Crypto-agility in the post-quantum age

The Tipping Point for Quantum Computing

We are at a tipping point for quantum computing, which is on the verge of becoming a reality. While its potential is tantalizing, it also represents an unprecedented threat to traditional data security infrastructure and the cryptographic algorithms that protect it. Post-quantum cryptography – algorithms designed to be secure against classical and quantum computer attacks – is the response.

Quantum computers exploit the principles of quantum mechanics to solve complex problems that classic computers cannot feasibly tackle. These machines use qubits, which can exist in multiple states simultaneously, as opposed to normal computers, which only use "zeros" and "ones". This creates an exponential scale, which is what gives them their computational power.

Of particular concern is their ability to crack widely used public key encryption algorithms such as RSA and ECC (elliptic curve cryptography). By the time a sufficiently powerful quantum computer becomes available, these encryption methods, which protect virtually all current digital communications, will be obsolete.

The date when cryptographically-relevant quantum computers will appear remains uncertain: estimates range from five to 10 years. However, the risk is immediate due to the "harvest now, decrypt later" attacks that are already taking place, especially for data with a longer lifetime.

If an organization retains sensitive data for the long term, such as financial information, personal data or even trade secrets, this represents a significant and growing risk. What is at stake is nothing less than the most valuable digital assets: intellectual property, private and sensitive data, authentication systems and secure communications.

The financial, operational and reputational damage from such exposures could be catastrophic, and unavoidable without proactive measures.

What is Post-Quantum Cryptography?

Post-quantum cryptography (PQC) refers to cryptographic algorithms designed to be secure against attacks by classical and quantum computers. These algorithms are based on mathematical problems that remain difficult to solve even for quantum computers.

In 2024, the National Institute of Standards and Technology (NIST) published its first set of standardized post-quantum cryptographic algorithms, including CRYSTALS-Kyber, CRYSTALS-Dilithium, SPHINCS+ and FALCON. In March 2025, NIST selected a new algorithm, Hamming Quasi-Cyclic (HQC), which will serve as a backup to the existing Module-Lattice-Based Key-Encapsulation Mechanism (ML-KEM) algorithms recommended by FIPS 203 to protect against quantum attacks.

HQC is based on error-correcting codes, a concept that has been fundamental to information security for decades. Unlike ML-KEM, which relies on structured networks, HQC's unique mathematical basis offers a robust alternative that can help combat the potential threats posed by future quantum computers. This shift in mathematical approaches is crucial for maintaining the integrity of encrypted data.

The Time for Change is Now

The time when currently encrypted data can be decrypted using quantum technology is closer than many people think. However, while most organizations are actively working on cyber resilience strategies, including their core IT infrastructure and components of the supply chain, the risk to quantum computing is not as widely considered.

Changing cryptography in a complex IT environment is not something that can be done overnight. It can take years, especially for large organizations with complex IT environments. Historical precedent shows that major cryptographic transitions typically take 5-10 years to complete.

Beginning the Transition

To begin a transition to post-quantum cryptography, a number of steps must be followed:

1. Cryptographic Inventory: Not all data is equally important, and not all data needs to be encrypted in the same way. It is therefore necessary to identify where cryptography should be used in the digital heritage. This should include the most sensitive data, applications, networks, identity systems, and third-party connections.

2. Risk Assessment: Given the cost of post-quantum cryptography, it makes sense to prioritize protecting the most sensitive data rather than trying to protect everything. Evaluate your data in terms of its sensitivity and longevity. Information that must remain confidential for more than five years should receive immediate attention. For less sensitive data, standard encryption methods will suffice in keeping it secure.

3. Crypto-Agility Implementation: Being crypto-agile – having the ability to switch between different cryptographic algorithms in response to new threats – will be essential in the post-quantum era. Develop frameworks that allow you to quickly replace cryptographic algorithms without the need for extensive system redesign. Crypto-agility also requires employee training, so invest time and resources to bring your employees on this journey with you.

4. Prioritized Migration: Start with your most sensitive systems and data, particularly those that protect intellectual property or personally identifiable information.

