Automation helps organizations in delivering better efficiency as well as experience. As part of their digital transformation journey, organizations are focusing on end to end business process automation and IT process automation.

The key to successful AI/ML implementation is to set the ‘right expectations’ beforehand. Taking the time to plan the journey, forecast deviations and establish workarounds help businesses realize its full potential

Think big, but start small. A step-by-step approach starts with breaking down end-to-end processes into small bits and beginning automation with simple but high-impact use cases

Video analytics as a service will deliver sportspersons the competitive edge they seek by honing their performance.

The COVID-19 crisis and increased demand for remote work capabilities are driving the need for AI automation at an unprecedented rate.

AI algorithms in healthcare often tend to adopt unwanted biases inadvertently, leading to improper diagnosis and care recommendations. Explainable AI could be key to resolving it.

The lucrative business of banks selling their customers “financial advice” coupled with financial products has been in the spotlight recently with the events that have shaken up the banking and financial services world.

In 2012, the Knight Capital Group lost $460 million in 45 minutes because the systems were not setup for the risks the intelligent solution exposed them to¹ – this was down to a lack of proper governance mechanisms across the bot lifecycle.

The demand for remote work capabilities in the wake of the COVID-19 crisis is catalyzing the adoption of AI and Automation at an unprecedented pace.

Artificial Intelligence for Drug Discovery market is expected to be US$ 8,419 Million by 2026 1. This traction can be attributed to the growing conviction in the potential of Artificial Intelligence (AI) in reimagining Drug Discovery.

Learn how AI/ML are driving future solutions to be more accommodative of the ecosystem in which our customers’ businesses operate.

The rapid growth and adoption of technology in the last couple of decades has led to huge advances in scientific research and healthcare practices, improving both the quality of life and care.

In our interactions with enterprise leaders, we come across varied expectations. There would be situations when a chief marketing officer of the company would need help in terms of comprehending the customers better to market products more effectively

There has been a lot of hype around the possibility of robots replacing humans in numerous jobs across industries.

Contact center (customer care) is an important aspect of any large product/service organization.

Today sales teams across organizations are dealing with humungous amount of information.

Within the next ten years, Cognitive Computing will be omnipresent – not only from a customer‘s perspective but also from that of the companies.

Outlook, Adoption and Future across the enterprise

Today, an increasing number of organizations are adopting agile methodologies in their development lifecycle, thereby transforming and accelerating the whole development process, but that is not the case with operations.

In the medical insurance domain, the insurance company or payer is accountable for timely and accurate claims processing.

An organization’s business capability rests upon the efficiency of its Procure-to-Pay process, especially for companies that procure raw materials, transform the raw materials in some way and sell the finished goods in the market.

This article is about the evolution of our enterprise portal from a non-descript amalgamation of links to a tightly integrated, role-based platform for employee self-service and information

Using social media as a central element of business growth strategy has become a norm for organizations, both small and big.

Manual touchpoints within any system flow holds information that facilitates decision-making.

When it pertains to classification problems in Machine Learning (ML), the definition of accuracy is straightforward, it is “the ratio of the number of predictions that the model got correct to the total number of predictions made”.

Artificial intelligence (AI) is the simulation of the human intelligence process by machines.

Digital transformation and constantly evolving digital landscapes are making internal and external stakeholders hyper-connected across mobiles, social media and other digital avenues.

Traditionally, enterprises release Request for Proposals (RFPs) to define the scope of work for system integration and managed services. The eventual goal is to reduce the total cost of ownership (TCO) and drive better business outcomes.

With technological advancements taking shape at a rapid pace, Artificial Intelligence (AI) has become ubiquitous.

Game changing automation is about bringing together strategy, domain knowledge and technology.

Future of AI in Legal Departments: towards better, faster, and cheaper legal services

Technology has redefined farming over the years and technological advances have affected the agriculture industry in more ways than one.

AI is touching every aspect of our life to enhance efficiency but there are still some concerns surrounding it

It is time for enterprises to revisit the POC lifecycle, especially in the new digital paradigm powered by AI

An AI-based solution capable of assisting seamlessly can transform the response to large-scale disasters.

AI driven cognitive software platforms offer the potential to add value to advisory services, in private banking and wealth management

Getting classification in AI right

Adverse media screening can reveal involvement of entity in activities such as money-laundering, terrorist funding, organized crimes etc.

