In this exclusive webcast, Concentrix's Ryan Peterson, Everest Group's Shirley Hung, and Valmont's Heidi Hough discuss turning AI ambitions into operational advantages. The past year has marked a turning point in the corporate AI conversation. After a period of eager experimentation, organizations are now confronting a more complex reality: While investment in AI has never been higher, the path from pilot to production remains elusive. Three-quarters of enterprises remain stuck in experimentation mode, despite mounting pressure to convert early tests into operational gains. "Most organizations can suffer from what we like to call PTSD, or process technology skills and data challenges," says Shirley Hung, partner at Everest Group. "They have rigid, fragmented workflows that don't adapt well to change, technology systems that don't speak to each other, talent that is really immersed in low-value tasks rather than creating high impact.

Were you unable to attend Transform 2022? Check out all of the summit sessions in our on-demand library now! Digital twins enable enterprises to model and simulate buildings, products, manufacturing lines, facilities and processes. This can improve performance, quickly flag quality errors and support better decision-making. Today, most digital twin projects are one-off efforts.

Artificial intelligence is being adopted by organisations across the world to make better decisions, to innovate and to achieve increased efficiency with intelligent automation of business processes. This is leading organisations towards what I call'enterprise autonomy' – and to a world in which the majority of what we today call office work is automated. In my book'The Autonomous Enterprise – Powered by AI', published by BCS, The Chartered Institute for IT, this week, I define autonomous enterprises as having the bulk of their transactional and simple decision-making processes automated, but that is not all. They also tap the enormous amount of data that they are capturing from their digital and automated transactions for analysis and decision support. They use the data extensively to optimise their processes and business operations and, importantly, to innovate.

Digital transformation is nothing new. Depending on your definition, it can go back as far as the middle of the twentieth century. Even by the most conservative interpretations, leading enterprises have been on the digitalization path for a couple of decades. Over the last two years, however, digital transformation has taken on a new urgency. As organizations have weathered the upheavals instigated by the pandemic, digitization has become integral to their responses and also their future plans.

Of the many technologies with the potential to deliver significant value in the near future, Artificial Intelligence (AI) seems firmly planted atop the list for CIOs. Indeed, nearly all (95 percent) of the CIOs, CTOs, and technology leaders surveyed by IEEE agreed that AI will drive the majority of innovation across almost every industry sector in the next one to five years. "The focus will shift more toward AI-enabled transformation that solves more significant business problems with business-focused solutions," says Jerry Kurtz, executive VP, Insights & Data, at Capgemini Americas. "AI is an enabler and powerful capability, but the time for proofs of concept and science projects is quickly coming to an end. In 2022, expect AI engagements to become larger, more strategically significant, and more mission-critical – with a focus on long-term scalability."

CIOs are implementing both automation and AI at a quickening pace, prodded into expanding and expediating deployments for the speed and cost-saving efficiencies they each deliver. Recently released figures quantify the accelerating rate of adoption. More than 72% of global enterprises already started AI implementations, according to a January report from Everest Group. The firm expects that global spending on AI services will accelerate by 32%, from $25 billion in 2019 to $95 billion by 2024. The global robotic process automation (RPA) software market hit $1.2 billion at the end of 2019, posting year-on-year growth of more than 75%.

In the case of many advancing capabilities – such as machine learning or IoT – edge computing can be the link that supercharges potential business outcomes. For example, an organization might want to collect IoT data from sensors or devices in the field and process them using artificial intelligence (AI) in the cloud. "While this works in small deployments used for proof of concept and pilot projects, it lacks the ability to scale," says Dave McCarthy, research director within IDC's worldwide infrastructure practice focusing on edge strategies. "At some point, the amount of generated data overwhelms networks, resulting in unacceptable response times." Digital transformation is typically focused on the enablement of better products, services, experience, or business models.

This year, the Robotic Process Automation (RPA) market is predicted to hit $2.5 billion, having grown at a compound annual growth rate of between 70 and 80 percent over two years, according to a report produced by the Everest Group. There could be some 2.5 million robotic desktop automation (RDA) bots running on desktops and between 700,000 and 800,000 RPA robots on cloud and on-premise servers, Everest's data says. Although RPA usage is expanding across industries, geographies, and organizational sizes, many RPA buyers are still in the earliest stages of research or adoption. For those just starting with RPA, there are a number of key concepts that are helpful to understand. As we explained in our RPA in plain English primer, "RPA automates everyday processes that once required human action – often a great deal of it performed in rote, time-consuming fashion."

Supriyo Das, Vice President and Global Practice Head – Software Engineering, Industrial and Engineering Services, Wipro Limited said, "We are thrilled with this recognition. Product complexity is ever increasing with growing digital adoption, proliferation of software across industries, need for a seamless end user experience and minimal product recalls. At Wipro we have invested in infrastructure, talent, industry focused solutions and strong partnership to help our customers overcome these challenges. Our investments in new-age technologies such as 5G, Artificial Intelligence (AI) / Machine Learning (ML), Robotic Process Automation (RPA) Internet of Things (IoT), Blockchain, Certification & Compliance Labs and talent has started reaping benefits. We are confident that our offerings and solutions powered by Wipro EngineeringNXT platform will continue to meet and exceed expectations of customers. This recognition is a testimony to our commitment towards achieving excellence."

Artificial intelligence AI takes the lead over intelligent automation IA. Intelligent automation is the combination of "'robotic process automation and artificial intelligence to automate processes,'" according to a recent article on the topic in HR Dive, a publication for human resources professionals. Organizations that embrace intelligent automation may experience a return on investment of 200% or more, according to an Everest Group report cited by HR Dive. However, that doesn't mean organizations can expect a reduction in headcount, according to the report. In fact, projections of a reduction in workforce thanks to intelligent automation may be "highly exaggerated," the Everest Group noted.