5. Supplier Engagement: Confirm that all suppliers in your ecosystem are aligned with emerging standards to ensure end-to-end protection and agility.

In Summary

By starting your post-quantum transition today, you can help protect your organization's most valuable data as we enter the quantum era. The alternative is to wait for quantum computers to break existing encryption – by then, it will be too late for data that has already been compromised. The future is quantum, and the time to future-proof your data is now.

Meta to launch new smart glasses with display next month

Meta's New Smart Glasses: A Glimpse into the Future of Wearable Tech

Meta, the tech giant behind Facebook and Instagram, is set to introduce its first consumer-ready smart glasses. This innovative product, known internally as Hypernova, is expected to revolutionize how users interact with digital content through augmented reality (AR) technology. The glasses are scheduled to be unveiled at the company’s annual Connect conference, an event dedicated to virtual reality, augmented reality, and the metaverse.

The Hypernova glasses will feature a small digital display embedded in the right lens. This display is designed to offer a 20-degree field of view, primarily for receiving notifications such as incoming text messages. While the display may seem modest, it represents a significant step forward in integrating AR into everyday life.

In addition to the glasses, users will receive a wristband that pairs with the device. This wristband utilizes sEMG sensor technology, which detects and interprets electrical signals from hand movements. This allows for intuitive control of the glasses through hand gestures, enhancing the user experience and making interactions more seamless.

The glasses are expected to retail for around $800 each. They will be sold under a partnership between Meta and EssilorLuxottica, a leading eyewear company. Although the specific brand name has not been confirmed, there have been reports suggesting that Prada-branded smart glasses could be part of this collaboration. Prada’s signature thick frames and arms might provide a suitable design for the Hypernova model, blending fashion with functionality.

According to a letter dated July 23 from the Customs and Border Patrol to a lawyer representing Meta, the Hypernova model will enable users to take and share photos and videos, make phone calls and video calls, send and receive messages, listen to audio playback, and interact with an AI assistant through various methods, including voice, display, and manual interactions.

This letter is part of routine communication when determining the country of origin for a consumer product. A source confirmed to CNBC that this letter was indeed in reference to Hypernova. The details provided in the letter highlight the potential capabilities of the device and its intended use cases.

As Meta continues to expand its presence in the AR and metaverse space, the release of Hypernova marks a pivotal moment for the company. With its focus on innovation and user experience, Meta is positioning itself as a leader in the future of wearable technology.

The development of Hypernova also underscores the growing importance of partnerships in the tech industry. By collaborating with EssilorLuxottica, Meta is leveraging the expertise of a well-established eyewear company to bring its vision to life. This strategic alliance could pave the way for other collaborations in the future, further expanding the possibilities of AR technology.

In addition to the Hypernova project, Meta has been actively involved in other initiatives, such as its partnership with Midjourney to license AI image and video models. These efforts reflect the company's commitment to pushing the boundaries of what is possible with technology.

As the tech landscape continues to evolve, Meta's latest venture into smart glasses is a clear indication of the company's ambition to shape the future of digital interaction. With its focus on innovation, user-centric design, and strategic partnerships, Meta is well-positioned to lead the next wave of technological advancements.

Upgraded Old Speakers to Bluetooth with Raspberry Pi Zero 2W

Exploring Wireless Connectivity for an Old Speaker System

Repurposing old devices can be a rewarding and creative endeavor. I have an older Sony speaker system that, while still functional, only accepts audio through an AUX cable. This limitation made it inconvenient to use with my other Tribit speaker, which offers wireless playback. To address this, I started exploring self-hosted services and Raspberry Pi operating systems, eventually finding a solution that transformed my Hi-Fi speaker into a modern wireless device.

The Challenge of Adding Bluetooth

The main challenge was integrating Bluetooth connectivity into the speaker, which lacked this feature. Instead of soldering or modifying the speaker itself, I opted for a more straightforward approach by using a Raspberry Pi Zero 2W. This affordable single-board computer has built-in Bluetooth capabilities, making it an ideal choice for the project.

