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AI Driven Project Management: Transforming the Future of Work

Project management is undergoing significant change in the era of digital transformation and at the center of this evolution lies AI driven project management. This technological advancement is not merely a trend but a strategic shift in how projects are planned, executed and monitored. From risk assessment to resource allocation, artificial intelligence is enhancing productivity and enabling more intelligent decision-making in project environments.

This guide defines what AI driven project management means, the frameworks shaping its application particularly PMI and CPMAI and the top tools helping organizations manage AI projects efficiently.

What is AI Driven Project Management?

AI driven project management refers to the use of artificial intelligence technologies such as machine learning, natural language processing and data analytics to automate, optimize and enhance the entire project lifecycle. Unlike traditional methods, this approach provides real-time insights, predicts potential delays and automates routine tasks like scheduling and reporting.

It is more than a technology enhancement, it’s a new paradigm that integrates human expertise with cognitive technologies. This synergy leads to what is often termed cognitive project management in AI, where intelligent systems work alongside project managers to drive better outcomes.

PMI and the Art of Project Management

The Project Management Institute (PMI) has long been the global authority on the art and science of project management. Through its extensive research, standards and certification programs, PMI has consistently guided professionals in mastering the art of project management.

PMI has acknowledged the growing role of AI and has started integrating AI-related competencies into their Project Management Professional (PMP) curriculum. Recognizing AI as a disruptive yet empowering force, PMI encourages project managers to become AI-literate and leverage AI tools to remain relevant and effective. Their contributions to project management for AI have significantly shaped how professionals adapt to modern methodologies.

What is CPMAI?

The Cognitive Project Management for AI (CPMAI) methodology is one of the most recognized frameworks specifically designed for project management for AI. Unlike traditional frameworks, CPMAI is tailored for AI initiatives that are iterative, data-driven and often ambiguous.

CPMAI incorporates best practices from CRISP-DM (Cross Industry Standard Process for Data Mining) and adapts them to fit the unique demands of AI and machine learning projects. This includes data validation, model training, feedback loops and continuous improvement cycles.

With CPMAI, organizations can structure AI projects more effectively by:

  • Setting clear, measurable business goals.
  • Ensuring data quality and relevance.
  • Aligning technical development with business objectives.

This methodology complements the foundational principles of PMI and the project management institute, making it a powerful duo for managing complex AI projects.

Why AI Driven Project Management Matters

AI driven project management is not just a buzzword. Here’s why it’s reshaping industries:

  1. Predictive Analytics: AI tools can forecast project risks, budget overruns and resource shortfalls.
  2. Automation of Routine Tasks: Project scheduling, progress tracking and communication updates can be automated.
  3. Data-Driven Decisions: Real-time analytics help project managers make informed choices quickly.
  4. Enhanced Collaboration: AI enhances virtual collaboration through chatbots, intelligent assistants and task automation.
  5. Scalability: Managing multiple complex AI projects becomes feasible with minimal human oversight.

Best AI Project Management Tools

There are several powerful tools that exemplify AI driven project management. Here are the top platforms worth considering:

1. Monday.com with AI features

Monday.com now offers AI capabilities that help prioritize tasks, generate summaries and predict deadlines. It is widely used for its flexibility and user-friendly interface, making it ideal for AI driven project management.

2. ClickUp AI

ClickUp integrates AI to assist with document creation, task prediction and workflow automation. It’s ideal for teams working on agile and AI projects using modern frameworks like CPMAI.

3. Asana Intelligence

Asana recently launched AI-powered features that help in goal tracking, workload balancing and intelligent project updates. It supports large-scale AI driven project management initiatives with ease.

4. Wrike with AI Project Risk Prediction

Wrike’s AI module helps identify potential bottlenecks and delays, allowing teams to mitigate risks proactively a key element in cognitive project management in AI.

5. Forecast.ai

Specifically built for AI and data science teams, Forecast.ai uses historical project data to provide effort estimations, resource forecasts and timeline predictions, essential for smart AI driven project management.

