Microsoft Copilot for M365 is the generative AI that revolutionises organisations’ efficiencies by surfacing strategic insights, finding information, assisting with the curation of content, even summarising and planning your day as efficiently as clicking a button! What is missing from this equation is that deploying the technology isn’t as simple as flicking a switch and ‘going live” with Copilot for Microsoft 365. While the competitive advantage Copilot for Microsoft 365 offers is unparalleled, ensuring the protection of your organisation and its information assets requires more than activating the licenses.

This article examines the necessary preparation organisations should go through to prepare and mitigate potential pitfalls before integrating Copilot for Microsoft 365 into your organisation.

Despite the recent surge in interest in AI over the last 12 months, generative AI is a relatively young discipline as a technology that can engage with everyday users conversationally. Just a few years ago, AI was confined to academic research institutions, the subject of peer-reviewed papers and the research conference circuit. Organisations like OpenAI brought this technology to everyday users and now the workplace has realised the possibilities that context-based GenAI offers, igniting the interest in Copilot for Microsoft 365.

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Copilot for Microsoft 365  allows users and workgroups to automate their day, collaborate more efficiently, be more productive and use collated data from across the organisation to make more informed decisions; all based on information reserves that are continually added to.

While there are benefits generative AI can bring, organisations must address significant concerns regarding security and data governance when embracing such technology.

Here we delve into three steps crucial for the successful implementation of generative AI:

 Step One: Prepare the Environment and Consolidate Your Data

“Make Microsoft 365 the core of organisational information “

Making Microsoft 365 the core basis for business data, and therefore business intelligence is the most operationally logical choice for the majority of organisations. Most IT professionals understand that information becomes much more valuable when it is at users’ fingertips in the most-used platforms, rather than kept  in isolated silos. Migrating data into M365 allows the smart algorithms of Copilot for Microsoft 365 to access relevant information, enabling the AI to enhance its understanding of how your organisation works based on the information available to it.

Fortunately, the AvePoint Confidence Platform helps organisations achieve this consolidation of content through migration, a process which goes beyond a straightforward lift-and-shift.

AvePoint Fly empowers organisations to move from on-premises or remote email to digital collaboration platforms like Google Workspaces, Box, Dropbox, Slack and other collaboration platforms to M365. It discovers and maps existing applications and content, creating migration schedules that minimise operational disruption and downtime. With multiple legacy tenants’ data in one place, businesses can start to better capitalise on their digital resources immediately.

Step Two: Identify and Organise

“Strengthen your data to enable strong Copilot for M365 results”

AvePoint’s Insights and Policies provides the framework to identify high risk content and build efficient and compliant workflows automatically to remediate any potential breaches. Reviewing and strengthening information security provides the ability to establish a solid foundation, encompassing robust cyber protections, identifying areas of sensitive and overshared content and classifying of information according to sensible privilege rules. This is a vital preparatory stage to protect your intellectual property (IP) and ensure your information remains secure and accessible to the right audience.

AvePoint Opus streamlines the classification and organisation of information within M365 (amongst other repositories), ensuring a standard approach to manage content that minimises user intervention. The aim is to ensure information remains accessible and supports compliance with relevant standards and legislation while being available to those who need it.

Simultaneously, organisations should reassess privilege hierarchies and security rules, considering the large investments in solutions like Teams, Groups, OneDrive, SharePoint, Power Automate and so on. Resolving and revising access accumulated access rights accrued over the years, helps bolster security and internal operational efficiency through simplification and consolidation.

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Step Three: Continuous data management

“Ensuring relevant resources”

Tools such as Copilot for Microsoft 365 increase their value to the organisation over time, as they continually improve and refine their capabilities with the accumulation of information.

This is however contingent on the accuracy of your information. Keeping information that is no longer relevant and no longer serves a purpose can impact on the accuracy of machine learning’s findings. Information may represent older products or abandoned work practices that are no longer suitable for the organisation’s current environment.

It is however important to properly store and archive all data, both for compliance and as a source of contextual information for business intelligence with Copilot AI. Here, AvePoint Opus has you covered, keeping data accessible and secure.

Addressing ‘data hygiene’ regularly is imperative, yet many organisations have the resources to manage every aspect of their information assets. AvePoint   automates content lifecycle management by automating the archival of inactive or ROT content and disposing of content that has exceeded its regulatory lifecycle. Furthermore, addressing data hygiene issues also offers a mechanism to reducing storage costs associated with M365.

As outlined in this article, the presence of shadow IT and siloed information can significantly impact the effectiveness of generative AI-driven content curation. Just having access to Copilot for M365 as part of a M365 license does not guarantee quality generate content. Without careful consideration of the organisations information structures, classification methods and content lifecycle management, the potential power of generative AI tools are unrealised.

For organisations committed to realising the maximum benefits of Copilot for M365, we recommend seeking specialised guidance to become “AI ready”. As an early adopter of machine learning technologies, AvePoint has assisted hundreds of organisations across various customer segments to unlock the full potential of generative AI.

With AvePoint’s expert guidance, you can navigate the Copilot for Microsoft 365 journey confidently, leveraging  technology that is specifically designed to deliver optimal results.

To find out more about Copilot for M365 and how it and AvePoint can transform your organisation’s approach to data-based driven operations, contact AvePoint for a demo.

The post 3 Steps to Successfully Automate Copilot for Microsoft 365 Implementation appeared first on Tech Wire Asia.

Recent mainstream media coverage of Canada Air’s AI bot mis-step and a New York lawyer’s submission of hallucinated case law show that, at least in the public’s perception, running effective AI instances leaves a great deal to be desired.

Perhaps the disparity between the technology’s potential and its real-world worst-case outcomes is down to the nature of decision-making in large organizations. In fact, an Innovation Catalysts study published this year found that 81% of business decision makers believe there are reasons to exclude the IT department from strategic business decision making. Sure, the IT function has a responsibility to investigate and advocate for technology’s benefits, but it could be argued that there may be broader enterprise concerns that need to be addressed which involves all stakeholders, including IT.

The advantages of deploying AI in workflows for data processing, creativity, and operations are well-known, although every use case varies according to the organization and its approach. But harnessing the technology in production where results are based on local data means considering safeguards around intellectual property and legal & compliance issues, plus the need to embed transparency into the solution. This transparency is important to satisfy regulatory authorities concerned over issues like data processing and sovereignty, as well as customers’ and service users’ concerns about privacy and data practice.

