#FactCheck- Pakistan Video Falsely Shared as Attack on Army in West Bengal

Introduction

Significantly, in March 2023, the Prevention of Money Laundering Act, 2002's regulations placed Virtual Digital Asset Service Providers functioning located under the purview of the Anti Money Laundering/Counter Financing of Terrorism (AML-CFT) scheme. An important step toward controlling VDA SP operations and guaranteeing adherence to Anti-Money Laundering and Combating the Financing of Terrorism (AML-CFT) regulations.

The significance of AML-CFT procedures

The AML-CFT framework's incorporation of Virtual Digital Asset Service Providers (VDA SPs) is essential for protecting the banking industry from illegal activities including the laundering of funds and counter-financing of terrorist attacks. These regulations become more crucial as the market for digital assets develops and becomes more well-known.

The practice of money laundering is hiding the source of the sum received illegally, thus it's critical to have strict policies in place to track down and stop these kinds of operations. Furthermore, funding for terrorism is a serious danger to international safety, hence stopping the flow of money to terrorist companies is a top concern for global officials.

The goal of policymakers' move to include VDA SPs in the AML-CFT architecture is to set up control and surveillance procedures that will guarantee these organisations' open and honest operations. This involves tracking transactions, flagging questionable activity, and conducting extensive customer investigations. Incorporating such procedures not only reduces the potential for financial crimes but also builds confidence and trust in the electronic asset market.

It is important to see the significance of AML-CFT procedures and the changes in the legal framework to reflect the evolving characteristics of digital currencies. These procedures are essential to preserving the reliability and safety of the wider banking system.

Notifications of Compliance Show Cause

Under Section 13 of the PMLA Act 2002, FIU IND sent adherence Show Cause Notices to nine offshore Virtual Digital Asset Service Providers (VDA SPs) as part of its dedication to upholding compliance with regulations. This affirmative step requires organisations to be scrutinised and attempted to bring them under inspection.

Governmental Response

The Director of FIU IND has addressed the Secretary of the Ministry of Electronics and Information Technology to take further measures due to the disregard of offshore firms. According to the notification, URLs connected to these organisations that operate in India in violation of the PML Act's requirements must be blocked. 

Mandatory Registration for VDA SPs

Virtual Digital Asset Service Providers (both onshore and offshore) who perform a range of operations, including the trading of digital goods for monetary currencies, the distribution of digital currency, and the management or preservation of electronic assets, are now obliged to register with FIU.

Range of Statutory Responsibilities

In accordance with the PML Act, VDA SPs are subject to several requirements, including documentation, disclosure, and other duties. One of their responsibilities is to register with the FIU IND. The primary focus is on guaranteeing that VDA SPs comply with AML-CFT protocols, hence enhancing the general reliability of the banking industry.

Difficulties with Offshore Compliance

There are many obstacles in guaranteeing that offshore organisations comply with Anti Money Laundering/Counter Financing of Terrorism (AML-CFT), chief amongst them being their unwillingness to undergo registration. Some overseas Virtual Digital Asset Service Providers (VDA SPs) have been reluctant to comply with the existing rules and regulations, even though they cater to a significant number of Indian users. There are several reasons for this hesitation, such as worries about heightened monitoring, the expense of compliance, and the apparent complexity of governmental processes. Regulatory organisations have taken steps to close the discrepancy between offshore businesses' real activities and the regulations they must follow. In addition to maintaining the trustworthiness of the economic system, resolving the issues with offshore adherence is essential for promoting confidence and openness in the market for electronic assets.

Conclusion

FIU IND has demonstrated its dedication to creating an effective regulatory framework for Virtual Digital Asset Service Providers through its recent measures. India hopes to fortify its countermeasures against money laundering and safeguard the financial well-being of its users by expanding the AML-CFT legislation to offshore firms. The continuous efforts to restrict the URLs of non-compliant companies show a proactive approach to stopping illicit activity and fostering a safe and law-abiding virtual asset ecosystem. The safety and soundness of the banking sector will be crucially maintained by laws and regulations as the digital world develops.