To connect the speaker to the Pi, I used an AUX adapter with a built-in DAC. Since the Pi doesn't have an AUX port, I used a micro USB to USB-C adapter and connected an audio DAC that I previously used with my Samsung Galaxy S21 FE. This setup allowed me to avoid any physical modifications to the speaker.

Choosing the Right Operating System

After setting up the hardware, I needed an appropriate operating system. I chose moOde Audio OS, a dedicated audio streaming OS for Raspberry Pi. It’s based on Raspberry Pi OS Lite and includes a music streaming server, making it perfect for this project.

I used the Pi Imager tool to flash moOde Audio OS onto an SD card. During the setup, I configured Wi-Fi and SSH settings to enable a headless setup. Once the Pi booted up, I accessed the web interface by entering its IP address in a browser. However, I encountered an issue: there was no audio output initially.

Adjusting Audio Output Settings

Upon investigation, I realized that the OS defaults to HDMI as the audio output. To fix this, I navigated to the "Configure" section, selected "Audio," and then "Output device." By clicking the "Scan" button, I found the USB DAC and selected it as the audio source. After adjusting the volume levels, the audio played correctly through the speaker.

Next, I formatted a USB drive with the FAT32 file system and copied several tracks to it. The software automatically recognized the USB drive, allowing me to play audio without manual configuration. Rebooting the Pi confirmed that the USB drive was detected, and I could access the tracks from the library interface.

Enabling Bluetooth Connectivity

While the web interface provided a convenient way to manage local playback, my primary goal was to enable Bluetooth connectivity. I manually installed Bluetooth packages using the following commands:

sudo apt install bluetooth bluez blueman
sudo systemctl enable bluetooth
sudo systemctl start bluetooth

Then, I went back to the "Configure" section and enabled Bluetooth connectivity under the "Renderer" option. After restarting the controller, I paired my phone with the Pi via Bluetooth. A quick test with a YouTube video confirmed that the audio connection worked smoothly.

Final Results and Benefits

This project turned out to be one of the easiest Raspberry Pi projects I've completed. My Hi-Fi speaker now supports wireless playback without the need for an AUX cable. The moOde Audio OS not only solved the connectivity issue but also offered a user-friendly web interface for local playback.

Both the web interface and Bluetooth functionality work exceptionally well, with no noticeable degradation in audio quality. If you have an old speaker with AUX connectivity that lacks Bluetooth or Wi-Fi support, consider using a Raspberry Pi Zero 2W and moOde Audio OS to give it a modern upgrade. It's a cost-effective and efficient way to breathe new life into your existing audio equipment.

Windows 11 Brings Android App Resumption to PC – A Game-Changer

New Feature in Windows 11: Resume from Android

Microsoft is introducing a new feature in its Windows 11 operating system that allows users to seamlessly continue their activities across devices. This functionality, known as "Resume," is currently available in testing phases for specific applications, with Spotify being the first supported app.

The feature works by syncing your activity between your Android phone and your Windows 11 PC. For instance, if you're listening to a playlist or podcast on Spotify via your smartphone and then switch to your desktop, Windows 11 will notify you through a pop-up alert in the taskbar. This alert lets you know that you can resume your playback directly on your PC. Simply clicking the notification will open the Spotify app, resuming playback exactly where you left off on your mobile device.

To use this feature, you need to have the Spotify app installed on your Windows 11 PC and be logged into the same account used on your Android phone. If Spotify isn't installed, a prompt will appear offering to download it from the Microsoft Store. Once installed, logging into your account is necessary to ensure continuity of your playback session.

Additionally, the Link to Windows app must be running on your smartphone, and your mobile device needs to be connected and accessible from your Windows 11 PC. These requirements are outlined in Microsoft's blog post detailing the feature.

A Streamlined Experience Inspired by Apple’s Handoff

This new feature closely resembles Apple's Handoff capability, which allows users to transition tasks between iOS and macOS devices. Microsoft's version, called Cross Device Resume, offers a similar level of convenience and efficiency. Although the feature is still in the testing phase, it represents a significant step forward in cross-platform integration.

