Today's office workers spend a lot of time moving between different applications. They often have to reenter or copy and paste the same data – such as a customer's name and address details – from one application to another to complete a specific task. Such manual work is laborious, time-consuming, and prone to error. Robotic process automation (RPA) uses software robots to emulate human users and automate – as far as possible – these tedious, mundane tasks. Automation improves the user experience for both employees and customers. RPA boosts productivity and can typically free up between 15% and 30% of an employee's time to focus on tasks that deliver greater value to the organization and improve the customer experience. Companies which use SAP Intelligent RPA (RPA platform of SAP) achieve business benefits and show significant ROI (Return on Investment).

There has been a boom in SD-WAN deployments as enterprises around the globe seek new ways to boost network efficiency, simplify operations, and create new operating models to thrive in this new world of work. According to a report published by Research & Markets, the valuation of the global SD-WAN market is predicted to increase from USD $1.4 billion to USD $43.0 billion from 2019 to 203[1] with Asia Pacific poised to demonstrate the highest CAGR in the near future. With SD-WAN fast becoming a priority investment, it all boils down to rapidly delivering innovative business services that offer optimized user experiences (UX) at the right locations, for the right reasons, and with the right pricing to enable a unified future-ready networking fabric. This requires connecting people with SD-WAN technology with high levels of virtualization and automation across the network to improve human experiences, or in other words, creating an'Experience-First' network. However, the soaring reliance on cloud-based services and applications has magnified enterprises' need for enhanced agility, security, and flexibility of their existing SD-WAN infrastructures to ensure unparalleled network performance, service quality, and human experience.

Artificial Intelligence (AI) is clearly a growing force in the business sector. Recently, AI has broken the wrong perspective of many executives and business owners that it is applicable just to big companies like Facebook, Apple, Amazon, Netflix and Google. It is serving every corner possible when it comes to showing its potential. AI is taking centre stage across a wide variety of industries, including retail and manufacturing. New products are being embedded with virtual assistants, while chatbots are answering customer questions on everything from online office supplier's site to web hosting service provider's support page.

In 2016, AlphaGo, a machine, defeated 18-time world champion Lee Sedol at the game of Go, a complex board game requiring intuition, imagination, and strategic thinking--abilities long considered distinctly human. Since then, artificial intelligence (AI) technologies have advanced even further, 1 1. AI can be defined as the ability of a machine to perform cognitive functions associated with human minds (e.g., perceiving, reasoning, learning, and problem solving). It includes various capabilities, such as machine learning, facial recognition, computer vision, smart robotics, virtual agents, and autonomous vehicles. See "Global AI Survey: AI proves its worth, but few scale impact," November 2019, McKinsey.com.

Across a broad spectrum of sectors, artificial intelligence (AI), digital, the Internet of Things (IoT), process automation, and other technologies are shifting value from manufacturers and distributors to companies that operate end-to-end platforms and provide outcomes as-a-service. For many enterprises, that means constant change and disruption--and a growing threat of market obsolescence. Leaders, revising their five-year plans every quarter, are seeking ways to constantly reinvent their companies to stay ahead of the pack, with competitors of varying capabilities and scale and customers who expect more for less. And for many companies, the answer is large-scale global transformation. Indeed, 80 percent of CEOs in one study claim to have transformations in place to make their businesses more digital; 87 percent expect to see a change in their operating models within three years.1

As COVID-19 continues to affect millions of lives and livelihoods, it is delivering perhaps the most significant shock to industries--from education to healthcare to food supply--in almost a century. Mineral processing companies also have to grapple with profound uncertainty and volatility. Before COVID-19, some were already taking steps to build their capabilities to cope with fluctuations inherent in commodities markets. But recent events triggering challenges in workforce availability, supply chains, and demand created a need for higher levels of operational resilience in a short period of time. Here is where recent advances in artificial intelligence (AI) helped.

THE BIGGEST CHANGE being brought about by AI is not human replicas, but the emergence of digital operating models. These models aren't the sexy, headline-grabbing side of AI, but they are profoundly affecting how we do business and the way leaders of the twenty-first century must think. Marco Iansiti and Karim Lakhani, professors at Harvard Business School, explore these changes in Competing in the Age of AI with examples of businesses in many industries. "When a business is driven by AI, software instructions, and algorithms make up the critical path in the way the firm delivers value." And thus, how we think about the work we do and how we compete in the marketplace. The business plan describes the problem that is being solved for the customer--a reason to buy.

"The attention around AI tends to focus on the latest technologies," Iansiti argues, "but the firms that are thriving have harnessed the subtle, inherent power of AI to break down traditional operational constraints, capture new value, and accelerate growth and innovation." What sets AI-driven firms apart is their ability to avoid the inefficiencies and bottlenecks that plague growth when complexity -- primarily caused by humans -- outstrips organizational capacity. These firms strive to construct a model for operational execution that does not require human intervention (ideally, no real-time "human bottlenecks"). In the new digital operating model, most operational tasks circumvent humans entirely. The ultimate aim is to automate and digitize as many operational processes as possible to take advantage of digital reliability and scalability.