Trustworthy generative AI is a phrase that encompasses a set of smart services and practices that ensure safe operation: trustworthy, legally compliant, and transparent. Building those necessary elements is not a simple undertaking and represents a significant addition to the normal overheads associated with machine learning (compute and storage), and includes extra processes like query & response validation, bias monitoring, data sanitization, and provenance checking.

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Some vendors offer pre-trained models that can form some of the basis of a GenAI solution. But until now, there has been nothing on the market where a solution includes data security, use and development guardrails, manageability, and vendor support. In short, those elements that are mandatory to transform what’s essentially experimental (and therefore has potential risk) into a reliable production-ready platform – which is what Dell and NVIDIA can now offer.

The AI industry is doing its best to address many of the needs of larger organizations that are concerned about some of the potential misfirings that a premature rollout of GenAI could create. NIST’s Artificial Intelligence Safety Institute Consortium (AISIC), for example, has come about to create safe and trustworthy artificial intelligence and comprises more than 200 bodies. It produces empirically backed standards for AI measurement and policy, so organizations leveraging GenAI have guides to safe and legal AI deployment.

NVIDIA, a key member of AISIC, now offers NeMo Guardrails which is designed to support enterprise data security and governance standards, acting as a two-way arbiter between user queries and AI responses.

In enterprise use cases, working with internal data also brings challenges with regard to an organization’s intellectual property. Without proper safeguards, any GenAI instance represents a potential danger to an organization’s ongoing viability. It’s with that challenge and those detailed above that Dell and NVIDIA have partnered to offer a GenAI system that boasts topical, safety and security features, producing the closest to a production-ready, drop-in GenAI solution currently available on the market.

Dell Technologies’ Generative AI Solutions encompass best-of-breed infrastructure designed to greatly simplify the adoption of generative AI for organizations that need the power of machine learning technologies to leverage the value of their digital assets without compromising their ethos, data, customers, or third parties.

Based around the Dell PowerEdge XE9680 GPU-accelerated server, it’s designed for generative AI training, model customization and large-scale inferencing. It comes with NVIDIA AI Enterprise software, which allows rapid deployment of production-ready models in local, hybrid, and remote computing topologies.

The Dell Generative AI Solution range is highly scalable, with hardware that can be expanded according to need, with eight NVIDIA H100 or A100 GPUs fully interconnected with NVLink. The air-cooled 6U devices offer any variation of local and remote deployment at a lower TCO than equitable processing power from other vendors.

With NVIDIA AI Workbench, developers can experience easy GPU environment setup and the freedom to work, manage, and collaborate across workstation and data center platforms regardless of skill-level.

The combination of hardware and software designed from the ground up for generative AI development and deployment, comes with guardrails, data governance, and security baked in. Together, the two mean that organizations can deploy powerful AI-based applications safely and responsibly.

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Building trustworthy generative AI means greater buy-in from business decision-leaders outside IT, as many of their rightly-held concerns around the technology are addressed: transparent development and use, safeguarded IP and customer-facing responses, statutory compliance, and best-in-class operating costs.

To find out more about how the Dell Generative AI Solution portfolio takes machine learning to a fully-viable production setting, contact your nearest representative.

Dell Technologies: https://www.dell.com/en-sg/dt/solutions/artificial-intelligence/generative-ai.htm

NVIDIA: https://www.nvidia.com/en-sg/ai-data-science/generative-ai/

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In one of the largest and widest-reaching surveys on IT in recent years, the Innovation Catalysts study quizzed over 6,000 respondents globally, who gave their answers to a range of queries around innovation, AI, and ML and how their organizations were responding to new technology. (The full survey from Dell Technologies is available here.) The majority of IT professionals (85%) agreed with the proposition that AI and GenAI will significantly transform their industry. And 76% of respondents reported that their organization is already providing intelligent technology in the form of AI optimization software that improves their work experiences.

Given the obvious benefits of AI to all business functions, it’s important, therefore, to understand that access to the compute power and tools required for advanced intelligent algorithms is a prerequisite for today’s businesses. In today’s technology landscape, access to the most advanced AI tools and capabilities can be challenging, especially for businesses looking to innovate and differentiate themselves. The dominance of a few major technology providers has led to a proprietary approach, where the latest AI innovations may be tightly controlled and not easily accessible to a broader range of organizations. This proprietary nature of some AI ecosystems can present obstacles for businesses, especially those in the APJ region, to truly innovate and be creative with AI. They want to use the latest and greatest AI capabilities, but the lack of openness and compatibility between different AI systems gets in their way.

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The need for openness

Developers need open standards to create new uses for AI because it gives them the flexibility to deploy their solutions on-premise, in the cloud, and on edge devices; wherever, in fact, the business’s needs dictate. In parallel with that is the need for compute engines optimized for different devices, capable of delivering AI performance at the point of consumption. Open standards in software and hardware enable interoperability, providing customers the freedom to leverage the AI tools and infrastructure that best suit their unique needs and workflows. This empowers businesses to innovate with generative AI on their own terms, without being limited by a single vendor’s ecosystem.

What the technology industry must pursue, therefore, is a policy of the democratization of GenAI, and those goals are realized by open ecosystems and silicon diversity. Organizations pursuing this strategy of flexibility and choice will gain a significant strategic edge over competitors who primarily rely on public cloud services to manage their AI workloads. This is the key strategy to helping organizations gain a competitive advantage. Empowering businesses with access to the latest hardware optimized for generative AI can further amplify these strategic advantages.

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Powerful hardware

For organizations developing custom AI models and processing large bodies of data, the latest hardware designed from the ground up to be optimized for GenAI significantly lowers TCO, meaning leeway for research and experimentation even within tight budgets.

Better hardware also means projects reach production quicker, and end-users get faster results and an overall better experience. The new Dell PowerEdge XE9680 Server is designed for today’s GenAI workloads. It offers up to eight AMD Instinct MI300X accelerators and provides 1.5TB of coherent GPU accelerator memory per server (the highest ratio in the GPU market currently). That means a lower DC footprint, yet with an increased inference capacity, so very large training datasets can be ingested quickly.

Open software

Hardware power and capabilities unlock an organization’s freedom to innovate without cost overrun, but the software running on it has to offer compatibility with existing AI frameworks, libraries, and models for true portability and compatibility.

