and transparency. “We’ve built guardrails into our AI, from prompt design to bias reduction and hallucination prevention, so customers can trust the outcomes.”
These design patterns are embedded into their applications and development framework, meaning clients don’t need to be data scientists or AI experts to build secure, ethical, multi-language AI solutions.
Balancing AI efficiency with human-centric values
All this being said, technology must go hand in hand with humanity, as Pushkar pointed out. Transforming organisations today, he said, requires more than technology; it demands a culture that’s ready to embrace change and AI. So how do you embed inclusivity, innovation, and the ‘Human Touch’ at scale?
Yvette’s response was, simply, that AI should augment human work, not replace it.
“The goal isn’t just to cut time and costs, but to expand what’s possible for people, driving innovation, inclusivity, and better decision-making at scale.”
She shared that AI can go beyond productivity gains by doing the heavy lifting: researching, uncovering hidden patterns, and surfacing insights we might not otherwise see. In workforce planning for example, Yvette said that instead of focusing only on headcount and budget, AI can scan for explicit and inferred skills, analyse external labour market trends, and factor in indicators like cultural fit or attrition patterns.
“This enables richer, more strategic decisions that not only improve efficiency but also strengthen organisational culture,” she explained.
Leaders play a pivotal role in enabling this, ensuring transformation happens at a pace that fuels business productivity while safeguarding inclusivity, fostering innovation, and maintaining the right guardrails.
Yvette shared two main thoughts on this. “I believe the primary role of leaders is simply to get started. It’s easy to put up barriers and dwell on concerns, but we’ve already done the heavy lifting to ensure fairness, equity, appropriateness, and trustworthiness. So, step one is to take that leap.”
Second, for decision-makers weighing whether to roll these tools out, the challenge is finding the balance between leveraging automation for scale and efficiency, and preserving the human touch where it’s essential. “I’m all for efficiency—removing friction wherever possible—but there are moments where human interaction is still critical.”
Using the example of call centre support, she pointed out that fully automated solutions can serve almost all customer needs, but customers will still want to speak with a person if their case is unusually complex or if they need reassurance beyond what AI can provide.
“The key is having the option to opt out and connect with a human. Similarly, in performance reviews, imagine AI automatically assigning low ratings purely based on unmet goals. While that might be factually correct, it ignores important context. A human manager might know the employee was on leave, had their project changed, or had goals that were never updated in the system. That’s where human judgment remains indispensable.”
She argues that automation should augment, not replace, human involvement. Leaders must continuously monitor how these processes are working, how they’re being used, and—most importantly—how employees feel about them.
The ultimate measure is whether people feel supported, treated fairly, and confident in the systems enhanced by AI.
For CHROs and CEOs investing in the future, Yvette emphasised that it’s not just about using AI as a tool, it’s about partnering with it. “CHROs need contextual AI literacy: the ability to interpret AI outputs within the flow of work, applying critical thinking to assess when to act on AI’s recommendations and when to involve humans.” “Over time, as confidence grows, the balance between human intervention and AI autonomy will evolve. The focus shouldn’t be on prompt engineering, but on learning how to work alongside AI to execute work better.”
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