The U.S. Department of Commerce's National Institute of Standards and Technology (NIST) has released its Artificial Intelligence Risk Management Framework (AI RMF 1.0), a guidance document for voluntary use by organizations designing, developing, deploying or using AI systems to help manage the many risks of AI technologies. The AI RMF follows a direction from Congress for NIST to develop the framework and was produced in close collaboration with the private and public sectors. It is intended to adapt to the AI landscape as technologies continue to develop, and to be used by organizations in varying degrees and capacities so that society can benefit from AI technologies while also being protected from its potential harms. "This voluntary framework will help develop and deploy AI technologies in ways that enable the United States, other nations and organizations to enhance AI trustworthiness while managing risks based on our democratic values," said Deputy Commerce Secretary Don Graves. "It should accelerate AI innovation and growth while advancing -- rather than restricting or damaging -- civil rights, civil liberties and equity for all."

The integration of digital technologies with a data-driven approach is transforming the way businesses operate and the value they aim to generate. The use of digital technologies such as cloud computing, artificial intelligence, and machine learning is enabling businesses to collect and analyze large amounts of data in real-time. Data analytics is not a buzzword any more. Business leaders will agree that data analytics is more than just numbers. It is a culture, a thought process that aims to leverage business intelligence.

As the uses of artificial intelligence (AI) continue to expand, there is a growing need for effective risk management to deal with issues ranging from technical, such as algorithm failures, to ethical, including bias in decision-making. A new ISO/IEC Standard provides essential guidance on risk management for organizations of all sizes and types that utilize AI in their systems or processes. ISO/IEC 23894 shows users how to manage AI-related risks effectively in order to achieve objectives and improve performance. "While AI systems are similar to traditional IT systems in many ways, they also present new aspects such as their ability to learn," says Wael William Diab, who chairs the joint IEC and ISO committee that develops AI standards. "SC 42 took the novel approach of developing a framework that employs well-established techniques around risk management. ISO/IEC 23894 provides a holistic and proactive approach to managing AI-related risks with the goal of enabling users to manage the risks effectively to harness the full potential of AI."

Key trend #1 -- Migration to the cloud will accelerate, although the rising scale of cloud costs will become increasingly scrutinized by finance types as the economy tightens. Organizations will struggle with hybrid and multi-cloud architectures. Watch for new and innovative pricing schema to help combat the rising costs (e.g., fee caps and fixed fee). The flexibility and scalability the cloud offers to organizations. Cloud computing allows companies to easily add or remove resources as needed, without having to invest in expensive hardware and infrastructure.

Today, most businesses are embracing digital transformation to meet ever-increasing customer expectations and to remain competitive and relevant in the world economy. While many organizations still struggle to adopt new technologies – often due to the lack of a tailored digital strategy and the reluctance of many to change the way of business operations that have been continuing for decades – digital transformation examples abound across all industries. According to Statista, worldwide digital transformation spending is projected to reach $2.8 trillion in 2025. Although digital transformation undeniably makes businesses, regardless of their size and kind, more viable and easily accessible to customers, becoming a digital-first organization is not as simple as it seems. Digital transformation involves simple processes like the integration of communication tools as well as complex ones such as the migration of entire business operations to a cloud-based platform.

Integrate automation into your business strategy or risk getting left behind. Over the last year, companies had to embrace technology and automation to maintain operations and keep customers serviced. Almost every business had to implement new systems and solutions rapidly to overcome immediate challenges brought on by the pandemic. Even if the trend existed before 2020, the last year saw unprecedented acceleration that is likely to continue. Every business owner now understands what benefits are available from process automation and advanced IT infrastructure.

A common definition is it's the simulation of human intelligence in machines that are programmed to think as humans do and impersonate their actions. AI can refer to any system that exhibits traits associated with the human mind, such as the ability to learn and solve problems. Technology products and services bolstered with AI capabilities can lead to significant benefits for organizations: increased efficiency, automation of manual processes, enhanced decision making, improved customer service and experience, and the ability to solve complex problems--to name a few. However, IT and business leaders need to be adept at separating the hype from the reality. As research firm Gartner notes, many organizations struggle to put a realistic value on AI. Business leaders tend to overestimate the impact of the technology and underestimate its complexity, it says.

Non-stop growth in artificial intelligence is undoubtedly increasing the efficiency of business operations. Machine Learning (ML) analytics is simplifying various internal activities in an organization which were once considered impossible without human assistance. Machine Learning capabilities are evolving with every passing day and are bringing a new edge to business operations. With highly result-oriented Machine learning models, businesses are now able to reach output targets not imagined before. Automating multiple organizational operations and creating sentient machines with an accurate response system Businesses are seeing an unprecedented level of growth in every sector.

The previous year has shown us that you have to be prepared for both expected and unexpected disruption, emerging risks, and economic uncertainties. Your business models and operations, employees and technology have to be agile and resilient. New business risks are everywhere. What challenges can organizations expect in the emerging and evolving risk landscape, and how can they overcome them? Ronald van Loon is a Protiviti partner, and recently had the opportunity to examine their study, conducted jointly with North Carolina State University Poole College of Management's Enterprise Risk Management (ERM) Initiative, on Executive Perspectives on Top Risks:2021 and 2030 and share his outlook regarding the shifting risk landscape and its impact on modern organizations.

Text Processing can transform the unstructured data into insightful information with the help of machine learning models. Organizations are now clamouring data to improve their businesses. An increase in Demand for customer-services has prompted the organizations to generate and utilize data on an everyday basis. But the humongous amount of data retrieved by organizations is unstructured and unsegregated. This creates a significant challenge for organizations to get an insight into the functionality of their businesses.