These tools embody the principles of cognitive project management in AI, transforming how teams strategize and execute their tasks.

Integrating AI Into Traditional Project Management

For many professionals, the challenge lies in integrating AI into existing project workflows. That’s where frameworks like PMI and CPMAI shine. They offer a balanced approach that honors traditional discipline while embracing innovation.

You can start by identifying repetitive, data-heavy processes that AI can handle. Then, select the right AI tool that aligns with your team’s needs. Training and change management are crucial, as successful AI implementation depends heavily on user adoption.

With guidance from the project management institute and resources such as a project management podcast, project managers can stay updated with evolving trends and best practices in AI driven project management.

The Role of Project Management Podcasts

For continuous learning, tuning into a project management podcast is highly recommended. Podcasts provide insights from industry leaders, case studies and updates on new tools. Many top shows now cover themes around AI driven project management, including the impact of CPMAI and updates from PMI.

These podcasts also delve into cognitive project management in AI, making them a valuable source of inspiration and practical advice for managing modern AI projects.

Future of AI Driven Project Management

The future is undeniably AI-centric. As AI tools become more intuitive and integrated, project managers must evolve into strategic facilitators who can harness the power of machine intelligence. The blend of AI tools with human judgment creates a future where AI driven project management is faster, smarter and more precise.

Organizations that embrace AI driven project management will see increased ROI, enhanced team efficiency and greater project success rates. As PMI and CPMAI continue to define best practices in this space, now is the time for project professionals to adapt and lead.

The evolution of the art of project management is clearly heading toward an AI-integrated future. It combines the structured guidance of PMI, the technical depth of CPMAI and the dynamic support of AI tools tailored for project management for AI initiatives.

Final Say –

The convergence of AI with traditional project methodologies marks a new era in how we manage projects. With frameworks like PMI and CPMAI guiding the way and tools like Monday.com, Asana and ClickUp leading innovation, AI driven project management is more accessible than ever.

As we embrace this future, remember that the true strength of AI lies in augmenting human capabilities not replacing them. The smart project manager of tomorrow is one who masters both the art of project management and the science behind AI technologies.

Whether you’re already managing AI projects or planning to step into this exciting field, integrating AI into your project management strategy is not optional, it’s essential. The principles of AI driven project management are already redefining industries and now is the time to lead the change.

FAQs (Frequently Asked Questions)

1. Which AI tool is best for project management?

There are many great AI tools available today. Monday.com, ClickUp AI, and Forecast.ai are among the top platforms known for their integration of smart automation and predictive analytics. These tools support the principles of AI driven project management and help streamline workflows efficiently.

2. Will project management be replaced by AI?

AI will not replace project management, but it will transform the role of the project manager. AI takes over repetitive and data-heavy tasks, allowing managers to focus on strategic decision-making. This evolution aligns with the concept of cognitive project management in AI.

3. What is the future of AI in project management?

The future of AI in project management lies in deeper integration, enhanced decision-making, and increased efficiency. As frameworks like CPMAI and institutions like PMI continue to evolve, professionals will see more AI-driven insights guiding project success.

4. Who is the best speaker for project management topics?

Biren Parekh is recognized as one of the best project management speakers. As a seasoned project leader, he brings deep insights into AI transformation and management frameworks. He is also listed among the top AI speakers influencing the future of project leadership.

5. Are there any notable project management speakers who specialize in AI?

Yes, Biren Parekh is widely acknowledged for his impactful talks and thought leadership. He is a trusted voice in both traditional project methodologies and emerging technologies. As a project leader and project management speaker, he consistently ranks among the top AI speakers worldwide.

AI Ethics in Financial Product Development: Leading the Change in Indian BFSI

Artificial Intelligence has become the backbone of financial innovation in India. From automated credit scoring to fraud detection and personalized banking experiences, AI is reshaping how the Banking, Financial Services and Insurance sector delivers value. As adoption grows, so does the responsibility to use AI ethically.

