Impact of Artificial Intelligence on Society

Category: Artificial Intelligence, Business, Machine Learning

“Artificial intelligence would be the ultimate version of Google. The ultimate search engine that would understand everything on the web. It would understand exactly what you wanted, and it would give you the right thing. We’re nowhere near doing that now. However, we can get incrementally closer to that, and that is basically what we work on.” – Larry Page

Artificial Intelligence (AI) has far reaching capabilities to address the challenges faced by society. Governments and regulatory bodies need to look at the benefits that can be derived from AI and put them to optimal utilization for achieving the desired results. The strategies deployed would be applicable not only for emerging countries but also for advanced nations of the world. Let’s look at some of the ways by which AI can be applied to different walks of life for creating a positive impact on society.

The evolution of Artificial Intelligence has fueled economic growth and innovation through digital empowerment. Businesses across the world need to motivate and equip their staff with future proofing skills like automation, machine learning and data analytics. This would help in fostering a culture of technical and financial inclusion and reduce the digital divide among nations. Policy makers, researchers, business leaders need to collaborate with each other for inclusive growth and development of new products and business models which can result in development of human capital and reduction of costs through automation.

Natural disasters like floods, earthquakes, cyclones could result in loss of lives, environmental damage and disruption to social and economic activities. AI helps in preparedness measures for planning and execution of crisis management by capturing and analyzing large amounts of satellite images within a short span of time. It can also support emergency response teams by modelling disaster zones for providing timely travel advisories, and mobilizing resources for finding citizens. Flood forecasting alerts can be shared in the regions which are impacted through inundation models and machine learning supplanting the traditional methods of manual forecasts.

Climate change is one of the major challenges faced by planet earth. AI helps to mitigate the impact of climate change by developing predictive models for environmental monitoring. It helps homeowners for designing energy efficient buildings and optimization of renewable energy. It helps in climate modelling by monitoring the rise in sea levels and ice sheets. Deforestation, climate change and usage of chemicals and fertilizers have a serious impact on the degradation of topsoil. Conservation of soil is extremely critical for preservation of farmable lands. AI helps in monitoring soil erosion and keeping the soil health at check with the help of complex algorithms and drones. It can help prevent illegal logging and catch wildlife poaching for building sustainable biodiversity and ecosystem.

The enhanced monitoring and diagnostic features of AI is a game changer in the field of healthcare. It helps in detecting diseases at an early stage for prescribing personalized treatment plans and drug protocols. It enables free flow of information electronically across medical facilities which helps in enhanced efficiency by reducing time delays. AI helps in identifying cancer, heart diseases and supports in delivering critical healthcare needs for patients suffering from trauma. It provides high end affordable healthcare through digitization and remote solutions.


We at Newlineinfo Corp have a dedicated team of highly skilled AI professionals capable of harnessing the power of AI for delivering scalable solutions that can build a better society.

Trends in AI – How to Prepare for AI Success

Category: Artificial Intelligence, Business, Machine Learning, Management

”Artificial intelligence and machine learning, as a dominant discipline within AI, is an amazing tool. In and of itself, it’s not good or bad. It’s not a magic solution. It isn’t the core of the problems in the world.” – Vivienne Ming

Artificial intelligence coupled with Machine and Data Learning has become an integral part of our lives and has gained acceptance across multiple industries covering biomedical intelligence, gaming, commute and financial services. Despite its far reaching advantages and benefits, organizations across the world are still grappling with multiple challenges to foster a culture of innovation that would drive enterprise level change and set the framework for growth and sustainability. Let’s look at some of the ways by which organizations can prepare themselves for successful implementation for AI for achieving competitive advantage in the future.

Before embarking on this AI journey, businesses need to review their existing processes for identifying any potential issues that need to be prioritized. Leadership team needs to have a clear agenda to fix these issues before making large investments into AI. There is a high probability that the implementation of Artificial Intelligence could result in automating some of the manual and repetitive tasks resulting in better workflows. However the top of the house issues or challenges could still remain unattended. In order to achieve a flywheel effect, businesses should view their operations holistically and not look at sporadic gains and one-off initiatives. This would help in transforming end customer experience through digital innovation and better product offerings.

The leadership team needs to defend their traditional ways of reporting and embrace new ways of developing well defined frameworks for building effective forecasting and modelling tools. Creating AI Models would help in predicting demand and supply changes for delivering customer centric solutions. Based on the demand projections companies would also be able to forecast their threats and opportunities that lie before them. Leadership team can make use of these insights for strategic planning and accelerating their investments in AI.