When it comes to deploying AI solutions, doing it alone can get tricky.

Artificial Intelligence (AI) is transforming the technology landscape of the digital age. The world is moving towards an increased adoption of AI powered smart applications/systems which will increase exponentially over the next few years.

Explainable AI paradigm provides better insights into the AI system and helps to open up the black box of deep learning architecture

Discover how to humanize AI to deliver analytics that matter?

It should be evident by now that AAI (Applied Artificial Intelligence) has crossed the hype bubble and has it’s presence in several use cases in marketing, sales, operations, IT, HR, fintech, healthcare and beyond.

Investment in AI is wasteful unless there is successful adoption & utilization

It is important to ensure that the AI solutions are validated for bias before putting these to use in real world applications

AI-driven moderations will help sports become more enjoyable and free from opportunities to cheat

AI and automation is not so much about technology as it is of changing human behavior.

Recombinant data strategies & ML models can help IT service providers create innovative offerings in AI-ML

AI is transforming the M&E space by improving efficiency and enhancing customer experience. This paper discusses its potential impact.

The need for an evolving fraud detection system necessitates an AI-based anomaly detection system in the Procure to Pay context. This paper details how.

AI has the power to transform telcos and will soon penetrate its every sphere

The Board is a collaborative knowledge-sharing forum designed to connect experts across industries and geographies

How do you get AI at the RIGHT place in the RIGHT process at the RIGHT time in your organization?

Characterizing licensing fee for different cognitive services can be an interesting direction for future work.

Companies building cognitive automation systems face challenges with respect to attractive pricing for clients

Chatbots are evolving as a mandatory enterprise tool.This paper presents an architectural approach for an efficient chatbot design using proxy patterns, based on the OOAD

AI is transforming the banking industry and redefining customer experience.

The need for an evolving fraud detection system necessitates an AI-based anomaly detection system in the Procure to Pay context. This paper details how.

Can you envisage a robot working alongside humans? Nagesh Mallikarjuna explores this dimension in his paper on Digital Colleagues.

An Autonomous Network in the Telecommunications industry can impact every aspect of a business. This paper discovers how

More than 70% of all costs of a Service Desk are labor-related which can result in costly human errors and lower customer satisfaction. This paper discusses how an unmanned, fully-automated Service Desk can overcome these challenges.

By 2020, AI will penetrate virtually every product and service and the role of the AI Solution Delivery Leader will evolve with the shift in the scale of AI adoption

When it comes to AI talent hunt, at all levels, quality and relevance must always take precedence over quantity. Let's explore the 'Double Pyramids' framework for AI talent planning while setting up an enterprise AI capability hub.

AI and automation have the power to boost your top line. It is time to think beyond just cost reduction and bottom line impacting metrics.

This paper discusses about how Artificial Intelligence can augment the human effort in performing complex tasks in the KYC process

This paper delves into some of the practical challenges in automating KYC process and how the right mix of executive buy-in, technology expertise, domain knowledge and change management can yield success

More than 70% of all costs of a Service Desk are labor-related which can result in costly human errors and lower customer satisfaction. This paper discusses how an unmanned, fully-automated Service Desk can overcome these challenges.

Customer Contact Centers will soon be passe and Customer Experience Centers will rule the roost as competition gets more intense.

This paper looks into the limitations in traditional Traceability process and how Natural Language Processing Techniques can enhance Traceability across SDLC.

Retailers must adjust their business strategies with an AI-first lens to keep pace with customer demands

Infrastructure Management Services (IMS) have always aimed at driving cost efficiencies, quality improvements and resilience.

The fact that AI is gaining steam and being leveraged by diverse organizations to create new business models cannot be disputed.

There has never been a better time to collaborate with bots – they are your new digital friends. Artificial Intelligence (AI) bots are getting to maturity to assist you achieve extraordinary levels of productivity

The Amazon order-fulfillment center in Tracy, California, is more than a million square feet. That’s equal to 28 football fields. Imagine if it was all up to humans to traverse this warehouse, finding, packing and shipping goods! But Amazon’s smart warehouse uses Kiva’s robots to make things easier for its employees.

