Singapore, December 1, 2025 – As 2026 approaches, one message is clear: innovation and integrity must advance together. The past year has shown how rapidly emerging technologies – particularly Artificial Intelligence (AI) and automation – are redefining not only productivity, but the very nature of digital trust. The year ahead will challenge organizations to move beyond experimentation and establish guardrails that ensure technology serves as a force for resilience, not risk.

AI: A Dual-Edged Catalyst

Artificial intelligence is transforming cybersecurity at every level. AI-driven threat detection, automated incident response and predictive analytics have become vital tools for defending against increasingly sophisticated attacks. Yet, AI is also creating new vulnerabilities – and even enabling AI-powered attacks that are faster, more adaptive and harder to detect.

Adversaries are increasingly using AI to automate reconnaissance, craft realistic phishing campaigns, develop sophisticated malware and identity weaknesses in real time. AI tools can amplify the scale and speed of traditional cyber threats, giving attackers the ability to exploit systems and users with unprecedented precision.

As both defenders and attackers harness AI’s capabilities, the margin for error continues to shrink. Without strong access controls, generative and agentic AI systems can be manipulated through prompt injection or data poisoning, leading to misinformation, data corruption and unauthorized model changes.

“These ‘AI-powered’ threats highlight the importance of identity and access management within AI environments. Implementing least-privileged access, continuous session monitoring and role-based permissions ensures that only authorized users – human or machine – can interact with sensitive datasets and training models. In 2026, success will belong to those who treat AI security not as an afterthought but as a prerequisite for innovation”.

Zero Trust as the Foundation for AI-Ready Security

Across the Asia-Pacific (APAC) region, digital transformation is accelerating, and so are cyber threats. Attackers are already leveraging AI to automate phishing, create deepfakes and launch targeted social engineering campaigns that are increasingly difficult to detect. The response must be equally intelligent and adaptive.

“A zero-trust security model where every access request is verified, and every privilege is temporary, provides that adaptability. In a world of autonomous systems and machine-to-machine communication, zero trust ensures that no identity, device or process is trusted by default. When paired with Privileged Access Management (PAM), zero trust enforces strict oversight of high-level accounts, reduces lateral movement after compromise and strengthens defenses against both human and AI-driven attacks. This layered approach aligns directly with evolving global directives that emphasizes identity-first security, secure software development and least-privilege access as foundational cybersecurity principles”.

The Rise of Non-Human Identities

As automation and AI become embedded across workflows, organizations are managing an expanding population of Non-Human Identities (NHIs), such as digital entities such as bots, service accounts and AI agents that access data, APIs and applications autonomously. Each of these identities requires authentication, permissions and continuous oversight. Without proper governance, they can create blind spots in visibility and control, allowing attackers to exploit unmonitored access paths.

“Applying zero-trust and least-privilege principles to machine identities must be considered essential. Every Non-Human Identity (NHI) should be uniquely identifiable, auditable and subject to the same access policies as human users. Extending identity and access management frameworks to include these automated entities ensures accountability and prevents credential misuse in increasingly autonomous environments,” added Takanori Nishiyama, SVP APAC and Japan Country Manager, Keeper Security.

Secure-by-Design in the Era of Automation

Another key trend shaping 2026 is the convergence of secure-by-design principles with AI-driven development. Building systems that are secure by default minimizes the need for constant patching or reactive fixes after an incident occurs. Integrating protections like Multi-Factor Authentication (MFA), Single Sign-On (SSO) and comprehensive logging from the start helps ensure resilience throughout a product’s lifecycle.

AI can also play a constructive role here, enabling proactive threat modeling and real-time code analysis to detect vulnerabilities early in the design process.

“AI itself must be protected from model bias, data poisoning and unauthorized manipulation, reinforcing the need for identity controls, PAM and zero-trust architectures as the foundation of secure software ecosystems,” says Takanori Nishiyama, SVP APAC and Japan Country Manager, Keeper Security.