The concept was previously revealed in an accidental preview during a pre-recorded Build session earlier this year. The video showing the feature was quickly edited to remove the demonstration, but the functionality has since been confirmed in current test builds. The process remains largely the same, with Spotify serving as the primary example.

Microsoft is expected to expand support for this feature to other apps in the future. While Spotify is the initial partner, there are indications that WhatsApp may also receive similar capabilities. This expansion could encourage more developers to adopt the feature, especially those who have apps available on both Windows 11 and Android platforms.

Encouraging Microsoft Store Adoption

The Resume feature also serves as a promotional tool for the Microsoft Store. By prompting users to install apps directly from the store, Microsoft aims to boost traffic and engagement with its platform. This aligns with recent efforts to improve the overall user experience and increase the visibility of apps available through the store.

Despite the benefits of this feature, some questions remain about why it took Microsoft so long to implement such a straightforward and useful functionality. Many users might find it surprising that a company with such a strong presence in the tech industry hasn't introduced this capability sooner.

Future Prospects and User Expectations

As more developers join the initiative, the potential for seamless cross-device experiences grows. Microsoft is likely to reach out to major app developers to encourage them to integrate this feature into their offerings. The success of this feature will depend on how widely it is adopted and how smoothly it integrates with existing workflows.

For now, the feature is available only in test builds, but it's clear that Microsoft sees value in expanding this functionality to a broader range of applications. As the feature matures, it could become a key selling point for Windows 11, especially for users who rely heavily on multiple devices throughout their day.

Do AI Firms Prioritize U.S. Interests?

The American AI Narrative and the Influence of Tech Giants

In early May, Sam Altman traveled to Washington to share a story about America. Appearing before a Senate committee, Altman described how he grew up during the internet's rise, spending late nights in his family’s attic learning to code on products invented in the United States—personal computers, silicon chips, and software. This early exposure to the “spirit of American innovation,” he told the senators, set him on a path to found OpenAI, launch ChatGPT, and spark the AI boom. “I think America is just an incredible and special thing,” he said, “and it will not only be the place where the AI revolution happens but all the revolutions after.”

Altman’s written testimony, submitted to the Senate, added an important note that he did not mention aloud. “This future can be almost unimaginably bright,” OpenAI’s CEO wrote, but only if “an American-led version of AI, built on democratic values like freedom and transparency, prevails over an authoritarian one.” Silicon Valley’s tech giants have reframed the AI boom as more than just scientific and economic advancement—it has become a clash of civilizations. They are focused on competition with China, believing that Chinese AI, if it surpasses its American counterpart, could extend a repressive surveillance state globally.

Despite this rhetoric, it is unclear whether AI companies are actively upholding American freedoms. Instead, they seem more interested in what America can do for them.

The Rise of AI and the Fear of Authoritarianism

China has long been a concern for tech leaders. Eric Schmidt, Sheryl Sandberg, and others have warned about the need to outpace China in various technologies—including AI, quantum computing, and 5G. These concerns have grown louder since the launch of ChatGPT. Dario Amodei, CEO of OpenAI’s rival Anthropic, wrote last fall that “AI-powered authoritarianism seems too terrible to contemplate.” Democracies, he continued, must unite to stay ahead.

Silicon Valley has always had certain American ideals embedded in its culture: individualism, the belief that you can build anything you dream of, and the promise that hard work will pay off. However, the previous tech revolution—the arrival of the social web and smartphones—was framed as a path toward global connection and democratization. Now, the arrival of artificial intelligence has taken on a distinctly “America First” tone.

There are two main ways to understand what is happening here. One view suggests that the world’s most powerful tech companies are aligning with the current ruling political class in America, framing their missions in ways they believe will favor MAGA Republicans, particularly Donald Trump, to avoid regulation and enrich themselves. Another perspective is that these companies are producing dramatic innovation that, in earlier eras, would have been under the purview of the U.S. government, and they recognize the responsibility they have to the world’s citizens. The truth lies somewhere in between.