Would you believe that your word processor’s autocorrect function is your day-to-day encounter with artificial intelligence? As simplistic as it may sound, autocorrect is indeed an artificial intelligence function: it traces patterns, understands trends, learns from past errors, and predicts what you meant. But that’s just the hazy beginning.

Insurance fraud detection is a challenging problem, given the variety of fraud patterns and relatively small ratio of known frauds in typical samples.

In my previous article, I spoke about how with the mainstreaming of Machine Learning and Deep Learning, it is becoming increasingly difficult to decipher how machines make decisions.

We started working on our anomaly detection suite of solutions two years back, with the platform being live at Wipro and our customers for well over a year now.

In my last blog , I spoke about the magnitude of damage P2P fraud can cause to the organization and the need to address the problem with a different mindset with a more data driven approach.

Organizations with large mobile workforce have their employees and back-office teams spending a significant amount of time and effort in claiming reimbursements for their business and other admissible expenses.

Insurers today have been under tremendous pressure to increase their overall profitability. With their topline growth restricted to a single digit, insurers are now looking at improving their bottom line by reducing the cost of risks and by managing other operating expenses.

Technology is disrupting business processes across industries at an unprecedented and exponential scale, with several business domains now at the tipping point.

In my previous article, I spoke about how with the mainstreaming of Machine Learning and Deep Learning, it is becoming increasingly difficult to decipher how machines make decisions.

In one of my recent papers, titled “Belling Schrodinger’s cat“, I had picked the analogy of Schrodinger’s thought experiment around how it was not possible to conceive.

Big Data techniques can enhance risk management through improved detection of frauds and violations of compliance controls – I spoke about it here earlier.

In my last blog, I stressed on the importance of understanding and defining the problem before getting on to execution.

Top concerns for executives today are not just to grow their businesses and outpace competition, but also the threat they could face from incidents of fraud and non-compliance.

The Procure to Pay (P2P) process does not often get as much focus as it merits in the organization’s overall risk landscape – especially for organizations with significant supply chains (manufacturing, retail etc.). However, the key risks involved are around control failures and can lead to overpayments, discrepancies in rates, poor tracking of payments made vs. goods or services received and finally outright fraud.

In this paper, automation service is defined as any method, technique or tool that can help reduce the intervention of human in any activity.

Last year an Artificial Intelligence (AI) system finally cleared the Turing test – a test where humans interacts with a machine and is unable to differentiate if they are actually interacting with a machine or a fellow human being.

This paper explores the 5 factors driving ‘The Automation Ecosystem Requisite’ and illustrates the art of the possible through real-world use cases.

Shift in the anomaly detection systems requires Big Data based pre-emptive anomaly detection systems.

Watch Wipro CIO Team’s human-centered, AI-led response to empower employees during the COVID-19 crisis

As we move towards a world of high volume, variety and velocity of data, AI and Automation can augment humans to scale operations with high level of accuracy. Rohit Adlakha (Vice President & Global Head, Wipro HOLMES and Automation Ecosystem, Wipro Ltd) and Ray Wang (Principal Analyst and Founder, Constellation Research, Inc.) discuss Wipro’s AI and automation journey and how humans, machines and processes can come together to drive outcomes for enterprises and enhance end use experience.

Big Data will provide a tremendous boost to the AI revolution. Wondering how? K R Sanjiv, CTO, Wipro Ltd. discusses the convergence of two technologies in this HBR and Wipro article.

Cognitive systems that can sense, learn, infer and interact are here and will unleash an exponential growth in computing power. What does the future look like? Find out in this infographic.

Recent advances in networking and communication technologies have led to the emergence of the Internet of Things (IoT) – a deeply interconnected web of machines. This paper explains what is driving the IoT and how industries are adopting it.

How is the digital economy changing the way information is disseminated in enterprises and the importance of intelligent data in this paradigm shift.

A report from The Economist Intelligence Unit (EIU) sponsored by Wipro Limited that draws upon a survey conducted in 2016 around the globe..

Over the next decade, cognitive computing–based software will become ubiquitous from both a consumer perspective and an enterprise perspective

AI here to help

Most of the high-priority incidents/outages that result in significant business losses do not happen in siloes.

Cost take-out is a big win for any automation project but it often over-shadows other aspects where AI could make a far bigger impact in terms of top-line.