Quantum, Compliance and the Expanding Risk Horizon

Looking beyond AI, quantum computing is steadily emerging as both a breakthrough and a looming challenge.

“Preparing for the post-quantum era requires organizations to begin adopting quantum-resistant encryption now. The “store-now, decrypt-later” threat where adversaries harvest encrypted data today for decryption once quantum capabilities mature, demands proactive mitigation through cryptographic agility and long-term data protection strategies. At the same time, regulatory frameworks across APAC are tightening around privacy, data residency and AI governance. Organizations that embed compliance into their security architecture – rather than treating it as a box-checking exercise – will be better positioned to adapt to new standards while maintaining innovation and speed,” says Takanori Nishiyama, SVP APAC and Japan Country Manager, Keeper Security.

From Innovation to Accountability

2026 will not simply reward organizations that adopt the newest technologies – it will reward those that adopt them responsibly.

“Cybersecurity can no longer lag behind transformation cycles; it must define them. Enterprises that combine AI-enhanced defenses with zero-trust principles, enforce PAM to govern both human and non-human identities and integrate secure-by-design practices will strengthen both resilience and reputation,” concluded Takanori Nishiyama, SVP APAC and Japan Country Manager, Keeper Security.

Innovation is accelerating faster than ever. The challenge for 2026 is to ensure that progress remains anchored in trust – the foundation of every secure digital future.

The report goes beyond showcasing AI innovation—it provides a strategic roadmap for objective driven and responsible AI adoption in Indian healthcare. AI has hundreds of applications across healthcare value chain, and this report reflects on 25+ real world uses cases from Indian healthcare providers and mapping a phased transformation journey—enable, embed, evolve. It also addresses critical challenges such as data fragmentation, ethics, governance, and workforce readiness, offering a blueprint for integrating AI across clinical, operational, and public health domains.

Key Insights from the Report:

• AI in Self-care & Health Management: Personalised tools for proactive health monitoring and risk prediction.
• AI in Patient Onboarding & Engagement: Multilingual chatbots, automated scheduling, and tailored care journeys.
• AI in Clinical Screening & Diagnosis: Faster, more accurate diagnostics using predictive algorithms and imaging tools.
• AI in Hospital Operations: Enhanced resource planning, discharge processes, and performance analytics.
• AI in Public Health: Real-time disease surveillance, climate-sensitive forecasting, and population health management.
• Governance & Ethics: Emphasis on data privacy, ethical safeguards, and stakeholder alignment.
• Technology Landscape: Use of Generative AI, speech recognition, agentic AI, machine learning, and RPA

Commenting on the report, Lalit Mistry, Partner and Co-head, Healthcare, KPMG in India said, “This paper explores the transformative role of AI in connecting the dots between vast untapped data, disconnected systems into a unified, intelligent network that delivers personalised and effective care. Providers across public and private sector can unlock huge value and efficiency by adopting AI-driven transformation to deliver better care and outcomes.”

Future healthcare success demands a new level of cross-functional collaboration across healthcare care settings and healthcare workforce. Tomorrow’s healthcare will be intelligent, not just artificially, but seamlessly integrated. With AI at the core, people, services, and providers unite to reimagine care, uplifting and not replacing, the human capabilities, to deliver smarter, more connected healthcare outcomes.

• 33% of firms are actively developing proprietary AI agents in-house, though only 10% have deployed at scale
• Nearly half of banks and insurers are creating new jobs to supervise AI agents

Paris, November 12, 2025 – Financial institutions are actively moving key customer-facing processes to AI agents, marking a rapid transformation in how customers interact with banks and insurers. According to the Capgemini Research Institute’s World Cloud Report in Financial Services 2026, the top processes for banks to deploy cloud-native, AI agents at scale include customer service (75%), fraud detection (64%), loan processing (61%) and customer onboarding (59%). Insurers display a similar pattern, with customer service also leading the way (70%), followed by underwriting (68%), claims processing (65%), and onboarding (59%) – collectively redefining the concept of what it means to be a financial services customer.

