Artificial Intelligence is transforming cybersecurity faster than any technology in history. What was once a battle between human attackers and human defenders is now a high-speed contest between AI-driven cyber threats and AI-powered security systems. As enterprises accelerate digital transformation, the security landscape is becoming more complex, more automated, and significantly more dangerous.

In 2025, AI is helping hackers launch faster, more targeted, and more scalable attacks — but it is also giving defenders unprecedented detection, prediction, and response capabilities. This article explores how AI is used on both sides, the top emerging AI-powered cyber threats, and why “Secure AI” is becoming the No.1 priority for CISOs worldwide.

1. How AI Is Helping Hackers — And How It’s Helping Defenders

How Hackers Are Using AI

Cybercriminals have embraced AI as a weapon. With advanced generative models and automation frameworks, they can now:

• Launch highly convincing phishing attacks using AI-generated emails, voice messages, and cloned identities
• Automate vulnerability scanning across thousands of systems simultaneously
• Create malware that adapts in real time, rewriting its code to evade antivirus tools
• Exploit AI-based systems themselves, such as poisoning machine learning models with manipulated data
• Carry out social engineering at scale, impersonating executives or employees with flawless accuracy

AI has dramatically lowered the skill barrier for cybercrime. Even inexperienced attackers can deploy sophisticated attacks using AI-powered hacking tools.

How Defenders Are Using AI

On the other side, cybersecurity teams rely on AI to strengthen defense mechanisms:

• AI-powered threat detection identifies anomalies that humans would miss
• Predictive analytics helps anticipate attacks before they occur
• Automated incident response isolates infected machines or blocks malicious traffic instantly
• Behavioral biometrics can differentiate between genuine and fake user actions
• Intelligent SOC operations reduce alert fatigue and increase threat hunting speed

AI gives defenders speed, visibility, and automation — three things desperately needed in a world where attacks are relentless and instantaneous.

2. Top 10 AI-Powered Cyber Threats Enterprises Must Prepare for in 2025

Cyber threats in 2025 are stealthier, automated, and AI-driven. Here are the top 10 risks enterprises must prepare for:

1. AI-Generated Phishing Attacks

Hyper-realistic emails, deepfake voice calls, and chat messages crafted by AI can fool even experienced employees.

2. Deepfake CEO Fraud

Attackers can clone a CEO’s voice or face to instruct employees to transfer money, reveal credentials, or approve transactions.

3. AI-Enhanced Ransomware

Malware that spreads automatically, selects high-value targets, and negotiates ransom using AI chatbots.

4. Automated Vulnerability Exploitation

AI tools that scan the internet for open ports, outdated systems, and misconfigurations — then attack instantly.

5. Credential Stuffing at Machine Speed

Bots using AI to test millions of username-password combinations, adjust behavior, and bypass CAPTCHAs.

6. Data Poisoning Attacks

Hackers manipulate training data of AI models so the models produce harmful or incorrect outputs.

7. AI-Powered Botnets

Autonomous networks that adapt their behavior, hide themselves, and launch large-scale attacks without human input.

8. Model Theft Attacks (AI IP Breach)

Attackers steal proprietary machine-learning models to copy business logic or weaken security systems.

9. Autonomous Social Engineering Bots

AI agents that mimic human conversation so well that they trick users into giving sensitive information.

10. Supply Chain AI Attacks

Attackers target third-party vendors, SaaS tools, or code repositories — and inject malicious AI behaviors downstream.

These threats demand a proactive, AI-driven defense strategy. Traditional security tools alone are insufficient.

3. Why ‘Secure AI’ Will Become the No.1 Priority for CISOs

In 2025, every major enterprise is adopting AI. But few are prepared for the new risks that come with it. This is why Secure AI is quickly becoming the top agenda item for CISOs.

Key Reasons Secure AI Is Critical

1. AI Systems Expand the Attack Surface

Models, APIs, training data, and prompts all introduce new vulnerabilities not found in traditional IT.

2. LLMs Can Leak Sensitive Information

Poorly configured AI tools may reveal confidential data through unintended responses.

3. AI Can Be Manipulated

Prompt injection, data poisoning, adversarial inputs, and model hijacking are real risks — and growing.

4. AI Output Is Not Always Reliable

Hallucinations can lead to wrong decisions in fraud detection, authentication, or security workflows.

5. Regulations Are Coming

Governments and industries are drafting strict rules for responsible and secure AI usage.
Enterprises must adopt frameworks now to avoid compliance gaps later.

Secure AI Focus Areas for 2025

• Robust AI governance
• AI model access control
• Audit logs for all AI interactions
• Data classification for AI training
• Reinforced prompt security
• Red-team testing for AI models
• Continuous monitoring for anomalous AI behavior

CISOs must treat AI systems like any other critical infrastructure — with strong controls, guardrails, and oversight.