Without openness, it’s impossible to achieve that portability across platforms, and therefore, AI can’t be considered democratized. The AMD MI300X Instinct Accelerators in the Dell XE9680 Server, which will be ready to ship in May, offers over 21 petaflops of FP16 performance, yet out-of-the-box, run the common standards in data science of PyTorch and TensorFlow, plus natively supports JAX, Open Neural Network Xchange (ONNX), and OpenAI Triton, inside the AMD ROCm software stack.

ROCm consists of a collection of drivers, development tools, and APIs that enable GPU programming from low-level kernel to end-user applications, and brings together hardware and software optimized for GenAI, large models and fast time-to-market for a business’s AI projects.

AMD’s ROCm is optimized for Instinct MI300X accelerators and is a freely available open software stack that’s capable of evolution and adaptation according to a business’s evolving needs.

An integral part of democratized GenAI is, of course, the open-source ethos. OSS (open-source software) drives quality and excellence, with thousands of users and developers refining and improving the code, allowing increased innovation.

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Better together

Open-source also equates to open flexibility, a situation that means developers can create GenAI-based products and services that operate on a range of devices with upstream support that is available from hundreds of the open-source projects that dominate the GenAI world.

The ultimate flexibility possible today is provided by the combination of the Dell PowerEdge XE9680, AMD’s Instinct MI300X accelerators’ 3rd Gen AMD CDNA (Compute DNA), and ROCm 6 software. A firm foundation and open portability allow businesses and organizations the tools and infrastructure needed to innovate at this critical juncture in technology’s evolution.

GenAI’s transformative powers offer APJ businesses a unique opportunity to develop the next generation of AI-powered software outside the constraints and deliberate roadblocks placed by big tech’s policies of separation and compartmentalization. The horizons can open with just a straightforward deployment configuration tailored to their needs and running on optimized hardware.

To find out more about the Dell PowerEdge XE9680, head to these pages according to your geography: Australia, New Zealand, Singapore, or India. Plus, you can head here to read more about the AMD Instinct MI300X accelerator at the heart of Dell’s next-gen AI-focused hardware.

The post Strategies for Democratizing GenAI appeared first on Tech Wire Asia.

Many endpoint devices are commonly recognisable: the smartphone in your back pocket, the desktop computer or laptop. However, endpoints can also include servers – powerful computers that provide digital services to users, such as file storage, data retrieval, or commonly used applications. When all an organisation’s endpoints are added up, they can number hundreds of thousands in large enterprises.

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Often, even discovering the existence of every endpoint is challenging, a situation that has been made more complicated since the COVID-19 pandemic and the continuing habit of working remotely. Endpoints suddenly included computers in people’s homes or personal laptops used during periods of lockdown.

Within just a couple of years from 2020, the number of endpoints using a company’s network rose sharply, and the number of cybersecurity incidents involving endpoints rose in step. Additionally, the cost of each security breach rose from $7.1m to $8.94m [PDF].

The higher number of endpoints in today’s businesses also means that more devices have at least the capability to delete, corrupt or compromise valuable data. Managing endpoints, therefore, means ensuring that devices work safely, whether from the actions of bad actors, from misuse or operators’ mistakes.

It’s clear, therefore, that managing and securing these devices needs to be at the forefront of any organisation’s cybersecurity and device management priorities. A properly managed and monitored endpoint fleet gives IT teams a clear definition of the devices it’s responsible for and a head-start on tracking down and responding to incidents caused by attackers or so-called internal threats. It also shows which devices are at greater risk of possible compromise, informing teams which endpoints need updating, patching or replacing, and with what priority.

Putting in place a rigorous endpoint management system gives organisations the best ROI of any security platform, and should be the foundation of a range of measures designed to protect the organisation’s users, digital assets and intellectual property.

Best practices in endpoint management are discussed in detail in “The Endpoint Defense Playbook: Locking Down Devices with NinjaOne“, which includes advice on how large fleet management tasks can be automated. But for the purposes of this article, let’s consider some steps that any company can take to close off many of the ways that endpoints put their owners’ digital assets at risk.

Audit
Before an IT team can know what they need to monitor, manage and protect, it has to know what devices appear on the network. An audit is therefore an unambiguous first step, although it should be noted that auditing has to be an ongoing process, as day-to-day, endpoints will change as the organisation evolves and the devices used cycle over time. A real-time network map is therefore required.

Secure access
Users, like endpoints, have to be able to prove who they are, and be granted privileges to operate on the company’s network. Passwords, two-factor authentication and single sign-on (SSO) are methods by which employees show they have the rights to be present on the network.

Zero-trust
Zero-trust is a security posture that dictates users and endpoints have no privileges whatsoever on a network by default. Then, policies grant access to applications, services, and devices on a per-case basis. In cases where no policy applies, the system reverts to zero trust or no access.

Encrypt
Encryption means that any data exchange inside or from outside the network is obfuscated and therefore immune to any eavesdropping. Data at rest should also be encrypted, so physical theft of, for instance, storage drives, will not yield any readable data by third parties.

BYOD policies
Since the emergence of the modern smartphone in the mid-00’s, users often prefer the convenience of at least occasional use of their own devices. BYOD (bring your own device) policies can determine which device types are allowed, and also stipulate which versions of software may run and operate on the network. Enacted policies will prevent insecure operating systems and software from running on users’ devices and ensure a maximum level of security among what is an unpredictable population of endpoints.

Proactive scanning
Endpoint detection and response (EDR) systems scan endpoints and log activity to flag anomalous behaviour to users or to systems administrators. Alerts can tell IT staff when action has to be taken to address apparent threats or to surface unusual patterns of behaviour that need further investigation.

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Patch & update
Software vendors are constantly updating their code to ensure that it is as safe as possible from malicious activity. Software on endpoints should run the latest versions of all software (including the operating system) so every device does not carry at least a potential attack vector. Zero-trust policies are applicable in this respect: endpoints not fully up-to-date can be denied access or given limited privileges by default.

Remediation planning

Despite all preventative measures, every network will always suffer some security or misuse issues. It is essential that IT teams have coherent plans that can be followed when there is the possibility of data breach or corruption. Remediation planning also requires the practise of recovery procedures, so teams are aware of the steps they need to take in the event of a possible incident.

Next steps
Endpoint management and security are mutually supportive processes that together form the basis for strong IT security and data loss prevention. In very small companies, it’s possible to manually implement endpoint management on a per-device basis. But in the majority of cases, an endpoint management software platform is necessary to oversee and, where possible, automate management policies.

