Thanks to its ease of use and scope of applications, Generative AI has the potential to level the corporate playing field, enabling any business of any size to incorporate artificial intelligence into their organization. However, as well as democratizing AI, tools such as ChatGPT also make it possible for all business leaders to fall into the same traps and make the same mistakes that until very recently were only open to the largest and best-financed organizations, especially when it comes to automation.
GenAI has made a dazzling public debut. It can write, verify or edit software code; create engaging marketing copy and equally engaging images; or design websites and corporate presentations. And, if we drill down further and focus that technology purely on elements of customer experience delivery, we find chatbots that deliver simple-to-use knowledge bases, small-scale customer sentiment analysis and the ability to generate personalized offers and packages, and other communication based on a customer’s history. And all of this is in addition to the capabilities we’ve come to expect from previous applications of AI.
An accessible advantage
Many of these advantages are available without a large upfront investment or major integration or customization program. As such, any organization can essentially buy an off-the-shelf competitive advantage that even a few years ago would have been out of reach — in terms of both costs and human resources — to any business beyond the Fortune 500.
Now factor in that GenAI has arrived at a moment in time when many businesses are under pressure to do more with less. In many countries there’s a real risk of recession or stagnation and, thanks to inflationary pressures combined with reduced consumer spending, organizations are seeing costs increase while transactions decrease.
And as such, it looks like an increasingly attractive means of helping organizations in their time of need. Indeed, this technology could prove to be a very powerful solution — a means of automating existing operations and adding new capabilities — but not until businesses identify the problems or use cases first. However, because the race for adoption and implementation has already started in many industry sectors, there’s a genuine risk that businesses start running before they understand why they’re running and what they’re racing towards.
Automation and job elimination
Irrespective of GenAI’s arrival, artificial intelligence had already asserted itself as the driving force behind the fourth industrial revolution. And in doing so, it had also become a catalyst for concern that an increasing ability to automate would lead to the elimination of many existing professional roles.
Whenever there’s a new technological breakthrough that has the potential to upend the status quo, there’s going to be a certain level of pushback. And there’s no escaping the fact that AI-infused automation is faster, more accurate and, when effectively scaled, more cost-effective at undertaking any number of repetitive, rules-based tasks than the average person. This capability is what made investment in and deployment of the technology a strategic priority among many large organizations over the past decade.
Supporting, not replacing
In its 2018 Future of Jobs report, the World Economic Forum (WEF) predicted up to 75 million jobs could be displaced as soon as 2025 because of AI’s growing capabilities. However, the report also noted that for the most part, business leaders perceived the technology as a means of supporting rather than replacing employees and potentially creating new types of roles and responsibilities. So, in essence, a net gain for the global workforce.
And, as such, less than 12 months after the report’s publication, 30% of organizations around the globe claimed to be ready for an enterprise-wide AI rollout with a focus on augmenting rather than eliminating jobs. And, even if there were major discrepancies between the sums involved, by the beginning of 2020, the majority of business leaders were investing up to $500,000 in AI initiatives, but the number of leaders preparing to invest $5 million or more in the technology had also doubled.
In terms of where that money was being funneled, automating tasks (35%) and supporting employees to make faster, better decisions (31%) were the top AI priorities for executives.
Crucially, these initiatives were mostly proofs of concepts and pilot schemes, where metrics were established, rollouts were gradual, and lessons were being learned and fed back into projects.
Pandemic panic
But then, of course, COVID hit and every business that could, turned to AI as a means of navigating their way through a very real Black Swan event. By the summer of 2020, 80% of organizations with an existing AI deployment had increased their use of the technology in relation to their business processes. The biggest advance in terms of the application was within digital operations, where 30% of organizations who had moved quickly believed they now had a competitive advantage. At the same time, one in four organizations significantly raised existing investments in the technology to improve customer experience, retention and revenue growth.
Indeed, during the pandemic, AI gave organizations in certain industries a material advantage. So much so that even businesses on the sidelines decided they needed to get in the game with 75% of organizations preparing to take their first steps towards AI adoption or increase existing investments once the pandemic started to stabilize, to give them the best chance of recovery.