4. Deepfake Attacks and Voice Cloning: The New Cybercrime Epidemic

Deepfakes are no longer experimental tech — they are a full-scale cybercrime weapon.

Why Deepfakes Are Dangerous

• They are incredibly realistic
• They are cheap to produce
• They can be personalized at scale
• They bypass traditional identity verification
• They exploit the most trusted attack vector: human psychology

Common Deepfake Attack Scenarios

• CEO video calls instructing employees to transfer funds
• Voice messages impersonating senior leaders
• Fake customer service calls requesting account access
• Manipulated videos damaging a brand’s reputation
• Political deepfakes used to mislead public opinion

How Enterprises Can Defend Against Deepfakes

• Use multi-factor authentication for all approvals
• Train employees to verify sensitive requests
• Deploy deepfake detection tools
• Monitor brand mentions for fake media
• Maintain zero-trust protocols

Deepfake attacks are expected to grow over 300% in 2025 — making them one of the most urgent cyber threats.

Final Thoughts

Cybersecurity in 2025 is a battle of AI vs AI. Hackers are becoming faster, more sophisticated, and heavily automated. But defenders are equally empowered with AI-driven detection, prediction, and protection tools.

The organizations that will thrive in this new landscape are those that:

• Embrace Secure AI practices
• Strengthen governance around all AI deployments
• Train employees on AI-enabled threats
• Invest in real-time, automated defense systems

AI is reshaping cybersecurity forever — and the winners will be those who prepare today, not tomorrow.

https://www.effectivegatecpm.com/mi4b39vn41?key=c4d8c0403f606dfdf446b73ba7ab537f

The post AI and Cyber Security ! first appeared on Manoj Kumar Nair.

AI for Business & Digital Transformation: What Enterprises Must Get Right in 2025

Artificial Intelligence has moved from being a futuristic concept to becoming the core driver of enterprise transformation. But as companies race to adopt AI, one truth is becoming clear: experiments are no longer enough. Organizations now need measurable business value, not just impressive demos.

From shifting away from PoC-driven AI adoption to handling “Shadow AI,” from embracing Small Language Models (SLMs) to implementing strong AI governance — 2025 marks a turning point for enterprise AI maturity.

Let us explore four critical pillars that define AI-driven digital transformation today.

1. From PoC AI Projects to Real ROI

For years, enterprises launched AI initiatives as “proof of concept” exercises. Most never moved to production. According to industry surveys, 70% of PoC AI projects fail to scale due to:

• Poor data quality
• Lack of integration with core systems
• Limited business ownership
• Infrastructure and compliance challenges
• No clear ROI metrics

The Shift in 2025:

Organizations are now adopting Outcome-Driven AI, not PoC-Driven AI.

This involves:

Problem-first, not technology-first approach

Instead of: “Let’s try AI for this use-case,”
Companies now ask:
“What business problem delivers the highest value if solved using AI?”

Clear ROI frameworks

Teams define value using measurable KPIs such as:

• Cost savings
• Time reduction
• Revenue uplift
• Customer satisfaction
• Risk reduction

Production-grade architecture

Enterprises are building:

• AI pipelines
• Automated model monitoring
• Infrastructure that scales
• Full integration with ERP, CRM, HRMS & operations systems

Cross-functional ownership

AI becomes successful when business, IT, and data teams own it together — not in silos.

Result: More AI projects are reaching production, delivering tangible value instead of remaining experiments.

2. Shadow AI — The Hidden Risk CIOs Are Finally Waking Up To

Shadow AI refers to employees using unauthorized AI tools without IT or security oversight.

Think ChatGPT, Bard, mid-level automation tools, browser extensions, code assistants — all used unofficially.

Why Shadow AI Is Dangerous

• Sensitive data may be uploaded to external AI systems
• No audit trail or usage visibility
• Competitive or customer data can leak
• AI outputs may be inaccurate or biased
• Violates compliance (GDPR, DPDP Act, industry norms)
• Creates parallel systems of automation without governance

This has become a top CIO concern in 2025, especially in sectors like banking, healthcare, IT, manufacturing, and consulting.

How Enterprises Are Responding

Creating approved AI tools lists

Employees can only use vetted & sanctioned tools.

Deploying internal enterprise AI assistants

Secure, private LLMs inside the company environment.

AI usage monitoring solutions

Tracking prompts, data exposure, and usage patterns.

Employee training on ethical & safe use

CIOs now treat “AI literacy” like cybersecurity training.

Clear policies on what data can go into AI systems

Data handling guidelines are becoming mandatory.

Shadow AI is not just a technology risk — it’s an enterprise trust and compliance risk.

3. The Rise of Small Language Models (SLMs)

Why Enterprises Choose SLMs Over Large GPT-Scale Models

2023–2024 was dominated by massive language models with hundreds of billions of parameters. But today, more enterprises are moving to Small Language Models (SLMs).

Why?

Lower cost

SLMs require significantly less compute — reducing infrastructure cost.