Leverage on the expertise of the digital workforce to transform raw data into actionable insights for achieving best results. However this cannot be done without acknowledging some of the key risks associated with AI that include data and bias risks. When they are not handled properly, these risks can cause severe damage to the reputation of the organization. Data is the lifeline of AI. While handling large volumes of data, businesses need to focus on ensuring that there is protection of customer data by enhancing their defenses against cyber threats and vulnerabilities.

Employees could fear job losses due to digital automation and replacement of many tasks with AI. This could impact employee morale resulting in poor performance and dwindling productivity. Before implementing AI, business leaders need to have regular discussions with their employees and restore their confidence in AI. Communicate openly with all staff members about the change and impress upon them the benefits associated with it. Capitalize on the skills and experience of staff members for creating focus groups and conduct training programs for making them future ready with digital competency. New jobs would need to be created for development, maintenance and management of AI systems. Collaborate effectively with all the key stakeholders and set transparent goals for achieving excellence through mutual acceptance and alignment towards organizational goals.


We at Newlineinfo Corp are committed towards future proofing our digital leadership by operationalizing data analytics and AI for achieving scalability and excellence in service delivery.

The Secret to AI Strategy – People

Category: Artificial Intelligence, Business, Deep Learning, Machine Learning

”Today’s AI is about new ways of connecting people to computers, people to knowledge, people to the physical world, and people to people.” – Patrick Winston

The advent of Artificial Intelligence has transformed the way businesses around the world are carrying out their operations. Companies which have fostered a culture of change and innovation have enhanced their corporate earnings and profitability through digital outreach that impacts their clientele. In order to competitive advantage, businesses need to reinvent themselves and be prepared to change their traditional mindset of treating AI as yet another plug and play technology through organizational transformation. Let’s look at some ways how this can be achieved by building a four layer framework.

The first layer in this multi pronged approach starts with having the right vision and the intent to achieve the desired organizational goals. Companies need to broaden their vision and look beyond the financial metrics for institutionalizing human centricity complemented by super human intelligence through Artificial Intelligence. Human centered Artificial Intelligence would help businesses overcome their challenges through strategic solutions and problem solving. AI is not going to replace humans but on the contrary leverage on human expertise and experience to achieve sustainable business growth and efficiency. Businesses need to achieve scalable business models by future proofing themselves through digitization and automation.

The second layer in achieving transformation through AI is through integration. Businesses need to bring about structural changes in the way they operate. Leadership team needs to review their organizational hierarchies and make concerted efforts to transition towards flatter structures that can help in vertical and horizontal integration of the workforce. Silos needs to be broken for drawing on the capabilities of different units within the organization. This would help in free flow of ideas and exchange of information resulting in unlocking hidden human potential and creativity. Build cross functional teams that consist of talented individuals who can brainstorm and provide innovative solutions for building customer centric products and adding value to the digital enterprise.

Next comes the Implementation phase. Implementation of AI poses multiple challenges like trust deficit, communication and behavioral issues. In order to overcome these challenges, think tanks of the organization need to connect with their employees on a regular basis to allay any fears of job loss due to implementation of AI. The leadership team needs to reinforce their faith in AI by helping their team members understand the vision and positive influences of this change. Site visits can be arranged to other companies who have implemented AI to quantify its benefits. Businesses can also look at running pilot projects in their operations that would help in socializing this change across different sections of their workforce for gaining acceptance and shedding any unconscious bias.

The final layer is Indication. Traditional productivity measures need to be flexed for building aspirational metrics. For tracking and measuring the performance of AI, businesses need to leverage on specific metrics like Key Performance Indicators like OKRs. The objective of the Objectives and Key Results (OKR) framework is to set transparent goals which are specific and measurable. OKR encourages team members to align themselves to their organizational goals. Leadership team needs to empower and motivate their teams to maximize their performance by incentivizing innovation and recognizing their efforts. This would bring about a culture of acknowledgement that would result in delivering high quality performance and superior business outcomes.

 We at Newlineinfo Corp have a highly engaged team committed to deliver scalable business solutions to our clients by harnessing the power of AI in the digital ecosystem.

Data Analytics: Efficient risk management

Category: Cyber Security, Data Management, Machine Learning, Management

“The risk management needs to lift up from risk control to risk intelligence which can identify the potential business growth opportunities.”― Pearl Zhu

Businesses need to constantly upgrade themselves to handle the risks emerging from a dynamic environment that is fraught with risk globally. They need to do a deep dive into their risk management strategies and look at fostering a culture of change for unlocking their business potential and achieving better business outcomes. Organizations need to think beyond traditional risk management methods through organisational transformation by adopting advancement technologies like advanced analytics. Let’s look at some of the ways by which it can be achieved. 

