Despite all of the hype and somewhat negative sensationalism surrounding artificial intelligence (AI) lately, the World Economic Forum (WEF) has recently reaffirmed the technology’s potential to uproot the global banking order in the not-too-distant future, particularly due to the synergies derived from new-age technologies working hand-in-hand. In what was billed as “one of the world’s largest studies into the impact of AI in financial services”, WEF researchers have also noted the importance of workforce engagement and reskilling, proactive regulatory frameworks and maintaining customer focus to preserve the best interests of society at large.
“Democratization” of AI and mutual reinforcement with other technologies
Coincidentally, Gartner’slatest Hype Cycle for Emerging Technologies (2018) has proclaimed that in the next decade, AI will become widely available to the masses. This will, in turn, lead to “democratized” AI (in the form of autonomous cars and drones, smart robots, AI-powered chatbots and virtual assistants, augmented reality and biochips), essentially shaping the future of both technology and work. A quick glance at the Google Trends chart (analysing the popularity of top search queries in Google over time) confirms just as much – demonstrating a significant spike in the volume of searches for AI and machine learning from the public-at-large over the past two years.
It is this intersection of democratization of new technologies with workforce engagement and reskilling that I would like to address in this article, with particular focus on banking and financial services in general. While that specific intersection isn’t that unique for our industry—think about the advent of automated teller machines (ATMs) in the 1960s, personal computers in the 1980s and smartphones in the late 2000s—there is something about AI, and its mutual reinforcement with other new-age technologies, such as cloud computing, blockchain/distributed ledgers or facial recognition, that is certainly worth pausing for and carefully calibrating the strategic choices that lie ahead.
These choices are not easy. Unlike the previous cycles mentioned earlier, there are predictions out there that:
AI will soon outperform humans at many tasks, with a 50-percent chance of AI fully taking over those tasks (2017 Yale and Oxford study);
DFNO (Design-for-No-Operations) will start taking off, potentially leading to NoOps organizational structures that have no operations employees at all (Forrester 2011);
Up to 50 percent of the world’s economy (1.2 billion employees and $14.6 trillion in wages) could be affected bymass adoption of existing technologies for activities that are automatable (McKinsey 2017).
Competition of the future
Such predictions, among others, have already led to calls for protecting workers’ jobs and minimum incomes, with universal basic income (UBI) trials underway in a handful of countries. Of course, the concept of a universal basic income was an idea floated by Thomas More in his Utopia more than five centuries ago. In a financial-services context, there are a few other factors at play—such as changing customer expectations and continuously falling returns. The emergence of social-media platforms and upstart ecosystem entrants have forced banks around the world to “wake up” to the harsh new reality and attempt to adapt and transform quickly—which is no easy feat for 100+-years-old institutions!
This shifting banking landscape and the emergence of new, synergetic technologies has created a unique new leadership challenge for the industry—with regards to equipping employees with new tools and skills, they need to take advantage of AI (which may not be in their current companies or even industries). In the environment of increased competition and low returns, successful AI deployment and integration is rapidly becoming a necessary factor—one that is a lot more dependent on people than the actual technology. What is really important is the permission and adoption of the culture of learning that financial-services firms need to embrace. AI-enabled productivity improvements will facilitate smoother customer experience, reduce cost-income ratios and even open up new revenue opportunities through big-data analytics—but only if the top of the house has the vision and resilience to stick to that strategy with investments.
I was struck by the Toyota example in Australia. Toyota recently committed to pay the reskilling fees of 2,500 employees, who were unfortunately made redundant upon the factory’s closure in Melbourne. The automotive industry has historically been at the forefront of innovation, with robots now ubiquitous in plants worldwide. Some manufacturers started testing and adopting AI technology for self-driving vehicles in the early 2010s—far predating where the banking industry is today. As such, it really is no surprise that Toyota, along with other firms such as Holden and Ford, have taken such proactive approaches with their employees. And indeed, the Australian government aimed to minimize the societal impact with the fully funded $30 million Skills and Training Initiative (covering health and wellbeing services, financial education and digital literacy, skills assessments and retraining, among others).
Every technology strategy must be preceded by a people strategy.