Faster inference

Ideal for real-time use cases like call centers, chatbots, or field mobility apps.

On-prem and edge deployment

SLMs can run:

• inside a laptop
• on small servers
• in private cloud
• even on mobile devices

This solves the privacy problem and removes dependency on public clouds.

Domain-specific accuracy

SLMs are easier to fine-tune for:

• Finance
• Insurance
• Healthcare
• Retail
• Manufacturing
• IT operations
• Cybersecurity

Better data privacy & compliance

No external data transfer → zero regulatory risk.

High control, low vendor lock-in

Enterprises can customize, audit, and govern these models easily.

Examples of popular SLMs in enterprise use:

• LLaMA 3.1 8B / 70B
• Mistral 7B
• Phi-3
• Gemma 2B / 7B
• Local enterprise SLMs (custom models)

Large GPT-scale models still have their place, but SLMs provide the right balance of power, cost, privacy, and control for enterprise needs.

4. AI Governance Framework — What Every Organization Must Implement in 2025

AI is powerful — but without governance, it becomes a risk.

Every organization needs a robust AI Governance Framework that covers:

1. Data Governance

• Data quality checks
• Metadata management
• Privacy & consent management
• Role-based access control
• Secure data pipelines

2. Model Governance

• Model lineage tracking
• Version control & audit trails
• Explainability & transparency
• Bias detection
• Periodic retraining checks

3. Ethical & Responsible AI

• Fairness
• Non-discrimination
• Transparency in AI decisions
• No harmful or deceptive use

4. Risk & Compliance Governance

• DPDP Act compliance (India)
• GDPR (EU)
• SOC 2, ISO standards
• Sector-specific regulations (BFSI, healthcare, etc.)

5. Operational Governance

• Incident management
• Model drift monitoring
• Access logs
• AI output validation
• Human-in-the-loop approvals

6. Organizational Governance

• AI usage policy
• Approved tools list
• Shadow AI restrictions
• AI readiness training

A well-designed governance framework ensures that AI:
remains safe, ethical, compliant, scalable, and trustworthy.

Conclusion: AI-Driven Digital Transformation Is Entering Its Most Critical Phase

Businesses have matured beyond AI experimentation.
2025 is about scalable, governed, secure, and ROI-driven AI adoption.

The companies that succeed will be those that:

Use AI to solve real business problems
Control Shadow AI risks
Adopt Small Language Models for efficiency and privacy
Implement strong governance & responsible AI frameworks

AI is no longer just a technological upgrade —
it is the foundation of digital transformation for the next decade.

The post AI for Business & Digital Transformation first appeared on Manoj Kumar Nair.

According to leading forecasts, 30% of all repetitive office tasks will be handled by AI agents by 2027, reshaping the nature of work across every industry.

This is not science fiction. It is already happening.

What Exactly Are AI Agents?

Unlike traditional AI tools where humans ask a question and get an answer, AI agents behave like digital employees.

They can:

• Plan steps independently
• Access apps, databases, and external tools
• Execute workflows automatically
• Learn from previous tasks
• Work continuously without fatigue
• Interact with other agents

Think of them as intelligent, automated colleagues that take over tasks that are structured, repetitive, or clerical.

Examples already in use:

• Inbox triage agents
• Meeting summary & action item agents
• CRM/ERP automation agents
• Research agents
• Data cleanup & reporting agents
• Code generation & validation agents
• Customer service agents

This is just the beginning.

Why AI Agents Are Becoming So Powerful

Three shifts have accelerated their rise:

1. Multimodal AI

Modern models understand text, charts, images, PDFs, audio, and video — enabling richer decision-making and more accurate task execution.

2. API-Driven Workflows

Products like Microsoft Copilot Studio, OpenAI ChatGPT Actions, and AWS Bedrock Agents let AI trigger real actions in Slack, Outlook, CRM tools, HRMS, project management apps, finance systems, etc.

3. Better Reasoning & Planning

New agent frameworks can break a single instruction into multiple steps, evaluate results, correct mistakes, and move forward without supervision.

Together, these capabilities make AI agents not just “assistants”, but autonomous workers.

What Tasks Will AI Agents Replace by 2027?

Let’s break down the 30% task replacement forecast. The impact is strongest in these areas:

1. Email & Communication Management (40–60% automated)

• Sorting, prioritizing, tagging
• Drafting replies
• Scheduling meetings
• Extracting follow-ups
• Escalating issues
• Translating messages

Most inboxes will be 80% machine-filtered.

2. Document Creation & Reporting (25–50% automated)

• Preparing slides
• Drafting reports
• Creating weekly/monthly summaries
• Translating content
• Extracting data from PDFs

Agents will pull data from multiple systems, summarise it, and produce ready-to-use reports.

3. Data Entry, Cleanup & Verification (50–70% automated)

Anything that involves:

• Copying data
• Validating fields
• Updating CRM/ERP entries
• Cross-checking logs
• Matching records

These tasks are highly rule-based — perfect for AI.