The AI War and the Role of the Trump Administration

Since Trump’s victory, Altman, Amodei, and their peers have become more forceful in their warnings. Generative AI, they argue, could supercharge China’s economy, propaganda apparatus, espionage capabilities, and coercive tactics—and even make its military more powerful than our own. Last month, Anthropic published a report on how to “Build AI in America” and “compete with China.” Alexandr Wang, former CEO of Scale AI and now chief AI officer at Meta, has told the Trump administration that the U.S. and China are in an “AI war.” Earlier this summer, executives from OpenAI, Meta, and Palantir joined a new Army detachment, the Executive Innovation Corps, to serve as part-time advisers. The group aims to “marry the nation’s most innovative private companies with our most important military missions.”

In the U.S., democracy and AI have become conjoined in a catchphrase. The highest echelon of American AI firms—including OpenAI, Anthropic, Google, Microsoft, Scale, Meta, and Palantir—all made recommendations to the Trump administration as it developed its “AI Action Plan,” appealing to variations on “democratic AI,” “American” ideals, and “Western” values. Similar invocations of democracy and American leadership appear in the lobbying documents, policy proposals, interviews, and congressional testimonies of these companies and their executives.

When the AI Action Plan was unveiled last month, Trump gave the industry a green light to develop new products with limited oversight. He promised few roadblocks would stand between them and the buildout of economically and environmentally costly infrastructure. “Our children will not live in a planet controlled by the algorithms” of our “adversaries,” President Trump declared when he announced the plan.

The Paradox of Democratic AI

But “democratic AI,” under a president who has already tried to overturn an election, may prove to be a misnomer. Tech firms have long demonstrated a willingness to act in their own interests, not the greater good. Now, the AI boom offers a way to conscript the American project to advance their techno-utopian visions, not the other way around.

OpenAI recently launched OpenAI for Countries, its version of the Marshall Plan: a project to “spread democratic AI” to other nations in the form of ChatGPT. Microsoft, Amazon, Nvidia, and other prominent AI firms also describe spreading their products and services around the globe as a sort of diplomacy on behalf of the U.S. Meanwhile, OpenAI and its rivals have become more aggressive in their efforts to keep individual users walled into their chatbots, where the companies can accrue valuable data and charge subscription fees.

The Need for Government Approval and the Risks of Dependency

The tech industry’s new ambitions—using AI to reshape not just work, school, and social life but perhaps even governance itself—do have a major vulnerability: the AI patriots desperately need the president’s approval. Chatbots rely on enormous data centers and energy infrastructure that depend on the government to permit and expedite major construction projects. AI products, which are still fallible and have yet to show a clear path to profits, are in need of every bit of grandiose marketing—and all the potentially lucrative government and military contracts—available.

Zuckerberg, who is also aggressively pursuing AI development, said in a Meta earnings call, “We now have a U.S. administration that is proud of our leading companies, prioritizes American technology winning, and that will defend our values and interests abroad.” Altman, once a vocal opponent of Trump, has written that he now believes that Trump “will be incredible for the country in many ways!”

This dependence has led to a kind of cognitive dissonance. In this early stage of the AI boom, Silicon Valley, for all its impunity, has chosen not to voice robust ideas about democracy that differ substantively from the whims of a mercurial White House. As millions of everyday citizens, current and former government officials, lawyers and academics, and dissidents from dictatorships around the world have warned that the Trump administration is eroding American democracy, AI companies have remained mostly supportive or silent despite their own bombastic rhetoric about protecting democracy.

Conclusion

The AI industry’s belief that its products can drastically improve the world may be genuine, but the rationale underlying its insistence is shallow at best. AI’s titans seem far less concerned with America as a democratic project and more interested in it as a brand, financier, and regulatory backer. Perhaps AI executives are also now AI patriots, but that is a secondary occupation; faith in technological acceleration, and maintaining their own power, still transcends a commitment to democracy.