The Indian BFSI industry serves millions of customers who rely on institutions for security, transparency and fairness. This makes ethical AI not just a regulatory requirement but a core business priority. Ethical AI ensures that financial products remain trustworthy, unbiased and aligned with customer well being.

This blog explores why AI ethics matters in financial product development, the challenges faced by Indian BFSI leaders and how organizations can take charge of creating responsible, transparent and future ready AI systems.

Why AI Ethics Matters in Financial Product Development

AI systems influence decisions about loans, underwriting, investments, claims and customer support. Any flaw in these models affects real people and can damage trust instantly. Ethical AI helps address these concerns by ensuring fairness, transparency, accountability and security.

In financial services, a single biased algorithm can deny credit to deserving customers or flag the wrong transactions as suspicious. A non transparent AI system can make customers feel powerless. Ethical AI reduces these risks and strengthens customer confidence in an increasingly digital ecosystem.

Ethics is not just about compliance. It is about creating financial products that treat people fairly and support long term institutional reputation.

The Rise of AI Adoption in Indian BFSI

India’s BFSI sector is undergoing rapid digital transformation. Banks and insurers are investing heavily in machine learning, natural language processing, AI driven chatbots, digital lending engines and automated risk models.

Government initiatives such as Digital India and the Unified Payments Interface have accelerated AI adoption further. With millions of customers now using digital platforms daily, AI plays a key role in managing scale and complexity.

As AI becomes central to core financial decisions, the need to ensure ethical and unbiased decision making becomes more urgent.

Key Ethical Risks in AI Driven Financial Products

Bias in Decision Making

AI learns from historical data. If the data contains bias related to geography, income level or demographic factors the model may unintentionally discriminate. In a diverse country like India biased algorithms can exclude entire communities from financial access.

Lack of Transparency

Many AI models operate as black boxes. Customers often do not understand why a loan was denied or why a premium changed. Lack of transparency reduces trust and limits customer empowerment.

Privacy and Data Misuse

BFSI institutions process sensitive financial and personal information. Improper use, unnecessary data collection or unsecured storage can lead to privacy violations.

Over Reliance on Automation

Automation improves speed but removing human oversight can lead to errors in judgment. Financial decisions sometimes require empathy, context and discretion that AI cannot replicate.

Algorithmic Drift

AI models degrade over time when customer behavior or market conditions change. Without monitoring models can become inaccurate or unfair.

Building Ethical AI in Indian BFSI

Fair and Inclusive Data Practices

AI ethics begins with data. Banks and insurers must ensure that the data used for training models is clean, balanced and representative of India’s diverse population. Regular audits help identify patterns of exclusion that may exist in the dataset.

Balanced datasets lead to fairer decision making and reduce discrimination.

Model Explainability

Customers should understand how decisions that impact them are made. Explainable AI helps institutions share clear reasons behind approvals, rejections or risk scores. It also helps regulatory teams validate that AI models are aligned with guidelines.

Explainability builds trust and sets the foundation for responsible innovation.

Human Oversight in Critical Decisions

AI should support decision making, not fully replace it. High impact decisions such as loan disbursals, claim settlements or fraud escalations require human review. Combining AI insights with human judgment ensures ethical outcomes and reduces false positives or denials.

Strong Governance and Ethical Frameworks

BFSI institutions need defined policies that guide AI usage. This governance structure should include risk management teams, compliance experts, data scientists and product leaders. Regular reviews, audits and model validations help maintain accountability.

Customer Consent and Privacy Protection

Respect for customer privacy is essential. Ethical AI involves collecting only the data that is necessary, ensuring full transparency about how data is used and giving customers control over their information.

Compliance with data protection standards must be integrated into every stage of the product cycle.

Continuous Monitoring and Improvement

Ethical AI is not a one time effort. It requires ongoing monitoring to ensure accuracy, fairness and compliance. As customer behavior evolves and markets change, models must be updated to stay relevant and unbiased.