4. Research & Analysis (30–50% automated)

• Competitor research
• Market analysis
• Risk analysis
• Trend scanning
• Drafting executive summaries

Agents can read hundreds of pages in seconds and extract actionable intelligence.

5. HR & Admin Workflows (20–40% automated)

• Screening resumes
• Scheduling interviews
• Drafting HR letters
• Employee queries
• Attendance & payroll checks

AI will handle the administrative load so HR can focus on people, not paperwork.

6. Project Management (25–35% automated)

• Updating project trackers
• Identifying blockers
• Creating follow-up lists
• Sending reminders
• Resource allocation suggestions

Your Monday-morning status meetings will soon be fully automated.

7. Customer Support (40–60% automated)

• Tier 1 and Tier 2 queries
• Refund workflows
• Ticket updates
• Basic troubleshooting
• Knowledge base access

Human agents will focus only on complex escalation cases.

Which Jobs Are Safe — And Which Are at Risk?

AI agents will NOT eliminate jobs overnight. But they will eliminate tasks inside every job role.

Roles that will evolve (not disappear)

• Managers
• IT professionals
• HR leaders
• Financial analysts
• Designers
• Cybersecurity experts
• Sales professionals
• Consultants
• Projects & operations managers

These roles involve judgment, creativity, customer interaction, or leadership — things AI can’t fully replicate.

Roles at highest risk

Jobs that are repetitive, clerical, or rule-based:

• Data entry operators
• Back-office staff
• Junior analysts
• Coordinators
• Process executives
• Call center Tier 1
• Basic support staff

These roles will shrink or transform into hybrid “AI-supervisory” roles.

What Professionals Must Do to Stay Relevant

The winners in the AI era are not the most technical — they are the most adaptable.

Here’s what every professional should do now:

1. Learn to Work WITH AI Agents (Not Against Them)

You don’t need hardcore coding skills. You only need to know:

• How to use AI tools effectively
• How to break tasks into steps
• How to validate AI output
• How to automate simple workflows

Become a digital supervisor.

2. Build Strong Human Skills

The most valued skills in an AI-first world are:

• Communication
• Critical thinking
• Leadership
• Creativity
• Decision-making
• Storytelling
• Contextual judgment

AI can write emails — but it cannot inspire teams or build relationships.

3. Master New AI Productivity Tools

Tools that will be standard by 2027:

• Microsoft Copilot
• Google Gemini Workspace
• OpenAI ChatGPT Actions
• Autonomous agent frameworks
• No-code workflow automation
• Domain-specific SLMs

Professionals using these tools will outperform those who don’t — by 5–10×.

4. Strengthen Your Domain Expertise

AI may automate tasks, but it cannot replace deep domain knowledge.
The best professionals will combine:

AI capability + domain expertise = unbeatable advantage

5. Shift From Task Execution → Strategy Execution

Let AI handle the repetitive work.
You focus on:

• Decision-making
• Problem-solving
• Innovation
• Customer experience
• Governance

This is where human impact becomes irreplaceable.

The Future Workplace: Humans + AI Agents Working Together

In 2027 and beyond, the workplace will look like this:

• Every employee will have their own AI agent
• AI will prepare your day before you wake up
• Emails, meeting notes, follow-ups, reports → automated
• AI will manage workflows, identify risks, and suggest strategies
• Teams will shift toward creativity, innovation, and complex problem-solving

The goal is not to replace humans.
The goal is to elevate humans by freeing them from repetitive tasks.

Final Thought

AI agents will transform the workplace faster than any technology in history.
The question is not “Will AI replace jobs?”
The real question is:

Will you learn to use AI to multiply your value — or will you let it outpace you?

The answer will define your career over the next three years.

The post How AI Agents will replace 30% of today’s Office Tasks by 2027 first appeared on Manoj Kumar Nair.

The Worst Cyberattacks in History – Lessons We Can’t Afford to Ignore

In today’s hyperconnected world, cybersecurity is no longer just an IT department concern—it’s a critical pillar of business continuity, national security, and even global stability. As organizations continue to adopt digital tools and platforms, the attack surface for cybercriminals and nation-state actors is growing rapidly.

Over the last two decades, several high-profile cyberattacks have disrupted industries, caused immense financial damage, and exposed vulnerabilities in even the most sophisticated systems. From ransomware to espionage to attacks targeting critical infrastructure, these incidents have changed the way we think about cybersecurity.

Here’s a deeper look at some of the worst cyberattacks in history, the damage they caused, and the lasting lessons they offer for business and government leaders alike.

1. NotPetya (2017) – The Most Expensive Cyberattack Ever

NotPetya was initially believed to be ransomware, but it was actually a wiper malware disguised to look like a ransomware strain. It originated in Ukraine through a compromised tax software update and quickly spread to multinational organizations through interconnected IT systems.

