In parallel, the telecom and internet revolution began to connect the world through internet where secured data can be accessed, shared, stored, viewed through the computers/mobiles using internet technologies. The linkage of computer, mobile devices with internet were restricted to specific industries initially and gradually spread to financial services, telecom, life sciences, medical, transport, aerospace and the likes. For eg, in a manufacturing sector, though Enterprise resource planning or ERP software is used to integrate the application and manage the business processes, an IOT connecting multiple applications and devices can use the intelligent data emanating from these applications to automate and improve productivity to a large extent. To conclude, as technology advancement is happening, an IOT with connected devices and sensors will revolutionize the day to day functioning with automation possible.
Amazon Web Services wants to make AI and machine learning available to every organization, even those who don't have expertise in-house. Also: What it takes to build artificial intelligence skills Apple's to-do list needs to include a dose of AI Artificial intelligence and machine learning: How to invest for the enterprise Bezos noted that AI is changing the nature of enterprise software itself. Areas of the enterprise to be impacted first by AI include digital marketing/marketing automation, salesforce automation, CRM and data analytics, the Cowen study, based on interviews with 146 leading AI researchers, entrepreneurs and VC executives, finds. Other enterprise areas likely to transformed early on include customer self-service, enterprise resource planning, human resource management and e-commerce.
The software giant has done so by adding a new adaptive access capabilities into Oracle Identity Cloud Services and has expanded its Cloud Access Security Broker service to support its SaaS products with automated threat detection. The Cloud CASB Cloud Service has an integrated user behavior engine, that establishes user baselines and compares activity to baseline to identify anomalous behavior. The CASB Cloud Service also integrates security monitoring and threat detection with Oracle's software-as-a-service (SaaS) applications, giving customers the ability to use machine learning to monitor threats to enterprise environments. Oracle threat detection may integrated with the Oracle Human Capital Management Cloud, the Enterprise Resource Planning Cloud, and the Customer Experience Cloud Suite.
Mr Virender Aggarwal, chief executive of Ramco Systems, knows what it is like to feel the world is collapsing around you. In January 2009, as the top man for Asia-Pacific, Middle East and Africa for Satyam Computer Services, a Big Six Indian outsourcing firm, he was summoned with other top executives to the company's Hyderabad headquarters for what he thought was a routine meeting. While in the city on HCL work, a chance airport encounter with Mr P. R. Venketrama Raja, vice-chairman of Ramco Systems, led to a friendship that often saw "VA", as Mr Aggarwal is known in the industry, offering free advice on the changes Ramco needed to make. Ramco focuses on aviation software, human resources & payroll, and ERP solutions based on Cloud.
Yes, artificial intelligence is proving out to be an excellent tool to optimise operational models and transform business operations for organisations all over the world. Advanced ERP systems with AI functionalities can assist businesses in discovering and leveraging gigantic volumes of structured data. The massive volumes of data generated can be utilised by businesses to eliminate error-prone mundane tasks and optimise operational processes. Artificial intelligence is reshaping the entire ERP software ecosystem thus, transforming business processes.
SAP is about as traditional a legacy vendor as you are likely to find, delivering complex on-prem ERP solutions for the largest organizations on the planet. And SAP S/4HANA, the company's public cloud product is designed to address that. It's important to understand that, even while SAP makes its move to the cloud, it's not completely abandoning its on-prem roots. And while he acknowledges that there is a level of complexity here with an ERP system you don't find with a phone app, it's still important to make it an easy update for customers.
The good news is that companies collect data at a rapid pace and in amounts that are growing year over year. So now we have two domino stone tracks running in parallel: data quality and ERP. There is another track that the company has to initiate to ensure that there is a solid base-line for AI solutions: consistent use of a simple, standardized and harmonized set of business processes. All of the three domino stone tracks, data, ERP and business process, need to rally first before any AI solution can be effectively deployed.
The good news is that companies collect data at a rapid pace and in amounts that are growing year over year. Their ERP solutions process transaction in-memory which means that transactional data is instantly accessible for analytics and subsequent transactions. So now we have two domino stone tracks running in parallel: data quality and ERP. All of the three domino stone tracks, data, ERP and business process, need to rally first before any AI solution can be effectively deployed.
The obvious approach is to implement an unsupervised, machine learning protective shield that delivers a defense layer to fortify IT security. A self-learning system with the flexibility of being able to cast a rapidly scalable safety net across an organization's information ecosystem, distributed or centralized, local or global, cloud or on-premise. Whether data resides in a large health system or is the ERP system of a large energy company or a financial institution, rogue users are identified instantly.
According to leading researchers, the most obvious candidates are the productivity applications like Enterprise Resource Planning (ERP) and Customer Relations Management (CRM) that have already subsumed much of the IT operational model, and this will effectively create a data environment that will, for the most part, manage itself in response to changing workload requirements. Backed by massive parallel processing, advanced algorithms and enormous amounts of data, these systems can actually improve their performance, and thus the processes they support, as time goes by – a complete reversal of the obsolescence that current systems face the moment they are deployed into production environments. AI will not only provide a more streamlined and less expensive IT footprint, it will boost the productivity of advanced analytical processes, increasingly diverse and distributed compute, storage and networking platforms and the real-time Big Data and IoT applications that are the key to competing in a digital services economy. Microsoft just launched an AI-infused Dynamics 365 platform on the Azure cloud that supports functions ranging from sales automation and customer service to manufacturing and supply chain execution.