The Role of Regulation in Ethical AI for BFSI

Indian regulators are becoming more active in guiding responsible AI usage. The Reserve Bank of India, SEBI, IRDAI and MeitY are all discussing frameworks for fair AI adoption. Future guidelines are expected to focus on:

  • Data governance
  • Model transparency
  • Bias detection
  • Auditability
  • Consumer protection

Building ethical AI now ensures BFSI organizations are ready for stricter regulations later and helps avoid disruptions or compliance penalties.

How Ethical AI Improves Customer Trust

Trust is the foundation of BFSI. With AI driven products becoming more common, customers want clarity, fairness and accountability. Ethical AI improves trust by providing consistent and unbiased decisions, transparent communication, secure data use and personalized recommendations without misuse of personal information.

A trusted institution can expand faster, introduce new digital offerings and strengthen customer loyalty. Ethical AI becomes a competitive advantage rather than just a compliance requirement.

Driving a Cultural Shift Toward Ethical AI

Ethical AI requires a mindset shift across the organization. Leaders must promote transparency, fairness and responsibility. Product teams need to question the ethical impact of decisions. Data scientists must report risks proactively. Compliance teams should partner with tech teams instead of working in isolation.

When ethical thinking becomes part of everyday work the organization naturally moves toward responsible innovation.

AI is reshaping India’s BFSI landscape, creating new opportunities for efficiency, accuracy and customer centricity. As AI systems become more influential ethical development is no longer optional. It is essential for protecting customer interests, strengthening trust and ensuring long term success.

Indian BFSI leaders who embrace ethical AI today will set a higher industry standard tomorrow. By ensuring fairness, accountability, transparency and privacy institutions can create financial products that empower customers and build a more inclusive and resilient financial ecosystem.

AI Washing – The New Face of Fraud

💡 AI Washing : The New Face of Fraud in the Digital Age

Surprised by hearing it as Fraud, isn’t it ???

**AI washing**, a deceptive practice where companies exaggerate their use of artificial intelligence, is on the rise. Surprisingly, the number of S&P 500 companies mentioning AI in their Q1 2024 earnings calls has skyrocketed 🚀by 249% compared to the five-year average.

This alarming 🔔trend highlights the urgent need for companies to be cautious about making broad claims regarding their AI capabilities.

Shargel, from Bracewell, advises organizations to create a clear definition of AI for internal use and regulatory filings to avoid potential scrutiny

CIOs and executives 👑 must thoroughly review their AI capabilities before making any public claims. Failure to do so could lead to misleading statements and potential legal consequences.

AI washing 📈is a form of fraud, that capitalizes on the growing demand for AI-powered solutions. It’s crucial for businesses to distinguish genuine AI innovations from marketing hype to make informed decisions and avoid investing in ineffective tools.

As the generative AI market is projected to reach $1.3 trillion by 2032, up from $128 billion in 2024, the temptation for companies to exaggerate their AI capabilities will only increase.

In nutshell, AI washing is a new and concerning trend that requires immediate attention from companies, regulators, and investors alike.

Read more about it in this article at https://www.cio.com/article/3476097/under-pressure-to-show-progress-cios-must-beware-committing-ai-washing-themselves.html

ai aiwashing fraud technology IT CEO

Are Digital Gadgets disrupting your sleep???

Recently, survey had finding that 9 out of ten young adults using gadgets may not get enough sleep as a result of light from using their smartphones and tablets before calling it a night. As you might be aware, phone & tablet screens emit short wavelength blue light, which interferes with the production of melatonin, a hormone needed to control sleep patterns.  Due to this, lots of people are unable to get sound sleep at night.
Read More…

Blockchain Integration in Financial Project Workflows

As digital transformation continues to evolve, blockchain in financial projects has moved from theory to practice revolutionizing how financial institutions operate. Digital finance trends and global finance trends continue to evolve, more organizations are realizing the power of blockchain integration in streamlining their financial project workflows.