Impact:
NotPetya crippled operations at some of the world’s largest corporations. Danish shipping giant Maersk had to reinstall 4,000 servers and 45,000 PCs, effectively rebuilding its entire IT infrastructure from scratch. Pharmaceutical company Merck lost valuable research data. FedEx (via TNT Express) saw major delivery delays across Europe.

The U.S., UK, and other nations attributed the attack to Russian military intelligence targeting Ukraine, but its global reach caused unprecedented collateral damage.

Estimated losses exceeded $10 billion, making NotPetya the most financially devastating cyberattack in history.

Lesson learned:
Third-party software dependencies and supply chain vulnerabilities are among the weakest links in cybersecurity. Companies must evaluate their entire digital ecosystem—not just their internal defenses.

2. WannaCry (2017) – A Ransomware Pandemic

WannaCry ransomware spread globally in May 2017, exploiting a vulnerability in Microsoft Windows (EternalBlue), which had been leaked from the NSA. It encrypted files on infected machines and demanded Bitcoin ransom payments.

The NHS in the UK was among the hardest hit, with thousands of appointments and surgeries canceled. Across 150 countries, over 300,000 computers were infected in critical sectors like healthcare, telecommunications, transportation, and banking.

Microsoft issued emergency patches for even unsupported systems like Windows XP. The attack demonstrated just how quickly a vulnerability can be weaponized if left unpatched.

Estimated between $4 billion and $8 billion globally.

Lesson learned:
Timely patching and system updates are non-negotiable. Relying on outdated or unsupported systems can expose even mission-critical institutions to avoidable risk.

3. SolarWinds Supply Chain Attack (2020)

Attackers compromised the build process of SolarWinds’ Orion software, inserting a backdoor (“SUNBURST”) that was then distributed to customers through legitimate software updates.

Approximately 18,000 organizations—including the U.S. Department of Homeland Security, Treasury, Microsoft, FireEye, and several Fortune 500 companies—unknowingly installed the compromised software.

The attack is widely attributed to Russian nation-state actors. It was less about data destruction and more about cyber-espionage, allowing access to sensitive data for months before discovery.

Costs range from $90 million to potentially over $100 billion, including reputational damage, response costs, and national security implications.

Lesson learned:
Security in the software supply chain is vital. Companies must invest in better code integrity, software composition analysis, and zero-trust architectures.

4. Equifax Breach (2017) – Identity Theft at Scale

Equifax, one of the largest credit reporting agencies in the U.S., failed to patch a known vulnerability in Apache Struts. This oversight allowed attackers to access sensitive personal information of over 147 million Americans.

The breach exposed names, Social Security numbers, birth dates, addresses, and in some cases, driver’s license numbers and credit card information. Public outrage led to congressional hearings, class-action lawsuits, and a complete overhaul of Equifax’s security leadership.

Equifax ultimately paid over $1.4 billion in fines, settlements, and cybersecurity upgrades.

Lesson learned:
Cyber hygiene basics—like patching—are foundational. When these break down, the cost isn’t just financial; it’s a loss of public trust that can take years to rebuild.

5. Stuxnet (2010) – The Cyber Weapon That Changed Warfare

Stuxnet was a highly sophisticated worm discovered in 2010. It specifically targeted Siemens industrial control systems at Iran’s Natanz nuclear facility. Unlike most malware, Stuxnet caused physical destruction by manipulating the speed of uranium centrifuges.

Iran’s nuclear enrichment program was severely disrupted. It’s widely believed that the U.S. and Israel were behind the operation.

Stuxnet marked the beginning of a new era—cyber warfare. It showed that malware could be used not just to steal data but to destroy infrastructure.

Estimated at over $1 billion for Iran’s nuclear program, not including geopolitical ramifications.

Lesson learned:
Critical infrastructure must be designed with robust segmentation and specialized cybersecurity protections, as it is increasingly in the crosshairs of advanced threat actors.

6. Colonial Pipeline Ransomware Attack (2021)

The Colonial Pipeline, a major fuel transporter for the U.S. East Coast, fell victim to a ransomware attack by the DarkSide group. In response, the company shut down operations, creating widespread panic and fuel shortages.

Long lines formed at gas stations across several states. Prices surged, and the U.S. government issued emergency declarations. Colonial paid a $4.4 million ransom to recover its data—some of which was later recovered by the FBI.

Total estimated impact: $15 million to $50 million, including operational disruption, ransom, and response costs.

Lesson learned:
Critical infrastructure entities must adopt stronger cyber resilience plans, conduct regular incident response drills, and ensure backup systems are ready for rapid recovery.

7. Target Data Breach (2013)

Hackers gained access to Target’s network through a third-party HVAC vendor, stealing credit and debit card data from over 40 million customers and personal data from an additional 70 million.

The breach severely damaged Target’s brand, especially given the timing—during the holiday shopping season. The CIO and CEO both resigned amid the fallout.

Over $292 million, including a $18.5 million settlement with 47 U.S. states.

