Artificial Intelligence is creating a buzzword with a significant aspect in the Finance sector. The financial sector around the world is trying to adopt & implement AI in its finance service capabilities. Exponential growth in the finance sector is measured in the last few years using Predictive Analysis. AI/machine learning technologies are helping bank business services to engage their potential customers. The rising popularity of messaging apps and the higher demands of customers in the banking, health, or wellness industry is giving chatbots a boost.

AI is making its presence felt everywhere in the connected world whether via data-driven deep learning technologies, smart robots, or autonomous vehicles. Industries ranging from manufacturing, retail, to healthcare and aerospace have all witnessed some remarkable examples of how AI technology is changing the way they do business in recent times. The impact of AI on an organization's ability to harness data and unlock new opportunities is huge. The transformative powers of AI-enabled solutions in enhancing the capabilities of business analytics and business intelligence have helped them achieve a prominent place in the Gartner Hype Cycle for Emerging Technologies. The sudden surge in the volume and complexity of data is driving the commercial adoption of AI across many industries.

Things such as extended learning beyond classrooms, real-time assessment and feedback, automated creation of personalized learning plans, and supporting teachers on time consuming tasks, are now possible courtesy of AI-based systems and applications. AI technologies are being utilized more and more these days to analyze the growing number of data points for evaluating the performance and the changing needs of students. AI is playing an increasingly valuable role in accelerating effectiveness and efficiencies in many areas of the educational administrative processes. Individualized learning is priority one for educators. AI-based solutions for education are rapidly accelerating the individualized learning mission.

Health care has come a long way and with the integration of technologies including artificial intelligence, machine learning¹ and natural language processing, clinicians derive insights from data with better outcomes. At the same time, the adoption of technology in healthcare has faced challenges with health care providers unable to harness the power of technology to address patient problems. Human-centered design is one framework gaining traction in the health care world, with physicians using frameworks to understand patient problems and address them. The human-centered model has the interest of patients and enables collaboration and communication. Simply put, human-centered design² brings together all stakeholders including patients, clinicians and technology to offer seamless experiences across the board.

How would you feel if an algorithm determined where your child went to college? This year Covid-19 locked down millions of high school seniors and governments around the world canceled year-end graduation exams, forcing examining boards everywhere to consider other ways of setting the final grades that would largely determine the future of the class of 2020. One of these Boards, the International Baccalaureate Organization (IBO), opted for using artificial intelligence (AI) to help set overall scores for high-school graduates based on students' past work and other historic data. The experiment was not a success, and thousands of unhappy students and parents have since launched a furious protest campaign. So, what went wrong and what does the experience tell us about the challenges that come with AI-enabled solutions?

The adoption of artificial intelligence (AI) in the enterprise continues: More than half (58 percent) of respondents to McKinsey & Company's recent global AI survey say their organizations have embedded at least one AI capability into a process or product in at least one function or business unit, up from 47 percent in 2018. Those increases were reported across all industries. What's more, nearly a third (30 percent) are using AI in products or processes across multiple business units and functions, McKinsey's data says. But, as the McKinsey research and others point out, some organizations are much further along in scaling their AI initiatives. What are teams succeeding with AI doing that others can emulate to propel their efforts?

In this blog, Microsoft talks about ways to address the top challenges to AI adoption through empowering inclusion, expanding access to accessible and affordable technology, supporting faculty and staff with skills, training, and resources, and partnering on long-terms AI strategies. Artificial intelligence is transforming higher education, according to a new study released today by IDC and commissioned by Microsoft. The report details the expected opportunity with AI in higher education and the challenges institutions must overcome to realize results. The study covered 509 higher education institutions in the US, and found that nearly all respondents--99.4 Fifteen percent called AI a "game-changer," and 54 percent of higher education institutions in the US have started to experiment with AI, while 38 percent have adopted AI as a core part of their business strategy.

The education sector is constantly changing after the involvement of advanced technologies Artificial intelligence and machine learning together. A report informs that by 2021, the application of AI in education and learning will increase by 47.5%. Artificial Intelligence in education is helping in processing the tedious challenges. As these days content is are becoming more accessible through smart devices, AI is a perfect way to change the way people learn educational materials. AI is changing the scenario of the education sector while evaluating the data-driven approaches.

The use of artificial intelligence and machine learning algorithms in healthcare is poised to expand significantly over the next few years, but beyond the investment strategies and technological foundations lie serious questions around the ethical and responsible use of AI. In an effort to clarify its own position and add to the debate, the executive vice president and chief technology officer for Royal Philips, Henk van Houten, has published a list of five guiding principles for the design and responsible use of AI in healthcare and personal health applications. The five principles – well-being, oversight, robustness, fairness, and transparency – all stem from the basic viewpoint that AI-enabled solutions should complement and benefit customers, patients, and society as a whole. First and foremost, well-being should be front of mind when developing healthcare AI solutions, van Houten argues, helping to alleviate overstretched healthcare systems, but more importantly to act as a means of supplying proactive care, informing and supporting healthy living over the course of a person's entire life. When it comes to oversight, van Houten called for proper validation and interpretation of AI-generated insights through the participation and collaboration of AI engineers, data scientists, and clinical experts.

SINGAPORE, October 18th, 2019 – Asia/Pacific* spending on artificial intelligence (AI) systems will reach USD 6.2 billion in 2019, recording an increase of almost 54% when compared to 2018, according to the latest IDC Worldwide Semiannual Artificial Intelligence Systems Spending Guide. Evidently, as industries invest aggressively in projects that utilize AI software capabilities, IDC expects spending on AI systems will increase to USD 21.4 billion by 2023 with a compound annual growth rate (CAGR) of 39.6% over the 2018-23 forecast period. From providing chat bots for better customer service to improve the efficiency of operations and tasks for their business models, industries like Banking, Retail and professional services are spending in this technology at scale says," Ritika Srivastava, Associate Market Analyst at IDC Asia/Pacific. In 2019, Asia/Pacific* spending on AI systems will be led by the Banking industry with 10.7% share of the total, followed by retail with a 10.2% share.