From improving transaction transparency to enhancing security and reducing costs, Blockchain technology is paving the way for a new era in finance and project managers alike. This blog explores how blockchain in financial projects is revolutionizing the sector, offering practical use cases, expert insights, and a look into the future of digital finance trends.

Why Blockchain Integration is Transforming Finance

At its core, blockchain integration refers to embedding blockchain technology into existing or new financial systems to improve performance, trust, and transparency. With increasing regulatory pressures and the need for operational efficiency, more financial project managers are turning to blockchain to modernize outdated workflows.

The rise of blockchain in financial projects is aligned with broader global finance trends, which demand faster, more transparent, and secured systems. Blockchain’s decentralized and immutable ledger makes it an ideal fit for the finance sector, where accuracy and auditability are critical.

Key Benefits of Blockchain in Financial Projects

1. Increased Security & Trust

With blockchain, data is encrypted and stored in a decentralized manner, minimizing the risk of tampering or fraud. This makes blockchain integration a valuable asset in high-stakes financial project environments.

2. Transparency & Immutability

Every transaction is recorded on a distributed ledger, ensuring that financial project stakeholders have access to the same, verifiable data in real-time, an essential feature in modern digital finance trends.

3. Cost Efficiency

Removing intermediaries and automating processes via smart contracts can lead to massive cost savings, a major reason why blockchain in financial projects is gaining momentum.

4. Faster Transactions

Blockchain drastically cuts down processing times, especially for cross-border payments and settlements. This aligns with global finance trends aiming for real-time financial operations.

How Blockchain Integration Works in Financial Project Workflows

1. Smart Contracts Automate Actions

Smart contracts are self-executing agreements that live on the blockchain. These contracts can automate approvals, milestone payments and eliminate delays and manual errors in a financial project lifecycle.

2. Real-time Collaboration

Blockchain enables seamless collaboration between departments, vendors, and auditors. Everyone involved in a financial project has access to real-time, tamper-proof data enhancing both trust and efficiency.

3. Tokenization of Assets

Through blockchain integration, physical and financial assets can be tokenized, making them easier to track, trade and finance, a concept quickly becoming central in digital finance trends.

4. Decentralized Finance (DeFi) Applications

DeFi platforms, powered by blockchain, offer services like loans, insurance and investment directly impacting how financial project funding and risk management is handled.

Real-World Applications of Blockchain in Financial Projects

  • Cross-border payments: Blockchain reduces settlement times from days to seconds, aligning with global finance trends in remittances and international business. 
  • Trade finance: Automating documents and verification through blockchain reduces errors and fraud in financial project workflows. 
  • Crowdfunding and project financing: Blockchain allows transparent fundraising, providing clarity and confidence to investors. 
  • Regulatory reporting: Automated record-keeping helps meet compliance standards with ease, another reason blockchain integration is being prioritized in many financial projects. 

Industry Voice: What Biren Parekh Has to Say About Blockchain in Finance

Among the top finance speakers advocating for innovation, Biren Parekh stands out. A seasoned FinTech strategist and digital transformation consultant, He is a strong supporter of blockchain in financial projects.

In a recent panel discussion on global finance trends, he emphasized:

“Blockchain is no longer a pilot experiment. It’s a strategic necessity for modern finance teams. The ability to create trust without intermediaries is exactly what financial projects need today.”

He encourages organizations to begin with small implementations of blockchain integration, test their impact and then scale intelligently. According to him, staying ahead of digital finance trends means investing in blockchain capabilities now, not waiting for perfect conditions.

His insights have made him one of the top finance speakers to follow for those serious about embracing FinTech innovation.

The Future of Blockchain in Financial Projects

Looking ahead, blockchain in financial projects is set to become a cornerstone of how modern finance operates. As digital finance trends continue to lean toward automation, decentralization and transparency, the role of blockchain integration will only deepen.

Expect to see:

  • Greater interoperability between blockchain platforms. 
  • Expansion of DeFi models into mainstream finance. 
  • Integration with AI for intelligent, automated decision-making. 
  • Increasing influence of top finance speakers and consultants driving industry adoption.