Creating a strong and safe IT environment for any organisation is essential for a business to operate in 2024, and it’s a subject that requires a great deal of attention. You can read in more detail about the best practices to implement endpoint management in “The Endpoint Defense Playbook: Locking Down Devices with NinjaOne“, which is available to download now.

The post The criticality of endpoint management in cybersecurity and operations appeared first on Tech Wire Asia.

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The conversation around data misuse extends further than generative AI. Consumers are arguably savvier about whom they give their information to and the permissions they grant. This is a consequence of organisational data misuse in the past – individuals are fed up with spam texts and calls. Significant data breaches also frequently make the mainstream news, and word quickly spreads, tarnishing brand reputations.

In recent years, data regulations have tightened to help protect consumers and their information. However, we are only at the start of this journey with AI. While laws are being introduced elsewhere in the world to regulate the technology, like the EU’s AI Act, the Australian government has yet to reach that stage. Saying that, in September, Canberra agreed to amend the Privacy Act to give individuals the right to greater transparency over how their personal data might be used in AI. The government has been put under pressure by business groups to prevent AI causing harm and, in June 2023, a paper was published exploring potential regulatory frameworks. However, at the moment, the onus is primarily on individual organisations to handle their AI technologies responsibly. This includes where the initial training data is sourced and how user data is stored.

Using untrustworthy public data to train algorithms does have consequences. These include so-called ‘hallucinations’, where the AI generates incorrect information presented in a manner that appears accurate. Toxicity can also be an issue, where results contain inappropriate language or biases that can be offensive or discriminatory. Air Canada was recently ordered to pay damages to a passenger for misleading advice given by its customer service chatbot, resulting in them paying nearly double for their plane tickets.

On the other hand, if an organisation uses its own customer data for AI system training, it faces a distinct set of risks. Improper handling can result in the violation of data protection regulations, leading to heavy fines or other legal action. In December 2023, researchers at Google managed to trick ChatGPT into revealing some of its training material, and OpenAI is currently facing a number of lawsuits in relation to the data used to train its chatbot. In January, another data breach exposed that the Midjourney AI image generator was trained on the works of over 16,000 artists without authorisation, which could lead to significant legal action.

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Many core business technologies, like contact centres, utilise large volumes of data, and these are often one of the first targets in a digital transformation. Continuous modernisation of CX is essential to meet the rising expectations of customers. AI instils new levels of intelligence in the platforms used by organisations, for example, anticipating customer needs, making tailored recommendations and delivering more personalised services.

Organisations need to evaluate platforms that have processes in place to ensure they safeguard data and privacy, especially if leveraging AI. So-called ‘green flags’ include compliance with the Notifiable Data Breach (NBD) scheme and the PCI Data Security Standard (PCI-DSS). Enabling consumer trust and confidence in how their sensitive data and transaction history are leveraged and stored is essential. Adherence to relevant governance means organisations are reducing the risk of fraud and security breach by improving data security and bolstering authentication methods, to name just a couple of necessary measures.

It can be easy to get in hot water when embarking on a new venture without expert guidance, and AI journeys are no exception. Partnering with a reputable organisation which understands how the technology best fits in a business can be the difference between success and failure. With Nexon’s expertise, organisations have successfully leveraged a range of AI-powered solutions, from Agent Assist and Co-Pilot tools that streamline customer support workflows, to Predictive Web Engagement strategies that deliver personalised digital experiences and increase sales.

Nexon has forged a strategic partnership with Genesys, a global cloud leader in AI-powered experience orchestration, which prioritises ethical data sourcing and customer privacy. Genesys is committed to understanding and reducing bias in generative AI models, which it uses in its software to automatically summarise conversations for support agents and auto-generate email content for leads and prospects. This is achieved through ‘privacy by design’ principles enacted from the inception of its AI development, an emphasis on transparency into how the technology is applied and the use of tools to find and mitigate possible bias.

Genesys envisions a future where ethical considerations play a central role in all AI applications. Genesys AI brings together Conversational, Predictive and Generative AI into a single foundation to enable capabilities that make CX and EX smarter and more efficient and delivers meaningful personalised conversations (digital & voice) between people and brands.

The company’s customer-centric approach ensures that its cloud platform and AI solutions meet ongoing needs and adhere to strict data, privacy and security protocols.

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As AI elements are introduced, they are tested rigorously to ensure they do not violate the protections that its cloud platform promises. Unlike other solutions, Genesys AI was built securely from its inception. Genesys provides users with control over AI use, providing understanding of its impact on experiences and enabling continual optimisation for better outcomes. Additionally, it provides a thorough exploration of the transformative potential of AI and how to responsibly leverage its capabilities for unparalleled customer experiences. You can read more into this subject in the white paper ‘Generative AI 101‘

Genesys has named Nexon a Partner of the Year twice in a row, thanks to its proven experience and expertise in delivering integrated digital CX solutions. This partnership solidifies the two companies’ collaborative efforts to provide organisations with innovative AI-driven solutions while upholding the highest standards of data ethics and customer privacy. Through this strategic alliance, organisations can navigate the complexities of AI technology, harnessing its transformative potential and drive growth and customer satisfaction responsibly and sustainably.

Contact Nexon today to discover how its AI expertise can drive superior customer interactions and streamline your business operations.

The post Ethical AI: The renewed importance of safeguarding data and customer privacy in Generative AI applications appeared first on Tech Wire Asia.

Organizations and governments worldwide, including Japan, face the dual challenge of mitigating risks and embracing the rapid advancements in AI. This involves managing uncertainties while also accelerating innovation and adoption to reap the benefits of this transformative technology.

Japan’s unique position in AI

Although Japan is known for its cautious approach to risk, it is also renowned for its innovative contributions to technology, particularly in smart robotics and automotive AI. However, reports suggest that Japan’s prowess in AI-powered hardware does not equally extend to its software capabilities, making it reliant on foreign large language models for generative AI.

Japan faces unique AI development and adoption hurdles, including limited data availability and cultural attitudes towards business risk. These factors complicate the integration of AI technologies within traditional business frameworks.

A recent study by Barracuda, titled ‘SMB cyber resilience in Japan: Navigating through doubt to an AI-powered future,’ examines AI’s impact on small to medium-sized businesses (SMBs) in Japan. It reveals a mix of optimism about AI’s benefits and concerns about security, knowledge, and skill gaps.