References

• https://pib.gov.in/PressReleasePage.aspx?PRID=1991372
• https://www.thehindubusinessline.com/books/reviews/business-economy/fiu-ind-issues-compliance-showcause-notices-to-nine-offshore-vda-sps/article67684613.ece
• https://business.outlookindia.com/news/fiu-issues-notice-to-9-offshore-crypto-platforms-writes-to-meity-for-blocking-of-urls

Introduction

‍

In the hyperconnected world, cyber incidents can no longer be treated as sporadic disruptions; such incidents have become an everyday occurrence. The attack landscape today is very consequential and shows significant multiplication in its frequency, with ransomware attacks incapacitating a health system, phishing attacks hitting a financial institution, or state-sponsored attacks on critical infrastructures. Towards counteracting such threats, traditional ways alone are not enough, they gravely rely on manual research and human intellect. Attackers exercise speed, scale, and stealth, and defenders are always four steps behind. With such a widening gap, it is deemed necessary to facilitate incident response and crisis management with the intervention of automation and artificial intelligence (AI) for faster detection, context-driven decision-making, and collaborative response beyond human capabilities.

‍

Incident Response and Crisis Management

‍

Incident response is the structured way in which organisations deal with responding to detecting, segregating, and recovering from security incidents. Crisis management takes this even further, dealing not only with the technical fallout of a breach but also its business, reputation, and regulatory implications. Echelon used to depend on manual teams of people sorting through logs, cross-correlating alarms, and generating responses, a paradigm effective for small numbers but quickly inadequate in today's threat climate. Today's opponents attack at machine speed, employing automation to launch attacks. Under such circumstances, responding with slow, manual methods means delay and draconian consequences. The AI and automation introduction is a paradigm change that allows organisations to equate the pace and precision with which attackers initiate attacks in responding to incidents.

‍

How Automation Reinvents Response

‍

Cybercrime automation liberates cybercrime analysts from boring and repetitive tasks that consume time. An analyst manually detects potential threats from a list of hundreds each day, while automated systems sift through noise and focus only on genuine threats. Malware can automatically cause infected computers to be disconnected from the network to avoid spreading or may automatically have its suspicious account permissions removed without human intervention. The security orchestration systems move further by introducing playbooks, predefined steps describing how incidents of a certain type (e.g., phishing attempts or malware infections) should be handled. This ensures fast containment while ensuring consistency and minimising human error amid the urgency of dealing with thousands of alerts.

Automation takes care of threat detection, prioritisation, and containment, allowing human analysts to refocus on more complex decision-making. Instead of drowning in the sea of trivial alerts, security teams can now devote their efforts to more strategic areas: threat hunting and longer-term resilience. Automation is a strong tool of defence, cutting response times down from hours to minutes.

‍

The Intelligence Layer: AI in Action

‍

If automation provides speed, then AI is what allows the brain to be intelligent and flexible. Working with old and fixed-rule systems, AI-enabled solutions learn from experiences, adapt to changes in threats, and discover hidden patterns of which human analysts themselves would be unaware. For instance, machine learning algorithms identify normal behaviour on a corporate network and raise alerts on any anomalies that could indicate an insider attack or an advanced persistent threat. Similarly, AI systems sift through global threat intelligence to predict likely attack vectors so organisations can have their vulnerabilities fixed before they are exploited.

AI also boosts forensic analysis. Instead of searching forever for clues, analysts let AI-driven systems trace back to the origin of an event, identify vulnerabilities exploited by attackers, and flag systems that are still under attack. During a crisis, AI is a decision support that predicts outcomes of different scenarios and recommends the best response. In response to a ransomware attack, for example, based on context, AI might advise separating a single network segment or restoring from backup or alerting law enforcement. 