As a first step employees from the different levels of the organization need to actively participate in this journey for building their core competency and redefining the business processes. This would help in breaking the functional silos and unearth the value of data for building effective data models for forecasting future trends through collaboration and knowledge sharing. Customer is king and leveraging on new age analytics would help understanding the changing customer behavior by establishing customer models and identifying underlying patterns. By leveraging on data mining techniques large quantities of data can be analysed for better client engagement, revenue growth and cost optimisation. Using big data and analytics would also help businesses rethink their marketing campaigns by understanding customer behavior. 

Analytics help in assessing the exposure of the organization’s risk and its ability to measure and predict likely scenarios through forecasting techniques. In this process the analysts would come across huge volumes of data which could be structured or unstructured. Structured data are more qualitative in nature that would include numbers and values sourced form online forms network and server logs etc with limited usage and storage options. These can be used with the help of Machine Learning algorithms by business users. Unstructured data include posts in social media, website, internet of things which is gaining widespread importance due to its native format and scalable storage options. The availability of data can be both internal and external to the organization. Risk analytics helps in integrating them for deriving valuable business insights vand effective decision making. 

By analysing myriads of data sets and repetitive trend risk analytics helps In identifying and detecting any threats in their businesses, example frauds. Leadership can track the changes that resulted in transformations to the industry and take appreciated actions in the midst of crisis. It would help in preventing any damage done to the corporate identity and protect the brand image of the company. Organisations need to learn from the mistakes of their past and ensure that they are not repeated. Analytics help in understanding the reasons behind such mistakes and preventing them from happening again by applying preventive measures. All companies irrespective of their vintage or size need to have a dedicated team of risk managers who can use big data and analytics to evaluate risks in real time and quickly what gears and take appreciated actions during uncertainty. Creation of alerts for monitoring deviations in real time would help in identifying any outliers for problem solving and evaluating performance. 


We at Newlineinfo Corp make use of latest technologies like Artificial Intelligence, Machine Learning and Internet of things for evaluation risks and manage them proactively with the help of risk analytics tools for achieving business growth and resilience.

How to Compete in the Age of Artificial Intelligence

Category: Artificial Intelligence, Branding, Business, Machine Learning

“A company’s approach to value creation requires consciously choosing the precise problem it is solving for the customer and its positioning in the marketplace.”― Marco Iansiti

A peep into the annals of history would tell us how the industrial revolution transformed economies that were erstwhile involved in agriculture and handicrafts into large scale manufacturing through mechanisation and factory system. AI factory is now driving yet another industrial transformation by gathering large data, effective decision making and digitising the operations of the 21st century firms. 

Artificial Intelligence is set to transform the modus operandi of businesses and the leadership team needs to reinvent themselves to foster a culture of change and innovation for building sustainable business models that deliver long term growth and prosperity. The advent of AI has set the pace for the dynamic change in the digital ecosystem and all organisations are vying with each other to gain a competitive advantage in the future landscape. Let’s look at some of the ways by which business can deliver superior performance by making revolutionary changes to their operations by leveraging on the strengths of AI

The use of AI is spread across different industries like mobile payments, lending, wealth management, health insurance, credit rating services. These businesses are handled by high end algorithms with the help of sophisticated analytics that remediates concentration risks in niche skills and creates a platform for learning and development. Once AI is designed and deployed, there is a huge potential for generating value through digital automation across the run time. The programs built on the digital core helps in identifying tremendous opportunities for growth across different businesses and reduces the need for human intervention. 

Traditional organizations are confronted by the far fletched outreach of AI and need to revisit their operations to compete with the digital revolution. Traditional processes involve a people centric approach in operations management. Traditional companies need to revive their constraints in their workflow and look at different ways of adopting AI driven techniques that would help in remediating their bottlenecks. This would help in revamping their operations resulting in better value proposition for their clients through digitisation and enabling customer centric business offerings. Scale, scope and learning are considered as key enablers that help in achieving higher productivity and optimal costs. Traditional firms run the risks of diminishing returns due to archaic operating models which are dependent on human, labor and decision making. Reinventing traditional businesses with the help of analytics and data driven AI algorithms would help them build a competitive edge over others in the emerging digital ecosystem. 