The research underscores general optimism among smaller Japanese organizations about the positive effects of AI on business operations. The majority of these businesses anticipate that adopting AI solutions will lead to workforce reductions over the next two years—66% foresee fewer full-time employees, and 70% expect to rely less on freelancers and contractors. This trend is expected to lower costs and reduce the human resource demands on companies, though it also highlights a precarious future for workers in roles vulnerable to automation.

ARE YOUR WEB APPLICATIONS SECURE? BARRACUDA REPORTS HIGH INCIDENT AND BREACH INVOLVEMENT

Muhammad Zulhusni | 22 February, 2024

In addition to cost reduction, businesses expect AI to enhance operational efficiencies across various functions, including marketing and customer relations. Approximately 67% predict that AI tools will produce over half of their content soon, and 60% believe AI will become the primary interaction point for customers. Moreover, thanks to AI, 76% anticipate quicker and more accurate customer insights.

Strengthening cybersecurity through AI

On a broader scale, 65% of respondents are confident that AI tools can streamline their cybersecurity needs, reducing reliance on human security teams or third-party services. Given Japan’s acute shortage of cybersecurity professionals, integrating AI for automated threat detection and response is seen as essential for enhancing security across all business sizes.

Most organizations recognize the need for external assistance to fully leverage AI for business benefits. A significant majority of businesses surveyed—76%—indicate the necessity of partners for researching and exploring AI. The same proportion (77%) seek help with implementing AI solutions and managing these technologies on an ongoing basis. Security vendors and managed service providers in Japan are well-positioned to help smaller businesses exploit AI’s advantages.

The release of ChatGPT by OpenAI in November 2022 showcased the capabilities of generative AI tools in creating natural, engaging dialogues. Despite widespread attention, businesses exhibit cautious engagement with generative AI. Awareness does not equate to comprehensive understanding; 56% grasp the distinctions between generative AI and other AI types like machine learning, while 44% admit to limited or no understanding. Consequently, many Japanese companies impose restrictions on AI use due to potential risks.

Approximately 69% of businesses perceive risks with workplace generative AI usage. While 18% permit its use—6% broadly and 12% in limited team settings—62% do not officially sanction it, suggesting covert use that may heighten security risks. Concerns also include data protection (57% of respondents), the absence of regulatory frameworks (47%), and opaque AI decision processes (31%). Additionally, 13% fear AI systems being compromised by cyber attackers.

Risks of using generative AI (Source – Barracuda)

AI and cyber threat evolution

There’s notable uncertainty about AI’s role in evolving cyber threats. About 55% of businesses are unsure how AI could be utilized in email attacks, with similar uncertainty extending to denial-of-service (62%), malware (57%), API attacks (56%), and cyber espionage (55%).

Despite these uncertainties, email threats remain a prominent concern for Japanese small businesses, with 53% highlighting account takeover attacks as a top threat. This form of identity theft allows attackers to misuse accounts, potentially leading to phishing scams, data theft, and more. Other significant threats include phishing and social engineering (37%), with ransomware also critical (39% reported it as a top concern, predominantly initiated via email).

Cyber threats concerning businesses in Japan (Source – Barracuda)

Survey participants generally understand the role of AI in fortifying cyber defenses, especially in areas like email security and employee cybersecurity training. However, there’s some ambiguity about AI’s effectiveness in other domains, possibly due to these areas being less familiar to smaller enterprises.

When asked which AI-enhanced security measures would improve their organizational safety, 36% pointed to AI-enhanced email security, especially against sophisticated threats like deepfakes. Another 24% believed AI could support more tailored, frequent training programs. The benefits of AI in continuous threat intelligence and response, as performed by Security Operations Centers (SOCs), were not as clearly understood.

The survey reveals a deficiency in AI-specific practices and policies needed for responsible AI usage. While 52% of businesses conduct employee training on AI use and vulnerabilities, only 35% have formal policies dictating AI usage. Even fewer have comprehensive governance structures in place, such as legal frameworks. This indicates a lack of control and management over AI applications within businesses.

A YEAR OF HIGH-SEVERITY ATTACKS AND GROUNDBREAKING CYBERSECURITY STRATEGIES IN 2023

Muhammad Zulhusni | 5 March, 2024

The latest ICS2 Cybersecurity Workforce Study shows that Japan has nearly half a million cybersecurity professionals, a notable 23.8% increase from the previous year, contrasting with a global average of 8.7%. Despite this growth, the demand far exceeds supply, with a shortage of 110,254 professionals, marking a 97.6% increase year-over-year — significantly higher than the global average of 12.6%. This gap is unprecedented compared to other nations evaluated in the ICS2 study.

This macro perspective mirrors smaller businesses’ daily challenges, particularly with AI-driven cyber threats.

Makoto Suzuki, Regional Sales Director for Japan at Barracuda, highlights the survey’s findings: Japanese SMBs recognize AI’s benefits for enhancing business productivity but remain cautious about the cyber threats it poses. Suzuki notes, “This could hold businesses back from harnessing the full potential of AI to revolutionize business performance and competitiveness by optimizing processes, reducing costs, improving quality, and providing new insights and ideas.”

The post How Japan balances AI-driven opportunities with cybersecurity needs appeared first on Tech Wire Asia.

A change is occurring in how organisations secure their network perimeters, users, applications and data. Secure access service edge (SASE) is starting to disrupt traditional approaches to networking and security, and is giving IT professionals an opportunity to fundamentally reimagine how they design their network and security architectures.

Previously, enterprise network architecture was based on discrete silos of network and security controls, with remote access provided via virtual private networks (VPNs). These approaches are being rapidly replaced by SASE and zero-trust network access (ZTNA) architectures.

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Getting SASE right can be a complex proposition that presents significant challenges. While major elements that make up SASE have been around in some form for at least 10 years, it is still an evolving technology.

A case study in SASE Success: India Insurance Company

As part of the research commissioned by Verizon Business to help companies cut through the noise to get a true picture of obstacles and opportunities in implementing SASE, S&P Global Market Intelligence conducted 10 in-depth interviews with decision makers and those purchasing SASE technology.

One successful SASE implementation case study was shared in an interview with a VP at one of the largest insurance companies in India, which we will refer to as “IIC” (India insurance company).