‍

Real-World Applications and Case Studies

‍

Already, this mitigation has been provided in the form of real-world applications of automation and AI. Consider, for example, IBM Watson for Cybersecurity, which has been applied in analysing unstructured threat intelligence and providing analysts with actionable results in minutes, rather than days. Like this, systems driven by AI in DARPA's Cyber Grand Challenge demonstrated the ability to automatically identify an instant vulnerability, patch it, and reveal the potential of a self-healing system. AI-powered fraud detection systems stop suspicious transactions in the middle of their execution and work all night to prevent losses. What is common in all these examples is that automation and AI lessen human effort, increase accuracy, and in the event of a cyberattack, buy precious time.

‍

Challenges and Limitations

‍

While promising, the technology is still not fully mature. The quality of an AI system is highly dependent on the training data provided; poor training can generate false positives that drown teams or worse false negatives that allow attackers to proceed unabated. Attackers have also started targeting AI itself by poisoning datasets or designing malware that does not get detected. Aside from risks that are more technical, the operational and financial costs involved in implementing advanced AI-based systems present expensive threats to any company. Organisations will have to make expenditures not only on technology but also for the training of staff to best utilise these tools. There are some ethical and privacy issues to consider as well because systems may be processing sensitive personal data, so global data protection laws such as the GDPR or India's DPDP Act could come into conflict.

‍

Creating a Human-AI Collaboration

‍

The future is not going to be one of substitution by machines but of creating human-AI synergy. Automation can do the drudgery, AI can provide smarts, and human professionals can use judgment, imagination, and ethical decisions. One would want to build AI-fuelled Security Operations Centres where technology and human experts work in tandem. Continuous training must be provided to AI models to reduce false alarms and make them most resistant against adversarial attacks. Regular conduct of crisis drills that combine AI tools and human teams can ensure preparedness for real-time events. Likewise, it is worth integrating ethical AI guidelines into security frameworks to ensure a stronger defence while respecting privacy and regulatory compliance.

‍

Conclusion

‍

Cyber-attacks are an eventuality in this modern time, but the actual impact need not be so harsh. The organisations can maintain the programmatic method of integrating automation and AI into incident response and crisis management so that the response against the very threat can be shifted from reactive firefighting to proactive resilience. Automation gives speed and efficiency while AI gives intelligence and foresight, hence putting the defenders on par and possibly exceeding the speed and sophistication of the attackers. But an utmost system without human inquisitiveness, ethical reasoning, and strategic foresight would remain imperfect. The best defence is in that human-machine relationship symbiotic system wherein automation and AI take care of how fast and how many cyber threats come in, whereas human intellect ensures that every response is aligned with larger organizational goals. This synergy is where cybersecurity resiliency will reside in the future-the defenders won't just be reacting to emergencies but will rather be driving the way.

‍

References

‍

• https://www.sisainfosec.com/blogs/incident-response-automation/
• https://stratpilot.ai/role-of-ai-in-crisis-management-and-its-critical-importance/
• https://www.juvare.com/integrating-artificial-intelligence-into-crisis-management/
• https://www.motadata.com/blog/role-of-automation-in-incident-management/

‍

The world of Artificial Intelligence is entering a new phase with the rise of Agentic AI, often described as the third wave of AI evolution. Unlike earlier systems that relied on static models (that learn from the information that is fed) and reactive outputs, Agentic AI introduces intelligent agents that can make decisions, take initiative, and act autonomously in real time. These systems are designed to require minimal human oversight while actively collaborating and learning continuously. Such capabilities indicate an incoming shift, especially in the ways in which Indian businesses can function. For better understanding, Agentic AI is capable of streamlining operations, personalising services, and driving innovations at scale.

India and Agentic AI

Building as we go, India is making continuous strides in the AI revolution- deliberating on government frameworks, and simultaneously adapting. At Microsoft's Pinnacle 2025 summit in Hyderabad, India's pivotal role in shaping the future of Agentic AI was brought to the spotlight. With over 17 million developers on GitHub and ambitions to become the world's largest developer community by 2028, India's tech talent is gearing up to lead global AI innovations. Microsoft's Azure AI Foundry, also highlighted the country's growing influence in the AI landscape.