The genesis of AI has given rise to a new age digital operating model called AI factory. AI factory follows a scientific approach in decision making by converting internal and external data into valuable insights for forecasting and projections. Businesses start to function differently and can relate to other digitized firms for developing custom models for predicting customer behavior and providing tailor made solutions. AI factory covers key components like data pipeline, development of algorithms, platform of experimentation and adequate software infrastructure. The transition from traditional to AI based organization requires a concerted effort and the leadership team needs to be wary of risks like loss of privacy and threats in cyber security. Unconstrained growth can be dangerous in the long run and could result in  social turbulence due to dislocations, inequality and market concentration. The change needs to be well defined and comply with the regulatory standards and guidelines laid down by governing bodies. 


We at Newlineinfo Corp are equipped with the skills of the future and set to expand our digital footprint through enterprise driven innovation and cognitive solutions. 

Cybersecurity trends to watch for in 2021

Category: Artificial Intelligence, Cyber Security, Deep Learning, Machine Learning

“Cybersecurity is a new area where equality will exist to allow intelligence to succeed”. – Ian R. McAndrew, PhD

The advent of new technologies poses serious security threats due to increasing cybercrimes and attacks by cyber criminals. Inorder to mitigate the threats and vulnerabilities in the cybersecurity landscape businesses can embrace Artificial Intelligence in their modus operandi. Let us look at some of the key implications of AI in Cybersecurity.

AI helps in faster detection of cyber risks and augments the recovery rate in the event of any cyberthreats through analytics and integrating the data sources with threat intelligence. AI sources huge amounts of risk data through research, blogs etc and provides sharp insights about cybersecurity alerts that helps in effective surveillance and staying ahead of any potential threats by raising the standards of Cybersecurity framework. Latest technologies like Machine Learning and Deep Learning techniques help in deciphering cyber risks and provide valuable inputs related to IP addresses of fraudsters and criminals. Security analysts can make informed decisions on the malicious code based on the inputs provided by AI and this saves the time and effort required to pursue large data sets for the cybersecurity professionals.

Due to the skyrocketing costs of recovering the system from  data breaches, businesses need to be prepared to handle any advanced cyber attacks in unforeseen circumstances. Creating a multi layered security system will help in securing the network infrastructure resulting in tightened control and adherence to compliance protocol. AI powered security tools and modern firewalls helps in proactive monitoring of network traffic and identifying the malicious file. Antivirus software can be used to remove the malefic content and viruses in the network infrastructure followed by regular backup procedures for demonstrating effective resilience and disaster recovery. 

AI and Machine Learning can be used for automating threat detection and building threat modelling by leveraging on observational data indicators. Deployment of powerful AI tools like Expert systems and neural networks would help in deploying threat models for identification of cyber threats.  AI and Machine Learning helps in consolidating the knowledge with the help of data analytics for building effective threat models. Business leaders and cybersecurity professionals need to actively engage in building a strategic framework for risk and management for safeguarding any cyber attacks like data poisoning in federated learning and circumvent malicious participants.

Cyber criminals use sophisticated techniques like distributed spam distraction, phishing etc.. for digital attacks with malefic intent. Such digital attacks can take place through emails or email attachments posting false URLs for the purpose of data mining and inflicting malware into the system resulting in financial frauds through business email compromise. The Machine Learning capability in AI helps in blocking the access to malicious links by scanning the images of the fake login pages and using visual indications to establish the genuineness of the login page. AI uses behavioural analytics and secured authentication to identify any fraudulent attempts in the digital landscape. AI upgrades it’s capabilities for detecting any phishing attacks from open source intelligence and it’s identification of phishing efforts breaks all geographical barriers and boundaries.

Development and promotion of ethical guidelines for AI systems would make it more reliable by promoting a culture of transparency, data privacy and adherence to safety standards. Businesses and researchers should be open for sharing ideas related to research carried out in AI for free flow of information and exchange of new ideas. This will help in raising the bar for reaching better heights in the use of the AI in Cybersecurity through collaborative efforts and research work for countering any sophisticated cyber attacks in the future. Businesses need to identify the scope of AI in their business and ensure that adequate testing is carried out before deploying AI. This would help in unearthing any potential risks and flaws that would go unnoticed.


Disposition of AI in cybersecurity provides critical information about potential threats and vulnerabilities. Businesses can now manage the cyberattacks proactively and minimize their threat exposures that help in ensuring business continuity by demonstrating their resilience. AI can help in identifying gaps in the security framework by analysing the effectiveness of infosec controls. Prescriptive controls offered by AI would help in building robust controls and enhancing the quality of cybersecurity governance. At Newlineinfo Corp have a dedicated workforce and driven by our passion to provide world class service delivery to our clients and stakeholders.

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