Recent data from the Capgemini Research Institute shows that AI agents could deliver up to $450 billion in economic value by 2028, signaling the opportunity that exists for the financial services industry. To capitalize on this opportunity, 33% of banks say they are developing their own AI agents in-house, while 48% of financial institutions are creating new roles for employees to supervise agents.

With AI agents capable of autonomously managing complex workflows, the role of cloud is shifting beyond just an infrastructure or storage provider. Nearly two-in-three executives (61%) now identify cloud-based orchestration as critical to their AI strategy, transforming cloud platforms into innovation engines that can operationalize technologies at speed and scale.

“The combination of AI and cloud allows banks and insurers to tap the power of AI agents to better serve their customers with greater precision, speed and impact,” said Ravi Khokhar, Global Head of Cloud for Financial Services at Capgemini. “Our data reveals widespread industry optimism that the agentic era will open doors to new markets, signaling a new phase of transformation is upon us. To realize this potential, financial institutions must take a long-term view as humans work alongside agents. This means separating substance from hype. Leaders will need to consider how they can scale their agentic AI operation overtime, with a vision of what they want their businesses to look like at the end of this process.”

Only 10% of firms have implemented AI agents at scale

AI agent adoption is poised for rapid growth as 80% of financial services firms are in the ideation or pilot stage of deployment. However, a sizable opportunity remains to be unlocked as only 10% of firms surveyed have implemented AI agents at scale.

According to the report, banking and insurance executives identify customer onboarding and ‘Know-Your-Customer’ (KYC), processing loans and claims, and underwriting as the most inefficient business functions across the sector.  Firms are optimistic that agentic AI can address these longstanding challenges, with real-time decision-making (96%), improved accuracy (91%) and faster turnaround times (89%) cited as key benefits.

Beyond efficiencies, executives view AI agents as capable of delivering real business outcomes:

• 92% say that AI agents will help them expand into new geographies without heavy upfront infrastructure
• 79% believe cloud-native AI agents can unlock dynamic pricing and offers, maximizing revenue and outmaneuvering competitors
• 75% see an opportunity for delivering multilingual support that adapts to local regulations and cultural norms

With immense potential to become a force multiplier across the enterprise, C-suite executives are aligning their investments accordingly: nearly two-in-three leaders indicate that up to 40% of their organization’s generative AI budget today is allocated specifically toward agent technologies. By 2028, one-in-four firms expect to increase their spending on AI agent solutions by up to 60%.

Banks face lingering challenges to adoption

As financial institutions ramp up adoption of generative AI and AI agents, nearly all executives unanimously point to two critical roadblocks: a looming skills gap among business leaders and employees (92%) and a regulatory and compliance burden (96%). While expressing concern about the complexity of managing region-specific regulatory mandates, most executives (89%) simultaneously place compliance at the top of their organizational priorities over the next three years.

High implementation costs also emerge as a barrier to delivering real returns on AI investment. A growing number of firms (25%) are leaning towards the service-as-a-software model in the next 12-to-18 months, orchestrating a new approach for how AI is consumed and monetized. Rather than paying for licenses and infrastructure, firms will pay for outcomes such as fraud cases resolved, transactions processed, or customer queries handled.

Organizations embrace intelligent workplace technologies to enhance productivity, collaboration, employee experience, ISG Provider Lens report says

India, November 4, 2025 — A new study released today by digital travel platform Agoda shows that artificial intelligence (AI) adoption is high among software developers in Southeast Asia and India, but its usage is still maturing. Developers use it pragmatically to accelerate work without compromising quality, while organizations face the challenge of putting in place the policies, practices, and frameworks needed to support the next phase of AI evolution in the region.