Indian companies are actively integrating Agentic AI into their operations to enhance efficiency and customer experience. Zomato is leveraging AI agents to optimise delivery logistics, ensuring timely and efficient service. Infosys has developed AI-driven copilots to assist developers in code generation, reducing development time, requiring fewer people to work on a particular project, and improving software quality. 

As per a report by Deloitte, the Indian AI market is projected to grow potentially $20 billion by 2028. However, this is accompanied by significant challenges. 92% of Indian executives identify security concerns as the primary obstacle to responsible AI usage. Additionally, regulatory uncertainties and privacy risks associated with sensitive data were also highlighted.

Challenges in Adoption

Despite the enthusiasm, several barriers hinder the widespread adoption of Agentic AI in India:

• Skills Gap: While the AI workforce is expected to grow to 1.25 million by 2027, the current growth rate of 13% is considered to be insufficient with respect to the demands of the market. 
• Data Infrastructure: Effective AI systems require robust, structured, and accessible datasets. Many organisations lack the necessary data maturity, leading to flawed AI outputs and decision-making failures.
• Trust and Governance: Building trust in AI systems is crucial. Concerns over data privacy, ethical usage, and regulatory compliance require robust governance frameworks to ensure the adoption of AI in a responsible manner.
• Looming fear of job loss: As AI continues to take up more sophisticated roles, a general feeling of hesitancy with respect to the loss of employment/human labour might come in the way of adopting such measures.
• Outsourcing: Currently, most companies prefer outsourcing or buying AI solutions rather than building them in-house. This gives rise to the issue of adapting to evolving needs.

The Road Ahead

‍

To fully realise the potential of Agentic AI, India must address the following challenges :

• Training the Workforce: Initiatives and workshops tailored for employees that provide AI training can prove to be helpful. Some relevant examples are Microsoft’s commitment to provide AI training to 2 million individuals by 2025 and Infosys's in-house AI training programs.
• Data Readiness: Investing in modern data infrastructure and promoting data literacy are essential to improve data quality and accessibility.
• Establishing Governance Frameworks: Developing clear regulatory guidelines and ethical standards will foster trust and facilitate responsible AI adoption. Like the IndiaAI mission, efforts regarding evolving technology and keeping up with it are imperative.

Agentic AI holds unrealised potential to transform India's business landscape when coupled with innovation and a focus on quality that enhances global competitiveness. India is at a position where by proactively addressing the existing challenges, this potential can be realised and set the foundation for a new technological revolution (along with in-house development), solidifying its position as a global AI leader.

References

• https://economictimes.indiatimes.com/tech/artificial-intelligence/india-facing-shortage-of-agentic-ai-professionals-amid-surge-in-demand/articleshow/120651512.cms?from=mdr
• https://economictimes.indiatimes.com/tech/artificial-intelligence/india-a-global-leader-in-agentic-ai-adoption-deloitte-report/articleshow/119906474.cms?from=mdr
• https://inc42.com/features/from-zomato-to-infosys-why-indias-biggest-companies-are-betting-on-agentic-ai/
• https://www.hindustantimes.com/india-news/agentic-ai-next-big-leap-in-workplace-automation-101742548406693.html
• https://www.deloitte.com/in/en/about/press-room/india-rides-the-agentic-ai-wave.html
• https://www.businesstoday.in/tech-today/news/story/ais-next-chapter-starts-in-india-microsoft-champions-agentic-ai-at-pinnacle-2025-474286-2025-05-01
• https://www.hindustantimes.com/opinion/calm-before-ai-storm-a-moment-to-prepare-101746110985736.html‍
• https://www.financialexpress.com/life/technology/why-agentic-ai-is-the-next-big-thing/3828357/