“The primary driver [for SASE] was the pandemic. Before, we had a traditional bricks-and-mortar office infrastructure. When the pandemic hit, everything was being provisioned by the company. There was no way to use ‘bring your own devices (BYOD) – only company-owned, hardened machines could be used […] which took 10-15 days to provision,” he said.

Suddenly, many users, particularly contractors, did not meet security requirements because controls were not designed for off-site workers. In response, IIC implemented a SASE project focused initially on data access, followed by applications.

“Now, we can fully support BYOD, which was the hardest problem to solve. We were forced to go with an agentless approach, through an outside portal […] new employees and contractors are now productive from day one instead of waiting for their machine to arrive,” said the respondent, an Executive Vice President and Head of Business Systems and Infrastructure at the IIC, which currently employs over 10,000 people..

The company could immediately improve the user experience, meet remote worker security and compliance requirements, and improve productivity by supporting BYOD, which enabled employees and contractors to begin work immediately.

What is driving SASE adoption?

Some compelling factors driving SASE adoption are the size and maturity of organisations. For more mature, technically sophisticated enterprises, SASE implementations are motivated more by business and digital transformation needs than technical requirements.

Common business drivers include improved business agility, cost reduction, support for hybrid work (office-based and remote workers), improved end-user experience, reduced threat impact and risk, improved compliance and competitive pressure.

Source: Shutterstock

Larger organisations, especially those with over 10,000 employees, tend to suffer from technical debt and incompatible legacy systems that slow down deployments. Conversely, smaller organisations tend to adopt solutions faster and can often source the entire SASE stack from a single vendor.

Common technical drivers include network, security, IT modernisation and simplification, and simplified management of rapidly growing networks.

Key considerations for implementing SASE

Research participants indicated a variety of deployment approaches. None indicated embarking on a “big bang” implementation: some organisations rolled SASE out to high-risk users and apps first, while others chose lower-risk users and applications.

For example, some organisations with high short term risk exposures, such as the potential for breaches or failing compliance audits, chose to solve the issue for those groups first. Others, less concerned about short-term risk, took a more conservative approach like deploying to staff already using modern cloud apps.

“It was all about basic access first to support the remote workforce. Subsequently, it was about business-critical targets and high-risk estates, with quick wins peppered in between,” said one respondent, a Regional Information Security Manager for a large Australian IT services company.

“Any users who can migrate without losing any access to unsupported apps naturally will do so. This provides a faster, better user experience that rewards the user to move to SASE. They were excited to move away from VPN and use [it] as a […] fall-back plan,” said another, a Regional CISO at a large Singapore engineering firm.

Overall SASE projects vary in duration (from initial sign-off to production) from 6-12 months to over three years. Nearly half (45%) of all respondents indicated durations of 12 months or less; another 45% fell in the 13 to 36 month range; and the remaining 10% indicated more than three years to complete a SASE implementation.

In Asia Pacific, only one-third of participants indicated that SASE was deployed as part of a digital transformation initiative, as compared with three-quarters of their counterparts in Europe.

End matters

In the next part of this article, we’ll be looking more deeply into the study’s results, and getting the thoughts of Rob Le Busque, Regional Vice President at Verizon, APAC. In the meantime, head to this page to learn from the experiences of enterprises who have already migrated to SASE, detailed in the report produced in collaboration with S&P Global Market Intelligence.

Continue your exploration of SASE adoption with Part 2 of this feature, which will cover in-depth study results and insights from Rob Le Busque. Check back in the coming weeks for the next instalment and in the meantime, you can explore the research and business impact briefs for comprehensive insights at the following links: Research | Business Impact Briefs.

The post Deploying SASE: Benchmarking your approach appeared first on Tech Wire Asia.

The current state of the insurance industry

TechWireAsia spoke to Nikola Djokic, the Managing Director of Insurance at SAP Fioneer, about the current state of the insurance industry and the challenges it faces. “Insurance is undergoing a revolution,” he said. “The rise of the insurtech and access to data has allowed non-insurance brands to enter the market and offer insurance as part of their offering, adding value to their customers and generating new revenue. Rather than a separate vertical industry, insurance is now taking a role in several ecosystems. This all represents significant new market opportunities for insurtechs, new players and incumbents alike, but the change is rapid, and traditional insurers need to adapt quickly to take advantage of and benefit from the new world order.”

Digitalization has traditionally been hampered in insurance due to legacy systems. Often built over decades, they have created data silos and operational inefficiencies that hinder the adoption of modern technology. Insurers have struggled to integrate new digital solutions seamlessly into their existing infrastructure, leading to fragmented customer experiences and slow response times. Moreover, the risk-averse nature of the insurance industry has contributed to a reluctance to invest in digital transformation initiatives. Insurers have been cautious about migrating sensitive data to the cloud and adopting emerging technologies like AI and machine learning due to concerns about data security, regulatory compliance, and the potential for disruption to established business processes.

Mr Djokic said: “Decisions need to run from the user interface through the middle office to the back office and back again, and these have typically been disconnected. The process of assessing a customer for a policy, or a claim for a payment, traditionally required (and in many cases still requires) a lot of manual intervention.”

Third-party data has been available to facilitate these assessments, but it is rarely integrated into the core insurance solution, making it challenging to meet customer expectations for digital immediacy. “This has allowed new players – neo-insurers – unencumbered by legacy systems or processes to leapfrog ahead in niche areas,” said Mr Djokic.

Insurance penetration in Asia, standing at around two percent in developed markets and one percent in emerging markets, presents a barrier to sector expansion despite the region’s vast population of over four billion people. TechWireAsia caught up with Chirag Shah, the Managing Director of JAPAC Digital and Core Insurance at SAP Fioneer, to try and understand the growth potential of the industry in APAC.

He said: “The Asia Pacific insurance market is experiencing shifts driven by post-COVID-19 customer perceptions, particularly in healthcare. Rising awareness of the protection gap has led to increased demand for health and life insurance products, especially in emerging markets, where insurance penetration and density are lower compared to developed markets.

“Insurers must navigate challenges such as mobility, cybersecurity, and climate change while enhancing value creation within existing operations like claims and underwriting. Challenges include slowing growth, low penetration, and rising combined ratios, particularly in emerging markets.”