Lesson learned:
Even seemingly minor vendors can become the weakest link. Third-party risk management is essential.

8. Yahoo Data Breaches (2013–2014)

Yahoo suffered multiple data breaches affecting all 3 billion of its user accounts—making it the largest known data breach in history.

The company’s acquisition by Verizon was delayed and the purchase price reduced by $350 million. Yahoo’s reputation never fully recovered.

While exact figures are difficult to calculate, the loss in valuation, regulatory costs, and long-term brand erosion were immense.

Lesson learned:
Organizations must prioritize user data protection, invest in detection capabilities, and act transparently when breaches occur.

Key Takeaways for Today’s Leaders

1. Cybersecurity is a business risk—not just an IT issue.
   It affects brand, trust, revenue, and even national security. The boardroom needs to treat cybersecurity with the same urgency as financial performance.
2. Patch management is still a fundamental gap.
   Many of these massive attacks could have been prevented with basic maintenance and timely updates.
3. Third-party and supply chain vulnerabilities are growing.
   With increasing reliance on vendors and SaaS platforms, organizations must expand their threat models beyond their perimeter.
4. Incident response readiness is crucial.
   When—not if—a breach happens, your organization’s preparedness can make the difference between a brief disruption and a full-blown crisis.
5. Cyber hygiene needs to become a cultural norm.
   Training employees, enforcing MFA, reducing access privileges, and building a security-first culture is not optional—it’s essential.

The post The Worst Cyberattacks in History – Lessons We Can’t Afford to Ignore first appeared on Manoj Kumar Nair.

In the 1990s, software compliance was seemingly a non-issue. Today, it’s a crucial business issue with major cost and regulatory implications. How did this happen?

During the economic explosion of the ’90s, organizations purchased software with little concern for cost. No one, including the software manufacturers, paid much attention to software license compliance. Toward the end of 2001, as the growth in technology slowed considerably, the economic effects of Sept. 11 were painfully being felt, and a growing tide of regulatory reforms were being implemented, cost containment became the major issue for CIOs. CIOs found themselves under increasing pressure from both the chief financial officer and the chief risk officer to control costs while addressing increasing regulatory requirements, and they significantly curtailed their software purchases. As their traditional sources of revenue dried up, software manufacturers adopted an aggressive new approach, pursuing organizations they believed were out of compliance as a source of revenue.

Today, software vendors continue to generate significant revenues from zealous auditing, and there’s no end in sight. The BSA estimates that 25% of organizations that do business in the U.S. have some form of noncompliance, resulting in an estimated $6 billion in lost revenues to software manufacturers.

Potentially noncompliant organizations are identified in a variety of ways by software vendors:

• They compare their records of license sales against public information including the published number of employees and send a bill for the difference. The organization receiving the bill incurs the burden of proof to demonstrate compliance.
• They conduct audits themselves or through audit firms, often doing sweeps by geographical region or industry.
• They learn of suspected software piracy from disgruntled employees via anonymous Web sites and toll-free hot lines. With increasing IT turnover rates and offshore outsourcing, the incidence of piracy reporting by disgruntled employees has risen exponentially.

The Cost of Noncompliance

Noncompliance can be costly. Organizations that are out of compliance not only have to settle up with the manufacturers, but they may also have to pay fines that can total $100,000 per infraction. Fines equal the infringement on intellectual property plus four times the retail value of the software found to be unlicensed. Organizations that don’t focus on software compliance risk even more-costly audits from other software manufacturers, which tend to follow one another in auditing organizations that don’t have a handle on compliance.

The good news is that periodic audits are easy to do, are relatively inexpensive-and can offer major cost benefits. The new CIO in the example above who had been slapped with a $1 million bill developed a defensible, documented position on the organization’s compliance and was able to resolve the problem with less than $100,000 in license purchases.

How Do Organizations Fall Out of Compliance?

While some organizations choose to take their chances, most don’t knowingly put themselves at risk for being out of compliance.

Software license noncompliance can occur for a variety of reasons:

• Lack of an asset management system
• Misuse of MSDN media and licenses
• Reimaging of systems
• Assumption that vendor records are accurate
• Failure to perform periodic software audits
• Poor contract record-keeping
• Lack of understanding of software rights as granted in license (such as dual-use conditions) or changed licensing terms
• Overbuying server licenses but underbuying client licenses
• Lack of centralized or consistent procurement policies

Compliance isn’t easy. Many software manufacturers have so many different licensing programs that it takes a Ph.D. to make sense of them all. Manufacturers also include in their contracts the ability to change usage rights at will, which means that even the most diligent organizations may fall out of compliance without even realizing it.

Most organizations fall out of compliance as a result of a combination of inadequate record-keeping, ignorance of their license rights and lack of policies to address the issue. However, as hard as it is to stay in compliance, it’s even more difficult to face the consequences that can result from noncompliance.

