COVID-19 and efforts to contain it have had a profound impact on businesses and workers worldwide. As Canada and other countries take their first steps towards recovery, it's clear that the way we live and work will change significantly--and even permanently--in the new normal. The COVID-19 experience has dramatically accelerated companies' digital transformation. Organizations increasingly see data-driven decision making as crucial to their survival today and their success tomorrow, and they are driving forward with investments in AI, analytics, automation, and digitization to secure their future in a changing world. AI, digitization, and automation will open the door to tremendous opportunities for innovation and growth--and create new challenges and complexities for employers.

Leaders are seeking AI talent, even during this period of economic uncertainty. Companies at every level of AI sophistication see skills gaps--and are aiming to fill them. Companies across all industries have been scrambling to secure top AI talent from a pool that's not growing fast enough. Even during the economic disruptions and layoffs caused by the COVID-19 pandemic, the demand for AI talent has been strong. Leaders are looking to reduce costs through automation and increased efficiency, and AI has a real role to play in that effort.

Digital transformations have become a global trend in recent years. To be clear, in mainstream understanding, the term means to increase the use of data, which can then help us to build "smarter" machines, predict the future, dig out insights, eliminate human errors and maximize efficiency. However, according to the stats released by Boston Consulting Group (BCG) and McKinsey & Company, only about 30% of digital transformation projects ended up successfully. The result keeps us wondering: What are the key issues to account for such high failure rate? And more importantly, how can we resolve these issues?

AI is seeping into enterprises from all directions. It's being embedded in applications, software tools, devices and equipment. Yet, some organizations still don't have an AI strategy. "The journey to AI having an impact at a firm is challenging and sometimes long," said Nigel Duffy, global artificial intelligence leader at professional services firm EY. "To have an impact with AI you must solve a lot of problems, many of which have nothing to do directly with AI, [such as] how do you deploy solutions? How do you get them into your infrastructure? How do you get people to use them? What are the workforce and change management considerations? What kind of training is required? AI is too disruptive to ignore. If your company lacks an AI strategy by design, then it has one by default. A default strategy is a Wild, Wild West scenario in which AI is popping up in various places within an organization, without orchestration and alignment. The lack of cohesion and direction can result in several issues including governance and security. "[S]ome of those risks may not be well characterized, so they have not been addressed by the appropriate level of governance and review," said Duffy. "Most AI is going to come through procurement or it's going to come through the backdoor or technology you've deployed." Should an AI strategy be part of a digital transformation strategy? One reason some people think an AI strategy should be part of a digital transformation strategy is because the digital transformation strategy is viewed as the overarching business initiative that's facilitated by modern technologies. "If an organization's digital transformation strategy does not already include AI, then there is a real need to revisit the overall approach to transformation, said David Homa, director of the Digital Initiative at Harvard Business School.

Contract life cycle management systems have been around for decades, but the latest generation of AI-enabled tools can help elevate the contracting function. In recent years, organizations that have struggled to understand and manage the entirety of their obligations to customers and suppliers have shown increasing interest in their company's contract life cycle management (CLM). Specifically, organizations seem to be focused on CLM operating models, processes, and enabling technologies to manage these critical obligations. That appetite has increased in the wake of COVID-19, as many companies wrestle with a lack of visibility into their contracts across the enterprise. In the past, some organizations have standardized their processes within certain silos or even implemented CLM technology.

With its swift and dramatic impact on the global economy and the workforce that fuels it, the COVID-19 pandemic has sent an unequivocal message to enterprises around the world: Digital transformation is no longer a goal; it's an imperative. Fortunately, digital transformation already is underway at many corporations. In fact, a 2018 survey by Tech Pro Research revealed that 70% of companies either have already put a digital transformation strategy in place or are in the process of doing so. Organizations' appetite for digital transformation is evident at the highest echelons: As of 2019, 21% of the world's largest 2,500 public companies had designated a chief digital officer (CDO) or equivalent, according to PwC Strategy&. But the word "transformation" is illusory.

With how pervasive artificial intelligence (AI) is these days, executives--up to 85% of executives, in fact--know AI can fundamentally change their businesses. Organizations can look to use AI for everything from automating back-office processes to improving customer experience. In today's COVID-19 era, companies are adopting automation technologies to help compensate for disruption of core operations. Despite this enthusiasm, 76% of organizations surveyed barely broke even with their investments in AI capabilities. Only 6% had AI initiatives scaled across the enterprise, according to the Analytics Maturity Model (AMM) survey, developed jointly with Carnegie Mellon University through the Digital Transformation and Innovation Center sponsored by PwC.

Elite athletes know that in order to perform on the field, they first have to put in the prep work--proper nutrition and sleep, building strength and endurance in the gym. As more and more companies adopt AI technologies, they are quickly learning this same lesson: To get a big return from AI, they must first put in the preparation. As the adage goes, "Failing to prepare is preparing to fail." The research firm ESI ThoughtLab recently published a benchmarking study (cosponsored by Deloitte) exploring how companies are approaching their AI implementations, what value they are seeking, and what they are achieving.1 Today, companies are generally seeing a positive ROI from their AI implementations.

Leaders are seeking AI talent, even during this period of economic uncertainty. Companies at every level of AI sophistication see skills gaps--and are aiming to fill them. Companies across all industries have been scrambling to secure top AI talent from a pool that's not growing fast enough. Even during the economic disruptions and layoffs caused by the COVID-19 pandemic, the demand for AI talent has been strong. Leaders are looking to reduce costs through automation and increased efficiency, and AI has a real role to play in that effort.

Artificial Intelligence has become a nearly ubiquitous term nowadays. A Deloitte survey revealed that most companies -- a staggering 90 percent of those approached by the research and consultancy firm -- consider cognitive technologies to be of crucial strategic importance, and over 80 percent of those were either already using it on some level or planning to implement it in the near future. That is hardly surprising considering the dramatic efficiency savings that adoption can bring. According to Bill Eggers, executive director of Deloitte's Center for Government Insights, in the U.S. alone, federal employees spend about 4.3 billion hours per year on a variety of mundane tasks such as recording information and handling. He estimates that currently available AI and robotic process automation could free up about 1.3 billion of those hours by automating such tasks, effectively enabling quantum leaps in productivity as AI allows institutions to anticipate rather than merely react to problems after they occur.