Insurance everywhere

Source: SAP Fioneer

“‘Insurance everywhere’ alludes to embedded insurance,” said Mr Djokic. “Delivering insurance at the point it’s needed, as part of a purchase process, circumventing the need for a consumer or business purchaser to undertake a separate set of steps to insure their car, home, electronic item, or holiday.” By making insurance products more accessible and convenient, insurers can reach a broader audience and meet the evolving needs of modern consumers. Accessibility also opens up new opportunities for insurers to partner with other industries and platforms, expanding their reach and market presence.

Mr Djokic added: “[It] has the potential to increase the level of insurance generally, which is good news not just for the industry but society as a whole, as it becomes more protected. But it also means that non-insurance companies can take market share from the traditional players, unless those players turn the situation to their advantage, and become the ones offering insurance solutions to new industries.”

Personalization with data and AI

Traditional insurance practices rely on limited data and broad assumptions, often leading to unfair assessments of risk based on general demographics. This has sparked frustration among consumers who feel penalized for careful behavior while subsidizing riskier individuals. However, emerging technologies like telematics and IoT devices are beginning to change this dynamic by allowing personalized assessments and rewards for behaviors like safe driving and healthy lifestyles.

“We have seen examples of health insurance companies monitoring exercise levels with fitness trackers and dropping premiums accordingly,” said Mr Djokic. “There is now more data accessible to the insurer to contribute to the risk assessment, be it social media or online behavioral data, credit scores or – in the case of embedded insurance – data held or gathered by the non-insurance company.

“For the first time, we’re witnessing a ‘win-win’ in the industry, where data helps the insurer reduce their risks and pass this on in the form of reduced premiums to the customer. As consumers become accustomed to this level of tailoring, it will be essential for insurers to offer personalized insurance to stay competitive.”

Increased data availability is enhanced by AI, particularly machine learning, enabling dynamic risk assessments and tailored policy generation. Predictive analysis and risk scenario modeling help insurers proactively cover emerging risks like climate change and technological advancements. Automated policy drafting and scenario simulation improve efficiency and ensure comprehensive coverage tailored to specific customer needs.

“AI can interpret data accurately and immediately to deliver real-time claims processing and payment while mitigating risks.” Said Mr Djokic. “It delivers the speed consumers and businesses now expect while protecting the insurer.”

Mr Shah added: “Insurers in Japan and Korea may leverage AI and data analytics uniquely to cater to their distinct demographics and technological landscapes. Japan’s aging population may drive insurers to develop AI solutions for personalized services and risk management tailored to older demographics. Korea’s advanced technological infrastructure may facilitate the adoption of AI-driven underwriting and pricing models to enhance customer experiences and operational efficiency.”

The future with SAP Fioneer

On the future of insurance in APAC, Mr Shah said: “Despite challenges, Asia remains an attractive insurance market, with emerging markets expected to see higher premium growth in the next two years driven by rising economic growth, increasing risk awareness post-pandemic, and digitalization of distribution channels.

“Digitally embedded insurance is expected to grow significantly by 2030, driven by increasing digital penetration and partnerships with digital ecosystems.”

Mr Djokic says that the key to taking advantage of the new opportunities in insurance is connectivity – the ability to connect a core insurance solution to, for example, a new data source or user interface. “The secret to that is open technology,” he said.

For example, SAP Fioneer’s Engagement Hub is a tool for insurers to connect in an evolving ecosystem. With bi-directional communication, the Hub links a core insurance system with diverse digital channels, letting insurers craft tailored insurance solutions and adapt to market demands. The Cloud for Insurance cloud-native platform boasts fully managed services, ecosystem integration, and an intuitive user experience, allowing users to scale, innovate, and adapt quickly.

For more information on how insurers can embrace open technology and navigate the transformative changes in the industry, download the ‘Insurance Everywhere All at Once’ whitepaper from SAP Fioneer today.

The post Insurance everywhere all at once: the digital transformation of the APAC insurance industry appeared first on Tech Wire Asia.

From Microsoft splitting Teams from its Office Suite to Google potentially acquiring HubSpot, a lot is happening between these two tech giants.

Both companies continuously explore avenues to enrich customer engagement and streamline operational processes. This quest for enhanced connectivity and understanding of the consumer landscape is where integrating with, or in Google’s case, acquiring Customer Relationship Management (CRM) platforms like the online marketing software company HubSpot becomes a strategic imperative.

Companies like Google can leverage sophisticated analytics, personalized marketing tools, and comprehensive project management solutions by considering the incorporation or acquisition of the platform. The potential acquisition by Alphabet, Google’s parent company, of HubSpot—valued at US$35 billion, as exclusively reported by Reuters—underscores the importance of CRM systems in achieving these goals.

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Alphabet’s eye on HubSpot

Alphabet’s contemplation of making a bid for HubSpot emerges as a noteworthy move in the tech industry, particularly under the intensified regulatory gaze of President Joe Biden’s administration in the United States. This acquisition, if pursued, would mark a significant venture for a leading tech entity into high-value deal-making amidst regulatory scrutiny.

This potential deal could represent Alphabet’s most substantial acquisition to date, offering an opportunity to strategically employ its substantial cash reserves, which stood at US$110.9 billion at the end of the last year.

Recent discussions have taken place between Alphabet and investment bankers from Morgan Stanley regarding a possible bid for HubSpot. These talks have focused on the bid’s valuation and the likelihood of obtaining approval from antitrust regulators. However, Alphabet has yet to extend an offer to HubSpot, and the outcome remains uncertain, as noted by sources who wished to remain anonymous while sharing insights on these private considerations.

In response to inquiries about these discussions, a representative from HubSpot stated the company does not engage in speculation or rumors, emphasizing their ongoing commitment to their business and clientele. Requests for comments from Alphabet and Morgan Stanley have not received immediate responses.

Following the revelation of these discussions, HubSpot’s stock experienced an 11% increase to US$693, whereas Alphabet’s shares saw a slight decrease of 1%, pricing at US$153.34.

Since its public debut in 2014, HubSpot has carved a niche in providing marketing software to small and medium-sized enterprises. Despite reporting a net loss of US$176.3 million in 2023 from revenues of US$2.2 billion, the company’s growth potential has captivated investors, as evidenced by a 50% surge in its stock price over the past year.

Google Alphabet eyes HubSpot acquisition (Source – X)

The future of CRM: What this means for Google and HubSpot

Currently, the discussions about Google potentially acquiring HubSpot are speculative, with no confirmation regarding whether this collaboration will materialize. Should such an acquisition proceed, it represents a significant shift for both companies.