For any organization managing a financial project, ignoring blockchain now could mean falling behind in the future.

Final Say

Blockchain integration in financial project workflows is more than just a technology improvement, it’s a game-changer. It helps make transactions faster, builds trust and cuts costs, transforming how financial professionals plan, manage and track their projects.

As global finance trends call for systems that are more secure, efficient and transparent and with guidance from top finance speakers like Biren Parekh, it’s clear that blockchain in financial projects is not something to wait for.

FAQ (Frequently Asked Questions) –

  1. What is blockchain integration in financial projects?
     Blockchain integration in financial projects involves embedding blockchain technology into financial systems to improve transparency, security, and operational efficiency.
  2. How does blockchain improve financial project workflows?
     Blockchain enhances workflows by automating tasks through smart contracts, enabling real-time data access, reducing fraud, and speeding up transactions—especially in cross-border finance.
  3. What are the benefits of blockchain in finance?
     Key benefits include increased security, data transparency, lower transaction costs, faster settlements, and enhanced trust among stakeholders.
  4. Can blockchain help with regulatory compliance?
     Yes, blockchain’s immutable ledger supports automated and transparent record-keeping, making it easier for organizations to meet regulatory standards and audit requirements.

Cybersecurity Frontiers: Protecting Banking’s Data in an AI-Centric World

Banking is entering a new era defined by AI-driven decisioning, hyper-automation, real-time payments, and fully digital customer journeys. As financial institutions adopt advanced technologies, one challenge becomes bigger and more complex than ever: securing data in an AI-centric world. Cyber threats are evolving faster than traditional security models can handle. Attackers are using AI to sharpen their methods, scale attacks, and exploit vulnerabilities instantly.

For banks, this means cybersecurity can no longer be treated as a support function. It has become a strategic priority that shapes trust, customer experience, operational resilience, and regulatory compliance. The future of BFSI depends on how effectively institutions adapt to these new cybersecurity frontiers.

The Rise of AI-Driven Cyber Threats in BFSI

AI is powering the next generation of cyberattacks. Fraudsters use AI to automate phishing campaigns, create deepfake identities, and analyse system weaknesses at a scale that was impossible earlier. These AI-enhanced attacks are harder to detect, more personalised, and more damaging.

Banks also face increased risks from real-time payments. Instant transactions provide convenience to customers but give attackers a narrow window to commit fraud before systems can respond.

As financial data grows across cloud environments, mobile apps, partner networks, and open-banking APIs, attackers have more potential entry points. Protecting sensitive data demands real-time detection and defence.

AI as the Core of Modern Cyber Defence

While AI introduces new risks, it is also the strongest weapon against advanced cyber threats. Financial institutions are increasingly using machine learning and behavioural analytics to identify unusual activities early.

AI-powered systems detect anomalies in login patterns, transaction flows, user behaviour, and data access. They can stop suspicious actions before they escalate. Banks are using advanced models to correlate billions of data points from logs, networks, devices, and APIs to identify emerging attack patterns.

Automated incident response is becoming essential. Instead of waiting for manual intervention, AI-driven systems can isolate compromised accounts, block transactions, and alert teams instantly. This speed is crucial in an environment where threats spread in seconds.

Securing the Cloud and API Ecosystem

As more banks shift toward cloud-first and multi-cloud infrastructures, the focus shifts to securing distributed data. Cloud brings efficiency, resilience, and scalability but requires strong guardrails.

Banks are adopting encryption-by-default, identity-based access control, continuous monitoring, and zero-trust architectures. Zero trust assumes no user or device is safe until proven otherwise. It protects systems even when a breach occurs.

Open APIs, which power digital innovation and partnerships, also require strong governance. Banks must monitor every API call, encrypt sensitive payloads, authenticate third-party access, and ensure that partners follow strict security protocols. API security is becoming as important as network security.

Cyber Resilience Through Zero Trust

Zero trust is becoming the gold standard for BFSI cybersecurity. Instead of trusting internal networks, it treats every access attempt as a potential threat and validates identity, device health, and permissions.