Automation and the skills gap
LinkedIn’s 2017 Emerging Jobs Report showed a surging demand for new-age professions such as machine-learning engineers, data scientists and big-data developers. Of course, this demand must have replaced some other jobs, with one important trend being the evolution of specialist roles to more comprehensive skill-sets and job titles. This is consistent with employees’ own perceptions: according to a recent survey conducted by LinkedIn and Capgemini, nearly 30 percent of professionals believe their skills will be redundant in the next one to two years, if they aren’t already. With another 38 percent stating they believe their skills will be outdated within the next four to five years. This feeling is largely driven by lack of access to adequate training to stay abreast of new—largely digital—skills that are necessary to be successful in today’s fast-paced jobs landscape. For senior leaders in all industries, closing this skills gap is paramount to preserving employee trust and effectively moving their organizations into the future.
Another survey, this time of 300 senior leaders and C-Suite executives, has shown that while 82 percent of leaders plan to implement AI in the next three years, only 38 percent currently provide programmes aimed at reskilling employees to work alongside this technology. This really needs to change—not just for the sake of individual workers but for the overall health of businesses and societies at large.
Safety and security in the Age of AI
As far as societies are concerned, some further questions worth pondering (and I won’t pretend to know the answers to) would be the meaning and scope of privacy in this increasingly digitized world. Even aside from some of the recent and well-publicized data leaks, there are deeper implications to privacy from AI or blockchain angles—these technologies could be massively handicapped depending on where the public debates on privacy lead us, and they very well may diverge in different directions depending on the particular society (e.g. Open Banking in Australia, General Data Protection Regulation in Europe or Data Localization in China and Indonesia). The increasing likelihood of data or AI-powered algorithms falling into the wrong hands should also not be discounted—AI-driven cyber-attacks, in particular, can become less predictable and more precise.
Therefore, strong governance of AI implementation and careful calibration of potential risks versus rewards should always be top of mind for future leaders, both in public and private sectors alike.
While it is encouraging to see cases such as Toyota’s, Intel’s (which has trained 99,000 developers, students and professors in AI since April 2017) or Singapore’s (embarking on a three-year AI training initiative to cover 12,000 people), these are still a bit few and far between. As stipulated by the WEF, more concerted and targeted public-private collaborations are required in order to leapfrog into the real future—whether of work, technology, banking or anything else.
The ANZ Story…
For our part, ANZ has approached the challenging topic of AI adoption from multiple angles. Building on the relatively early implementation of robotic process automation (RPA), we have set out an overall AI strategy in the first instance, securing buy-in and targeted investment from senior leaders. We have then involved staff on the ground (impacted by the changes) to adopt and up- or re-skill, followed by wider-scale implementation in the key trade and supply-chain processes.
In fact, we went live with select AI capabilities earlier this year. One particular solution, built partially in-house and partially in collaboration with external vendors, covers the automated ability of machines to read, digitise, interpret and capture complex trade data. Tangible results for processes when we have gone live include:
- reduction in processing costs by ~25 percent to 30 percent;
- improvement in customer-turnaround times by about 40 percent.
On the back of this recent success, acknowledged by the industry as one of the leading AI deployments in financial services, ANZ is now aiming to scale this new automation approach into other processes in the corporate and institutional banking business across our major geographies. Our ultimate goal is to use AI as a key strategic capability in our automation agendawhile enabling our employees with appropriate tools and skills to adapt.
This relatively small innovation has also freed up our staff to focus on the trade data that is more unique and may actually require their involvement. It is exactly how AI is supposed to augment the traditional ways in which people (used to) work. AI isn’t necessarily going to replace people, but it will definitely make them better at whatever they do.
Emergence of augmented intelligence
Lately, there is a general affinity to frame the future as “humans vs. robots”—whereas I prefer another frame: that of “humans assisted by robots vs. humans alone”. While smartphones can certainly communicate with each other, they are most powerful when assisting humans with communications—and “robots” (or AI in general, for that matter) are the new smartphones in this scenario. Will some jobs be lost? Absolutely. But, as the past few centuries of human history have demonstrated, new jobs will emerge. I strongly believe that the future will belong to those who know their jobs well, recognize how to apply AI to their jobs and possess a strong and resilient mindset—– and both companies and governments have an important role to play to facilitate this future.
The views and opinions expressed in this article are those of the author and may not reflect the views of ANZ Banking Group.