Pioneering AI Governance and Federated Learning in Banking: Bharath Somu's Future Vision

Redefining Financial Systems with AI and Federated Learning

As the global banking sector undergoes a rapid digital transformation, leaders in artificial intelligence (AI) and machine learning are reshaping the very foundation of financial systems. Among them is Bharath Somu, a visionary in AI-driven infrastructure optimization. With a deep understanding of machine intelligence, cybersecurity, and regulatory compliance, Somu has introduced a groundbreaking framework for modernizing banking IT through the integration of federated learning and AI governance.

In his recent paper titled “Optimizing Infrastructure Services in Banking IT with Federated Learning and AI Governance,” Somu presents a strategic approach to leveraging decentralized AI systems. His work focuses on enhancing data privacy, improving system performance, and ensuring alignment with strict regulatory requirements. By combining federated learning models with comprehensive governance structures, his research offers a forward-thinking solution to many of the complex challenges faced by today’s financial institutions.

Reshaping the Foundation of Financial Infrastructure

Banking systems have traditionally relied on rigid, centralized IT architectures that struggle to adapt to emerging data privacy laws, increasing cybersecurity threats, and the evolving demands of digital customers. Somu’s framework reimagines this status quo by proposing decentralized, collaborative machine learning approaches that protect sensitive data while enhancing operational intelligence.

Federated learning, a method that trains AI models across multiple institutions without transferring raw data, is central to his proposition. “Banks must embrace decentralized intelligence to unlock the power of their collective data while preserving the sanctity of customer privacy,” Somu explains. This approach allows AI models to learn from diverse, siloed datasets across financial institutions, boosting model accuracy while ensuring compliance with privacy regulations such as GDPR and CCPA.

Somu’s research highlights several use cases where federated learning has shown significant advantages. These include fraud detection, credit risk modeling, and customer segmentation. For example, banks can detect suspicious behaviors across regions in real time without pooling customer data into a centralized repository. This not only improves security but also makes collaborative analytics a reality.

Governance as a Strategic Enabler

While federated learning addresses data decentralization, it also introduces complexity, particularly in terms of accountability, explainability, and ethical AI practices. That’s where Somu’s AI governance framework comes into play. By defining transparent model evaluation protocols, establishing audit trails, and embedding fairness into algorithm design, his approach ensures that these intelligent systems operate within well-defined ethical boundaries.

“AI in finance isn’t just about faster decisions—it’s about responsible intelligence,” says Somu. His governance framework introduces role-based accountability within AI development cycles, requiring collaboration between stakeholders from compliance, engineering, and risk management. Regular model audits, interpretability checks, and fairness assessments form the foundation of this governance layer, aligning with global regulatory expectations and stakeholder trust.

This dual-pronged architecture—federated learning underpinned by governance—enables banks to deploy high-performance models without compromising on ethical standards or compliance.

Real-World Impact and Enterprise Implementation

Somu’s ideas are not theoretical; they are being implemented in real-world scenarios. At American Express, he has led the development of intelligent infrastructure solutions that are already transforming how global financial services operate. His work on synthetic identity fraud detection, self-healing DevOps pipelines, and real-time anomaly detection for large-scale clients like Hilton Hotels demonstrates the practical application of his concepts.

By leveraging cloud-native orchestration and agent-based systems, his deployments integrate privacy-first AI into production environments. The result is increased resilience, reduced latency, and measurable improvements in fraud mitigation and customer experience.

Industry Recognition and Thought Leadership

From 2020 to 2025, Bharath Somu has been a prominent voice in fintech research, contributing extensively to academic and industry publications. His focus spans zero-trust infrastructure, cross-domain orchestration, and Banking-as-a-Service (BaaS) transformation. In every initiative, Somu emphasizes the seamless integration of AI into operational strategy, ensuring scalability without sacrificing trust.

His paper in the International Journal of Advanced Research in Computer and Communication Engineering (Vol. 12, Issue 12, 2023) adds to this growing body of work, offering a holistic view of how banks can future-proof their infrastructure.

Challenges Ahead: Complexity, Transparency, and Compliance

Despite the optimism surrounding federated learning, Somu’s research acknowledges the challenges involved. Implementing federated learning across diverse banking systems presents technical hurdles, including model convergence issues and data heterogeneity. Ensuring model explainability in federated contexts remains a persistent challenge, especially when outputs affect high-stakes decisions like loan approvals or fraud flags.