 How Can Organizations Protect Themselves From Software Noncompliance Audits?

Organizations tend to take one of two approaches to software compliance. One is to perform “true ups” on a monthly, quarterly or yearly basis and then purchase appropriate licenses as necessary. The second, more common, approach is to hope for compliance and pray that the audit request never arrives.

 Organizations need to take proactive steps to protect themselves from potential damage. Unfortunately, many organizations are still in reactive mode and seriously address software compliance only when confronted with an audit or a bill from a manufacturer or watchdog group.

Organizations must first determine what’s actually running in their environments. Plenty of technology is available to provide that baseline data. However, just because software is installed doesn’t mean that the organization has the right to use it. As with many issues facing CIOs today, technology comprises only about 20% of the solution. Business processes make up the other 80%, and no auto-inventory tool can help you with that.

To truly understand if it’s in compliance, an organization needs not only a baseline comparison, but also a view of the software it has purchased, has installed and is using. It has to prove ownership, which requires matching actual inventory (gathered through customers’ autodiscovery tools or through a third-party inventory audit) with internal contracts and manufacturers’ records. This information can be used as protection against fines, fees and penalties.

Once organizations reconcile all the necessary information from various sources, they then need to take steps to ensure software compliance. These steps can include renegotiating contracts, removing licenses that are no longer needed or used, or purchasing additional licenses.

Software Optimization: A Step Beyond

While compliance is usually the primary objective of organizations concerned about software license audits or dealing with bills from manufacturers, software optimization is the ultimate benefit. Organizations can use the resulting information to maximize the value of their software assets.

Software is a huge cost for most organizations. Organizations tend to use only approximately 70% of the server licenses they pay for and only about 70% of capacity. According to leading analysts, many CIOs believe that as much as 20% of all installed desktop software is unused, often becoming “shelfware.” Software optimization depends on knowing who is using what, how much and whether software is just running as opposed to being used in a meaningful way. Software license agreements should be evaluated and renegotiated to ensure that the organization is getting the best value.

Organizations that go through the process of determining true software compliance can benefit in another way — by reusing the information to drive tangible cost savings through:

• Maintenance consolidation audits
• Business continuity/disaster recovery assessments
• Security baseline assessments
• Server/storage consolidation studies
• IT optimization/technology life-cycle reviews
• Data center relocations

When viewed from a strategic perspective, the painful process of ensuring software compliance can transform into a significant business opportunity.

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Following are the major sub domains of Information Technology:

1. Infrastructure
Infrastructure is known to be the systems of hardware and software that facilitate software components to support the delivery of business systems with the help of any IT-enabled procedures.

2. Computing
Computing is a known goal-oriented activity that requires creating computer machinery. It includes studying as well as experimenting with algorithm processing with the development of both hardware and software. Computing encompasses scientific, engineering, and tons of social aspects.

3. Software
The software comprises a set of instructions, data, and programs that operate the computer and execute specific tasks. It is the opposite of hardware which primarily describes the physical aspect of the computer.

4. Networks
Computer networks primarily concern themselves with interconnecting computing devices and exchanging data and resources with one another. These networks use a comprehensive system of rules called communication protocols to transmit information over physical and other wireless technologies.

5. APIs
The full form of API is Application Programming Interface. It deals with any software with a distinctive function. The interface in this aspect can be considered a contract of service between two applications. This defines the method of communicating between the networks through requests and responses.

6. Analytics
Analytics has a catch-all term of variety in different places of business intelligence and applications that relate to these initiatives. The process of analyzing information with the help of a particular domain is known as website analytics, an important aspect of Information Technology.

7. Robotic Process Automation
This IT automation deals with the creation of software and systems to replace any repeatable procedures. This is also responsible for reducing manual intervention. This helps accelerate the delivery of Information Technology infrastructure and applications by processing manual processes automatically that previously required a human touch.

8. Artificial intelligence
This is a simulation of human intelligence that is processed by machines, especially concerning computer systems. The specific AI applications are expert systems, natural language processing, speech recognition, and machine vision.

9. Cloud computing
In layman’s terms, cloud computing is the method of delivery of computing services. This includes server storage alongside databases and networking software analytics and intelligence. This offers faster innovation and flexible resources, and economies of scale.

10. Communications
Communications play a vital role in Information Technology. It is an umbrella that includes any communication device encompassing the segments of television, cellular phones, computer and network hardware, satellite systems, and many more. It also encompasses the other services that are associated with these applications at large.

11. Cybersecurity
Cyber security protects internet-connected systems for hardware and software data from the verge of cyber threats. Individuals and other enterprises, therefore, use the practice to protect themselves against unauthorized access to data centers and other computerized systems.

12. Internet of Things
The Internet of Things or IoT is the collective network of connected devices and the technology that helps make effective communications between the devices and the cloud.

13. Machine Learning
This branch of artificial intelligence and computer science focuses on using data and other algorithms to imitate human learning, thus improving accuracy.