Integrating HubSpot’s CRM capabilities could provide Google with deeper insights into customer behavior and preferences, potentially enhancing its user engagement through the use of HubSpot’s analytics and marketing tools.

The acquisition would enable Google to broaden its portfolio, especially within the CRM space—a sector where it has not yet established a strong foothold. This expansion could open up access to new markets and customer segments, particularly targeting small to medium-sized businesses that predominantly use HubSpot.

Furthermore, Google’s cloud computing services could see substantial benefits from incorporating HubSpot’s CRM solutions, potentially improving Google’s position relative to competitors like Microsoft Azure and Amazon Web Services.

Positioning the acquisition as a competitive enhancement in the CRM and broader software market could assist Google in navigating the complexities of regulatory approval, presenting the deal as a countermeasure to the market dominance of entities like Salesforce and Microsoft.

Such an acquisition could also quicken Google’s growth within the burgeoning CRM market, offering a pathway to expand its market share and influence significantly.

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Regulatory scrutiny and market dynamics

This acquisition speculation comes at a time when Google faces multiple antitrust allegations, including a significant lawsuit challenging its dominance in online search. Alphabet CEO Sundar Pichai is exploring new growth avenues following a shortfall in advertising sales, as Google and YouTube vie for ad budgets against platforms like Facebook, Instagram, TikTok, and Amazon.com.

The technology sector is witnessing a resurgence in deal activity, exemplified by Synopsys’ agreement to acquire Ansys for around US$35 billion and Hewlett Packard Enterprise’s acquisition of Juniper Networks for US$14 billion. In the first quarter alone, technology mergers and acquisitions have surged over 42% year-on-year to approximately US$154 billion, as reported by Dealogic, highlighting the sector’s dynamism.

Overall, Google acquiring HubSpot could mark a pivotal development, potentially creating new synergies between their technologies and market strategies. This development could offer both companies opportunities for growth and innovation within the dynamic landscape of CRM technology.

The post Google parent Alphabet eyes HubSpot: A potential acquisition shaping the future of CRM appeared first on Tech Wire Asia.

The PABC’s recent Vendor Expo was a great event where we were welcomed to look at many of the companies and research teams based at the Center and get to know some of the work done in this vital field. We were also given insights into the philosophy behind the organization and introduced to some of the personalities that together differentiate it from a pure business-focused outfit.

Capturing the spirit of innovation at the juncture of research and realization is key to ensuring that research and experimentation in biotechnology become sound practice.

In some fields, the ethos of incubator organizations can fixate on the bottom line, better to realize returns for investors. But in biotech, it’s long-term research that yields outcomes that are for the good of humankind. Those goals are not at odds with a commercial mindset; the difference at PABC is in the commitment necessary to create a collaborative research environment and the provision of secondary support over several years, if necessary.

The Center was created by the Hepatitis B Foundation (hepb.org) with the remit of creating a confluence of academic research and nascent practice in the life sciences. PABC is also extending its education and development activities with its new Academic Innovation Zone (AIZ) – we were able to explore some of the participants’ work in person at the Vendor Expo.

As well as acting as an incubator for nascent companies, the PABC is known in the state for its work with high-school students. The Center’s AP Chemistry program , which is a collaboration with the local Central Busks School District, offers exceptional young people extracurricular learning opportunities. Plus, it organizes summer break science education programs.

Source: PABC

The first round of awards for the $5 million AIZ program came in the Fall of 2024. Those selected are given free use of facilities and funding, plus mentoring and advice. They also become part of the PABC’s collaborative environment, where cutting-edge work in the biotechnology field takes place.

The Academic Innovation Zone employs two talent scouts, themselves skilled biotechnologists, who assess applicants and proactively research the most interesting academic programs for potential. This process is ongoing to ensure the enthusiasm and inquisitive nature of young companies continue to keep the spirit of the PABC alive.

Three companies from the first wave of the AIZ are already reaching clinical trial stages, using some of the funds granted to them to transition from startup status to viable businesses in the sector. However, although always welcome, funds are only part of the AIZ story.

Biotechnology and life science companies have naturally, over the course of several years, been emerging from and relocating to the pharma belt between North Jersey and Philadelphia. As you might expect, many ties and joint projects emanate from major local universities, with early-stage biotech companies emerging from post-graduate programs.

Lou Kassa, President, PABC

By concentrating on the transitional period between graduate academic research and commercial viability, the PABC provides a continuous didactic journey for talented individuals and groups from the area. It’s a journey that can begin in high school and culminate in a fully-fledged, successful biotechnology company.

While there is access to venture capital and funding opportunities available through PABC, what drives the Center’s ethos was formulated by the nature of its founding bodies: the non-profit Hepatitis B Foundation and research organization, the Baruch S. Blumberg Institute. There’s an appreciation that work in the life sciences requires a long-term commitment to research. Exploration and experimentation are considered integral parts of the Center’s activities, and the facilities and long-term support on offer reflect that.

The recent success stories from the Pennsylvania Biotechnology Center’s Academic Innovation Zone include Serna Bio, a company investigating small molecule drug use in RNA-targeted therapies at a time when big pharma is moving away from phenotypic screening-based drug discovery. RNA is a space 35 times larger than what’s being targeted by classical drug discovery, so Serna’s journey is just beginning.

The CEO of Greene Street Pharma, Frank C. Jones, took time out from his work to show us around the company’s lab and facilities. Frank also dedicates time to teaching at the Center, where his infectious enthusiasm and charm help advance the knowledge of the next generation of biotechnologists. Greene Street’s transdermal delivery systems (about to enter human clinical trials) match the effectiveness of oral treatment delivery and will remove gastrointestinal complications for many patients.

Evrys Bio’s remit is close to the PABC founding organization’s heart, The Hepatitis Foundation. It’s concentrating on sirtuin-targeted antivirals that could help cure both B and C variants, while Aprea Therapeutics’ work looks to repair damage to the DNA of healthy cells to prevent their death or mutation – with use cases in long-term cancer treatment, among many others.

If you’re at all interested in life sciences, biotech, and medtech in general, the Pennsylvania Biotechnology Center isn’t just another incubator. As a center for excellence, it seems to have captured the elusive drive of curiosity in academic research and created a space in which it’s nurtured in the right way.

The post Harnessing humans’ inquisitive nature for humanitarian Life Sciences appeared first on Tech Wire Asia.