The age of AI is upon us, changing our lives in ways we could never have imagined. Through emerging advances in AI technology, we are seeing an array of new applications that are transforming industries and improving our daily routines. As AI and digital technologies based on big data become increasingly sophisticated and are used to bring significant improvements in service quality and productivity, it is crucial to consider the ethical implications of these technologies. For instance, AI systems that make autonomous decisions about individuals, such as loan acceptance or insurance policies, can produce biased outcomes if the algorithms used to train the AI are not designed to be fair and unbiased. This can lead to situations where AI systems make unethical or unfair decisions without anyone being able to intervene. Further ethical issues raised include coercion of data disclosure, dehumanization and threat to human dignity, social deprivation, disempowerment, and social engineering.

The technology services market is constantly changing. As the COVID-19 pandemic showed us, the technology services players who were ready to adapt their business models, were ultimately better prepared. Remote working became the norm and overnight technology service providers became ready to change their processes and created new ways of collaborative working. As the pandemic and many countless disasters or challenges in the past have shown us, change is the only constant, and it is vital to differentiate in what is clearly a crowded technology services market. Observability With soaring IT complexity, it is increasingly becoming important for technology service providers to have a deep understanding of their highly distributed application topologies and dependencies.

New technologies can create new opportunities to engage with customers — but is it always worth it for companies to build out a presence on these platforms? When it comes to launching a voice assistant on Amazon Echo or Google Nest, recent research suggests the investment won’t necessarily pay off. The authors analyzed stock price data for nearly 100 companies before and after they released voice assistant features, and they found that while some firms experienced a positive bump in valuation after launching their voice assistant, others experienced no increase or even a notable decrease in market value. Specifically, firms that launched informational features experienced an average 1% increase in valuation, firms that launched object-control features experienced no change in stock price, and firms that launched transactional features actually experienced an average 1.2% decrease in market value. As such, the authors argue that companies should think carefully before investing in a voice assistant to ensure that the value added will be worth the substantial development costs.

People have become very familiar with the term artificial intelligence (AI), but many of its users have only a rudimentary understanding of how it actually works. As a result, to date financial services and many other industries have yet to leverage its full capabilities. For financial services firms, adoption of explainable AI could drive adoption of AI-related technologies from the current rate of 30% to as high as 50% in the next 18 months, according to Gartner analyst and vice president Moutusi Sau, adding that lack of explainability is inhibiting financial services providers from adopting/rolling out pilots and projects in lending and from offering more products to the "underbanked" -- those who don't seek banking products or services, many because they don't think they will qualify. Moving to "explainable AI" will remove much of the mystery around AI, and, as a result will drive adoption of more AI-driven services experts agree. The Global Explainable AI (XAI) market size is estimated to grow from $3.50 billion in 2020 to $21.03 billion by 2030, according to ResearchandMarkets.

New technologies have enabled banks, insurers and other financial services firms to overhaul their operations and identify different ways of serving their clients. Over recent decades, innovative products have transformed the financial services industry – from payment types including credit and debit cards, to transaction processing such as telephone and online banking, to saving options such as investment funds and structured products, to e-commerce for financial assets, to risk management techniques, and beyond. Financial services firms must embrace the opportunities offered by innovation and further integrate disruptive technologies, such as artificial intelligence (AI), advanced analytics, robotics, the cloud and blockchain, to enable new services and capabilities. While there is still a place for traditional banking and financial services, customer expectations and preferences are evolving. According to VMware, almost half of UK consumers prefer to engage with banks via apps rather than in person, while two-fifths believe their smartphone is more important than their wallet in powering financial transactions.

Artificial intelligence (AI) is rapidly gaining momentum as a vital business resource as organizations discover new use cases in their efforts to improve processes, increase efficiency and automate costly, manual tasks. Industries such as financial services are ideal for AI-driven applications and a related technology, machine learning (ML), because they can bolster customer service and leverage data to increase competitiveness. AI includes software that's designed to work in ways similar to the human brain, while machine learning encompasses programs that alter themselves based on data that's fed into the programs in order to train them. Recent industry research gives a sense of how AI usage is on the rise. Global spend on AI is forecasted to double during the next four years, growing to $110 billion in 2024, according to research firm IDC's Worldwide Artificial Intelligence Spending Guide.

Covid-19 has catalysed financial services organisations to harness Artificial Intelligence (AI) to improve customer experience (CX), says a report published by the Capgemini Research Institute. However, financial services firms' implementation of AI at scale is the lowest across all industries, and where AI has been deployed, there are still some customer expectations that are not being met -- with half of the customers saying they receive no value from AI-enabled interactions. The report, titled, Smart Money: How to drive AI at scale to transform the financial services customer experience, revealed that the deployment of AI to improve the overall CX has grown significantly in the financial services industry in the past three years. Nine in ten (94 per cent) organisations say that improving customer experience is the key objective behind launching new AI-enabled initiatives. Just over half of customers (51 per cent) have daily AI-enabled interactions (like talking to a chatbot) with banking and insurance firms.

Artificial intelligence (AI) and machine learning (ML) technologies are having a significant impact on today's enterprise, particularly in the professional services space where they are driving greater efficiency and productivity. But before companies jump into acquiring the latest products, it is vital to understand how an AI strategy can assist with the overall objectives and solve the key challenges in the business. Only then will AI deliver real value to the business. Legal and financial services firms are leading the way in this regard. Instead of following the trend of deploying generalized AI tools that can be used "horizontally" across many industries and workflows, an approach exemplified by tech giants like Microsoft, Google and Amazon, legal and financial organizations have chosen a more targeted approach.

Artificial intelligence (AI) and machine learning (ML) technologies are having a significant impact on today's enterprise, particularly in the professional services space where they are driving greater efficiency and productivity. But before companies jump into acquiring the latest products, it is vital to understand how an AI strategy can assist with the overall objectives and solve the key challenges in the business. Only then will AI deliver real value to the business. Legal and financial services firms are leading the way in this regard. Instead of following the trend of deploying generalized AI tools that can be used "horizontally" across many industries and workflows, an approach exemplified by tech giants like Microsoft, Google and Amazon, legal and financial organizations have chosen a more targeted approach.

A new report by the Capgemini Research Institute has found that financial services firms are lagging behind in digital transformation compared to other industry sectors. Financial services firms report falling confidence in their digital capabilities, and a shortage of the skills, leadership and collective vision needed to shape the digital future. The report, part of Capgemini's Global Digital Mastery Series, examines sentiment on digital and leadership capabilities among bank and insurance executives, comparing it to an equivalent study from 2012. Over 360 executives were surveyed from 213 companies whose combined 2017 revenue represents approximately $1.67 trillion. Compared to 2012, a smaller proportion of financial services executives said their organizations had the necessary digital capabilities to succeed – with the confident few falling from 41 percent to 37 percent.