Drawing on extensive input from the developer community across Indonesia, Malaysia, Thailand, the Philippines, Singapore, Vietnam, and India, and drawing insights from leading regional companies such as Carousell, MoMo, Omise and SCB 10X, the report highlights three interconnected findings on AI adoption across Southeast Asia and India:

AI is mainstream but not mature

Across Southeast Asia and India, AI has become a daily companion in developer workflows. 95% of developers use AI weekly, and 56% always keep an AI assistant open. Productivity drives adoption, with 80% citing speed and automation as their main motivation. Engineers are seeing tangible results, with 37% saving four to six hours per week.

Yet AI remains primarily a productivity tool rather than a creative partner. Only 22% use it to solve unfamiliar problems, and less than half (43%) believe it can perform at the level of a mid-level engineer.

While 94% rely on AI for code generation, usage drops for downstream tasks such as documentation, testing, and deployment. This highlights a gap between use and reliability, pointing to the need for more consistent, dependable results.

AI is evolving through accountability

Oversight and verification are increasingly embedded in daily AI workflows. 79% of developers cite inconsistent or unreliable outputs as the primary barrier to broader AI use. To maintain quality, 67% review all AI-generated code before merging, and 70% routinely rework outputs to ensure correctness.

Formal policies are still rare; only one in four (25%) teams operate under official AI guidelines. Yet reliability continues to improve through team-led reviews and validation processes. This focus on verification doesn’t slow innovation; it strengthens it, allowing developers to move faster while keeping quality high.

Most (72%) developers report clear productivity gains and better code outcomes, proving that human oversight remains central to responsible AI adoption.

AI experience is uneven and risks creating gaps

With adoption now near universal, the focus has shifted to how developers use AI responsibly and effectively. Most developers are self-taught, 71% learning through tutorials, side projects, or online communities, while only 28% receive employer-led training. Access to structured programs also varies by market: developers in Singapore are almost twice as likely as those in Vietnam to have formal AI training programs.

Despite these gaps, developers are driving their own growth. 87% have adjusted their learning or career plans to leverage AI, and 62% expect it to expand career opportunities, laying the foundation for stronger, long-term capability across the region. This self-directed growth reflects a workforce learning faster than organizations can train, ambitious, experimental, and increasingly AI-literate.

“Artificial intelligence is reshaping how developers across Southeast Asia and India build, learn, and collaborate,” said Idan Zalzberg, Chief Technology Officer at Agoda. “What began as a way to speed up tasks like writing, testing, or debugging code has grown into a broader shift in how software is built. Today, AI helps teams move faster, learn continuously, and solve problems in new ways. “In this region, AI use is mainstream but still uneven. Developers are approaching AI with pragmatism – accelerating work, maintaining quality, and experimenting thoughtfully rather than replacing skill or judgment. The real opportunity lies in supporting this ground-up maturity with structured practices and responsible experimentation, turning high adoption into consistent, lasting capability.”

Confidence in AI high amongst developers in India

Across the region, India’s developer community is showing the strongest confidence in AI’s potential. 16.2% of India-based developers say they are “very confident” AI can already match a mid-level developer’s abilities – the highest among the seven markets surveyed. This signals a bold belief in AI’s capability, even as broader skepticism persists.

Daily use of AI as a core part of the coding workflow is also higher in India when compared with other surveyed markets. Nearly two in three (65.3%) developers say they always use AI when coding, while another 28.7% use it occasionally. This demonstrates that day-to-day developer practices in the country are now deeply AI-enabled, moving well beyond early experimentation.

The study was commissioned by Agoda and conducted in partnership with Macramé Consulting. As a leading digital travel and technology company in the region, Agoda is dedicated to upskilling local tech talent, fostering innovation, and investing in the communities where it operates. By sharing these findings,

Agoda aims to support developers in building the skills and frameworks necessary to drive the region toward becoming the Silicon Valley of Asia, combining cutting-edge technology with a culture of responsible, collaborative growth.

A new study by Accenture has found that European organizations are placing greater emphasis on maintaining control over data and infrastructure which is likely to accelerate the demand for sovereign AI.