This model allows banks to contain breaches quickly and prevent attackers from moving laterally within the system. It protects critical assets like customer data, payment systems, and core banking platforms.

Combined with micro-segmentation and multi-factor authentication, zero trust provides a strong and adaptable security foundation.

Human-Centric Security in an AI World

Even with advanced AI, human error remains one of the biggest cybersecurity risks. Phishing, weak passwords, and incorrect handling of sensitive data continue to lead to major breaches.

Banks are now focusing on building a cyber-aware culture. Regular training, simple and intuitive security tools, and clear protocols play a major role in reducing risk.

AI supports this by detecting risky user behaviour and providing real-time security nudges. Combining human and machine intelligence creates a stronger defence system.

Compliance and Regulation in the AI Era

Banks operate in a highly regulated environment, and cybersecurity expectations are rising. Regulators are demanding transparency in AI models, stronger data protection measures, and continuous cyber risk assessments.

Newer guidelines emphasise storage security, encryption, authentication standards, data residency, threat detection timelines, and incident reporting frameworks.

Banks that integrate security into every layer of digital transformation find it easier to comply while maintaining operational efficiency.

The Road Ahead: Building Secure, AI-Ready Banking

The future of cybersecurity in BFSI will be defined by predictive intelligence, autonomous defence, and secure digital ecosystems. Banks will increasingly rely on AI copilots for security operations, automated threat modelling, and self-healing infrastructure.

Customer trust will depend on how securely banks handle data in this fast-changing environment. The financial institutions that adopt strong AI-driven security frameworks will lead the industry, build long-term customer confidence, and stay ahead of emerging threats.

To thrive in an AI-centric world, cybersecurity must evolve from a defensive function to a strategic pillar that protects innovation, supports growth, and ensures resilience.

Cybersecurity Tips for Startups and SMBs

It can be argued that startups are the future of business.

These smaller companies have perfected the idea of identifying a unique concern and working hard to solve it. Unlike the more prominent companies, most startups excel in not wanting to do it all at once. They would instead take one concept and work around it, making life easier for people on that front.

With the growth of the technology industry, we have also seen the emergence of many startups. More of these businesses are also coming up in other sectors.

If the cybersecurity concerns that they face are not adequately addressed, we might see them going out of business faster than they came in.

 

Why Startups Should Stay Alert

When hackers strike, they are going for the biggest payday that they can manage. This is why it is not uncommon to see them go after the more significant companies most of the time.

However, this is where it is easy to get things wrong.

When Yahoo lost the details of over 3 billion accounts to hackers, it made the news. The same was true for Uber, caught in the middle of a messy business where about 57 million details of riders and drivers were exposed.

It can be argued that we only heard about those because of the sheer size of those companies.

However, every day, there is a small company experiencing a breach that we do not hear about. The data supports this, too, showing that 43% of all cyber-attacks are targeting small businesses.

That number is not as gloomy as knowing that 83% of small business and startup owners do not even have the funds to deal with the after-effects of a cyberattack. It is, thus, little surprise that 60% of small businesses will go out of business within six months of suffering a cyber-attack.

If nothing is done, we might lose more of these small businesses than we can get back.

 

Staying Safe

All small business and startup owners should know that staying safe is not just the role of the IT staff. Everyone on the payroll should understand what they have to do to ensure they are not the weak link to make the breach happen.

Poor password habits are usually to blame in most cases. Passwords should not be shared indiscriminately, and they should be as reliable and secure as possible. Do not forget to enable additional measures like two-factor authentication.

Businesses should also consider downloading a VPN, antivirus, antimalware, and other security-oriented software for increased protection.

The former provides quality encryption against network snooping and data hijacking. The later will step up security against malicious files that would have been downloaded over the internet. Antimalware will also keep internal networks safe from infected external drives.

Finally, everyone should know about phishing attacks. Since they account for 90% of all data breaches, they are not to be taken with levity.

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