Somu advocates for continuous monitoring systems and lifecycle model management as essential components of deployment strategy. He emphasizes the need for interdisciplinary training and operational feedback loops to sustain the accuracy and relevance of AI applications over time.

The Road Forward: Collaborative, Ethical, and Scalable AI

Bharath Somu envisions a future where financial institutions move beyond competitive silos and embrace a cooperative AI landscape governed by transparency, interoperability, and shared accountability. His blueprint fosters not just technological progress, but a new era of trust between banks, regulators, and customers.

“In the evolving financial ecosystem, innovation and integrity must go hand in hand,” Somu notes. “By aligning federated learning with ethical governance, we can build infrastructures that are not only intelligent—but also just, resilient, and inclusive.”

As banks worldwide confront unprecedented complexity, Bharath Somu’s insights serve as a timely guide. His contributions illustrate that with the right blend of innovation and governance, financial institutions can confidently navigate a future defined by data, driven by AI, and sustained by trust.

LG CNS Launches AI Assistant for Hiring, Interviews, and Budgets

Introducing AgenticWorks and AXThink: LG CNS Unveils New AI Innovations

LG CNS, a leading technology company, recently introduced two groundbreaking AI solutions at its headquarters in Magok-dong, western Seoul. These innovations, AgenticWorks and AXThink, are designed to revolutionize how enterprises utilize artificial intelligence, offering more advanced capabilities than traditional digital assistants.

AgenticWorks is an agentic AI platform that enables companies to think and act like humans. Unlike conventional AI systems that simply respond to commands, AgenticWorks can set goals and perform tasks autonomously. This new system is aimed at enhancing productivity by integrating AI agents with enterprise infrastructure seamlessly.

Key Features of AgenticWorks

The platform consists of six essential components:

• Builder: Allows for coding-based customization.
• Studio: Offers no-code development options.
• Knowledge Lake: Facilitates data preprocessing.
• Hub: Integrates AI agents with enterprise systems.
• Refiner: Enhances industry-specific AI models.
• Router: Selects the optimal model for specific tasks.

These components enable companies to tailor their AI solutions according to unique business needs. For instance, in human resources, AgenticWorks can analyze job applications, cross-check aptitude test results, recommend suitable candidates, and generate tailored interview questions. According to LG CNS, this process has increased productivity by 26 percent.

AI for All Employees

In addition to AgenticWorks, LG CNS unveiled AXThink, a service that applies AI to seven common office tasks for all employees. AXThink includes features such as a “Daily Briefing,” which summarizes important emails and schedules with voice guidance, automatic email summarization, real-time meeting translation, and digital approvals and signatures.

According to LG CNS, when Group affiliate LG Display adopted AXThink, workplace productivity improved by about 10 percent per day on average. Additionally, the company saved more than 10 billion won ($7.2 million) annually compared to outsourcing similar services.

The Growing AI Market

The global AI transformation market is expanding rapidly. Market research firm Statista projects the sector to grow from 355 trillion won this year to 970 trillion won by 2029. In Korea, Samsung SDS is securing market share with its Brity Copilot collaboration solution and FabricX AI platform, which have attracted more than 150,000 users.

Future of AI in Enterprises

LG CNS CEO Hyun Shin-gyoon emphasized the importance of connecting AI agents and enterprise infrastructure organically. He stated that through this approach, companies can dramatically enhance productivity. The introduction of AgenticWorks and AXThink marks a significant step forward in the integration of AI into everyday business operations.

As enterprises continue to seek ways to improve efficiency and reduce costs, the adoption of advanced AI solutions like AgenticWorks and AXThink is becoming increasingly essential. These innovations not only streamline processes but also provide valuable insights that can drive better decision-making.

With the rapid growth of the AI market, it's clear that companies that embrace these technologies will be well-positioned to succeed in the evolving business landscape. LG CNS’s latest offerings demonstrate a commitment to innovation and a vision for the future of AI in the enterprise world.