This was an important turning point — the moment when priorities shifted and mistakes started being made in terms of investment in and application of AI initiatives.
Automation is the only answer
At the corporate level, the pandemic crystalized the idea that AI was the key to future resiliency, success and reducing reliance on employees during a time when the labor market was at its tightest. At the end of 2020, eight in 10 business leaders interviewed by the WEF said they had already put extra resources into the automation of work processes to help those employees who had to adapt to remote working. However, 50% were also aiming to completely automate a number of jobs — rather than role-related tasks — within their organization. For 43% of organizations, the ultimate aim was to reduce their workforce through technology integration, compared with 34% that believed technology integration could actually create more roles at their firms.
Between 2021 and 2022, worldwide spending on AI grew 19.6% year-over-year to $432.8 billion. By the end of 2022; just 5% of organizations maintained the position that AI adoption would not benefit their business.
However, while this race toward AI was understandable in the circumstances, so was the certainty of its results. As the world moved towards 2023, it did so with a host of organizations that had overspent on a technology that had failed to deliver a genuine return on investment. But, as famed investor Charlie Munger said, “Show me the incentives, and I’ll show you the outcome.”
The wrong incentive
In the case of AI, the incentive was often an accelerated means of lowering costs and reducing headcounts to achieve short-term financial stability. Yes, AI can be applied in individual use cases or within a specific domain — a perfect example being the application of text and speech analytics within the contact center — but it can’t simply be plugged into one or any number of existing processes and start automating and delivering insights. Likewise, if the technology is being used on an ad-hoc basis rather than as part of a wider transformation, it’s impossible to unlock economies of scale. Instead, every new application needs to be developed from scratch to reflect the specific use case. And that, in turn, can quickly drive up rather than drive down costs.
An expectations reset
This difference between the perception of automation and the reality of implementation has led organizations to reset their AI expectations and, in many cases, realize that the technology’s greatest value is assisting and empowering employees rather than replacing them. In 2020, when asked, business leaders forecast that within five years, 47% of tasks would be automated. However, when asked again at the end of 2023, the consensus is that by 2027, just 42% of tasks will be automated.
But as well as damaging their finances, the race towards AI adoption has potentially dented the employee experience at many organizations. When roles rather than individual operations within those roles are being replaced by technology, those employees who are still needed can be left feeling as if they’re in limbo. How long will it be before their role can be automated, too?
Consumer concerns
For instance, when asked in 2021, 37% of Americans said they were more concerned than excited about AI and its role in their everyday personal and professional lives. And, since the rollout of generative AI, this negative sentiment has increased rather than diminished. Today, 52% of U.S. adults are more concerned than excited about AI and one in five genuinely believe it’s putting jobs at risk.
And it’s a similar story on the other side of the Atlantic where 32% of working U.K. adults think their job is at risk of being taken away by AI, and 52% of under-24s believe the existing pace of AI adoption means that their skills do not align with job opportunities and they won’t be able to take their first step on a career ladder.
Nevertheless, AI is already integral to business and will be a key driver of future success. Even the most conservative estimates forecast that the technology could raise global GDP by 7% and deliver year-on-year productivity gains of 1-2%.
But that success will depend on how you learn from recent history and use those lessons learned to avoid mistakes.
Involve employees in the process
Any investment in this technology needs to be clearly thought out and aligned with equally clear use cases and supported with an investment in the organization’s workforce. Employees need more than reassurance that their jobs aren’t on the line. They should be invested in the implementation process and your organization should provide upskilling and reskilling.
In their haste to counter the negative impacts of COVID, many organizations made the mistake of viewing AI as a means of digitizing and automating the world of work and over-invested as a result. Even if GenAI has raised the bar again in terms of capabilities, business leaders still need to use these technologies as a prism through which to see their business in terms of operations and domains that will benefit from automation and those that can only succeed through human endeavor and where there are opportunities to elevate that endeavor through digital means.
Learn more about our approach to using GenAI in getting ready for the future of work and the future of CX.