Sovereign AI refers to the ability of a country to develop and deploy AI using local infrastructure, data, models and talent to protect data from foreign access, bolster competitiveness, and decrease reliance on overseas technology providers.

In Europe, 62% of organizations are seeking sovereign solutions in response to current geopolitical uncertainty, a concern that’s heightened among Danish (80%), Irish (72%), and German (72%) organizations. Sectors with regulatory requirements and sensitive data are most likely to lead sovereign AI adoption including banking (76%), public service (69%), and utilities (70%).

This trend is expected to grow over the next two years, as 60% of European organizations plan to increase investments in sovereign AI technology especially those in Germany (73%), Italy (71%) and Switzerland (64%).

Mauro Macchi, Accenture CEO for EMEA commented, “Europe is facing an AI paradox. Its leaders understand the need to accelerate AI adoption to spur innovation and drive growth. But at the same time, because most AI technologies originate from outside the region, it could also be seen as a risk. A sovereign AI approach can help resolve this challenge by enabling European organizations to protect critical operations without hampering innovation and competitiveness. It’s with an innovative and thriving economy that we’ll be able to invest in strengthening our technology ecosystem, enabling local champions to grow and compete on the global stage.”

Balancing data control and access to global innovation
The survey highlights that, on average, just one-third (36%) of AI initiatives and data within European organizations require a sovereign approach due to regulatory requirements or data sensitivity. Capital markets and public services are sectors where such measures apply to a higher share of data.

European organizations are seeking a balance between data control and access to global innovation, with 65% acknowledging that they cannot remain competitive without non-European technology providers. 57% are considering using sovereign solutions from both European and non-European providers.

For its part, Accenture is helping Telia Cygate gain an early lead helping Swedish organizations adopt scalable and secure AI services. Accenture is also working across the ecosystem in Europe, including with AI infrastructure providers like Amsterdam-based Nebius, to provide clients with a foundation for their own sovereign AI factories that enable them to meet data residency requirements. Nebius is an AI cloud platform engineered to support the full lifecycle of AI workloads, integrating custom hardware, proprietary software and energy-efficient data centers located across Europe and the Middle East.

Mauro Capo, Digital Sovereignty lead for Accenture in EMEA said, “A sovereign AI approach is not about holding everything in one place. The goal is to make technology choices according to the degree of control organizations want to exercise over data, AI infrastructure and models, while benefiting from the scale, service breadth and pace of innovation that some non-European providers offer. These choices are decided by the use case and national priorities. Some cases need only local data residency, while others, in defense for instance, call for full sovereignty over the different AI components – local data, infrastructure and model, advanced encryption, or even air-gapped systems when necessary.”

Reframing sovereignty, from risk management to competitive advantage
Only 19% of organizations view sovereign AI as a competitive advantage, while 48% cite compliance requirements as their primary motivation for adopting sovereign solutions. Sovereign AI is still perceived as a technical issue within businesses, as only 16% of European companies have made AI sovereignty a CEO or board-level concern.

However, there’s a growing recognition of its strategic importance, with 73% of organizations calling for governments and institutions, such as the European Union, to play a key role in enhancing Europe’s digital sovereignty, through regulations, subsidies, or public investments. Small and medium enterprises are also seen as critical in this pursuit, with 70% of organizations considering it as important to helping them access sovereign solutions.

Accenture recommends four actions to maximize opportunities from sovereign AI:

1. CEO Ownership: Sovereign AI must be a CEO-led priority, aligning AI strategy with enterprise risk, growth, and geopolitical realities for maximum impact.
2. Reframe Sovereignty: Organizations should shift from viewing sovereignty as mere risk mitigation to leveraging it as a source of value creation and competitive advantage.
3. Expand Your Ecosystem: Companies should build hybrid ecosystems that combine local trust with global innovation, tailoring sovereignty measures to where they matter most.
4. Redefine Architecture: Firms need to architect AI across a multi-cloud continuum, embedding sovereignty into every layer – data, infrastructure, models, and applications – for resilience and adaptability.