14. Software/Application Development
This development method helps create a computer program with a set of other programs to perform different tasks that a business might require. Starting from the calculation of monthly expenses to scheduling any sales report, application business thereby helps in automating processes and increasing any kind of efficiency.

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Information technology has transformed the way we live and work, and it has brought numerous benefits to individuals, organizations, and society as a whole. IT has made it possible to automate routine tasks, improve communication, increase productivity, enhance decision-making, and foster innovation. IT is used in a wide range of fields, from business and education to healthcare and government, and it has become an essential part of many organizations’ operations.

As technology continues to evolve, the use of IT is likely to become even more pervasive, and new applications and innovations will emerge. The growth of big data, artificial intelligence, and the Internet of Things (IoT) is expected to bring about new opportunities and challenges in the field of IT, and those who are skilled in these areas will be in high demand.

IT has transformed the way we live and work, and it has brought numerous benefits to individuals, organizations, and society as a whole. Whether you are a business owner, student, healthcare provider, or government official, understanding how IT can be used to support your goals and objectives is essential in today’s digital world.

By embracing the opportunities presented by information technology, individuals and organizations can enhance their productivity, improve their decision-making, and foster innovation for the benefit of all.

The post Future Trends – Information Technology first appeared on Manoj Kumar Nair.

Would you drive a car that was way past its maintenance cycle? If your safety and security are dear to you, you obviously wouldn’t. The same logic applies to obsolete computers as they end up posing a major threat to your organization. The threat cannot be contained either; one aging hardware and software on even a single computer would put every other computer on your network at risk.

We are all very well-versed with security breaches that have plagued different devices across the world, PCs being the most vulnerable of them all. In such scenarios, obsolete PCs are a big NO. While we are at this, let’s also run you through the different aspects of outdated computers you need to know:

Increased Costs

Delaying technological upgradation in your organisation will only end up in increased costs. And as a business owner, that’s the last thing you want. Older technology is much less energy-efficient and requires a lot more power than newer technology. Also, older systems have higher failure rates than their newer counterparts. Likewise, the cost of fixing and repairing these old systems is way higher (due to non availability of parts) for systems that are more than four years old.

Decreased Productivity

If your systems are sluggish, you can’t blame your staff for decreasing productivity. Older systems are slower and crash more often, hampering productivity in your organisation. Updated technology enables your employees to be far more efficient, and they would be able to store and organize data in a much better way. And as per a latest survey – around 53% of employees feel that they would be able to perform better if their workplace had updated technology.

Security

This is one of the most important reasons why you need to upgrade your systems right away. Most companies update their software often with the hope that their systems will be safe from cyber-attacks. But sadly, that’s not how it works – most software updates don’t support older systems. This also means that your efforts of providing increased security to your organization clearly go down the drain.

Compliance Requirements

Certain industries have strict compliance requirements. And if your organization falls under one of these, you need to constantly upgrade your systems to meet the requirements of standards such as HIPAA. In case your technology is not up-to-the-mark, you may face penalties in the form of fees. Not meeting these standards that are laid out can also make your organization more susceptible to data breaches and hacks.

Lack of Flexibility

Old technology cannot perform like new technology, and this drawback limits the flexibility of your business. With improved tech, your firm gains an edge over other organizations while helping you work in different areas such as data analysis, which forms the base of critical decision making. With the new and updated software, you can also gauge the performance of your employees as well as the overall organization in a much better way.

How Susceptible are Your Outdated PCs?

Reports state that many companies across the world are currently operating on outdated computer systems. For this particular analysis, a sample of 35,000 companies was taken into consideration, and the results of this analysis were shocking.

Among the sample companies, over 2000 companies ran more than 50% of their computers on outdated versions of operating systems. Over 8500 firms were functioning on an obsolete version of internet browsers. While these reflected the gaps in the private sector, the government sector technology numbers aren’t promising either. Around 25% of government sector computers were running on outdated operating systems.

The effect can be seen when you consider WannaCry ransomware, which affected more than 300,000 computers across the world. Of the sample size, 20% of the computers fell prey to the WannaCry ransomware. The reason was simple – they were using Windows Vista or XP, both of which did not have a patch available. Both these outdated operating systems are no longer officially supported by Windows either.

These results are only from a sample size of 35,000 companies; the actual number runs into thousands across the world. No wonder the number of hacking incidents and cyber crimes are on the rise; organizations are not really taking this threat seriously. Some examples of organisations that have faced revenue losses due to outdated technology:

Summing Up

With the risks that we have listed and the examples of losses organizations faced due to outdated systems, we hope to have effectively conveyed the gravity of the issue. In today’s fast-paced world, keeping track of the number of cyberattacks is practically impossible. On your end, the only thing that you can do to protect the systems, data, and integrity of your organization is to frequently revamp and update the technology. It will save you a lot of expenses and losses in case of any mishaps. Staying prepared is the best way out, always.

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