According to IDC, 67% of CIOs report that the “accelerating arrival of new technologies” such as artificial intelligence (AI) is causing a serious skills shortage, which is hindering their customer experience transformation efforts. This is leading to a range of issues, including product development delays, product and service quality issues, customer satisfaction problems, difficulty reaching revenue targets, and revenue loss. Furthermore, IDC states that this figure is expected to rise to over 90% of organizations by the end of 2026.

However, talent shortages in the face of new technological developments are not new.

For example, over a decade ago, in the midst of the big data and analytics explosion, firms faced similar challenges.

Speaking to Vivek Jetley of EXL, back then, he estimated that the gap between the supply and demand of data scientists and analysts – people who can do advanced analytical and statistical work – was around 300,000-400,000 people in the US and UK alone.

However, he went on to suggest that hiring data scientists and analysts wasn’t the biggest talent issue that brands were facing. He believed that the bigger issue lay with leadership and its ability to guide, interpret and act on the insights produced by data teams. At the time, Jetley estimated that this gap was three to four times the size of the gap for data scientists and analysts.

I’ve been wondering about this leadership skills gap over the past few weeks, particularly in the face of flatlining customer experience results and the potential of new AI-driven technologies. As a result, I have been questioning whether a similar leadership skills gap related to AI expertise is emerging, and how that might be affecting companies’ ability to innovate and improve customer outcomes.

I say this because I’ve recently heard a number of stories that call into question the level of understanding some leaders have about this new technology, how it can impact their businesses, and what it takes to implement it effectively.

Here are two examples that illustrate how this leadership gap is being played out in practice.

The first story involves a marketing director who, at a quarterly board meeting, was urged by a board member to implement an AI-powered chatbot. The marketing director was slightly taken aback by this suggestion but replied that he would consider the board member’s proposal. At the next quarterly board meeting, the marketing director provided an overview of what had happened in the previous quarter and their plans for the upcoming quarter. Unfortunately, however, he also had to report that they had faced some unexpected challenges over the previous quarter, which caused them to just miss their targets. Upon hearing this, the aforementioned board director piped up and asked whether that would have happened if they had a chatbot in place.

This type of comment, I believe, reflects a broader pattern where many senior leaders are treating this new technology as a panacea for all ills. Moreover, comments like these suggest that many leaders do not fully understand the potential of this new technology and where it can be most effectively deployed.

The second story involves a customer service operations director who faced pressure from their leadership and board of directors to leverage AI self-service and agent-assist technologies to help drive improvements in service outcomes and productivity.

However, to do that would require the redeployment of agent resources from frontline customer service operations to design, train, test, manage, and monitor these new tools.

Consequently, this would have jeopardised their ability to meet their existing KPIs and service-level agreements (SLAs), putting not only their own performance at risk but also the rewards that agents would have received if they had met their targets. As a result, the customer service operations director decided to do nothing until they received the budget and additional resources required to undertake this new work.

The problem highlighted here is that the leadership and board of this brand hadn’t grasped the idea that the explosion of AI-powered software solutions is fundamentally changing the nature of enterprise software.

Traditionally, the responsibility for maintaining enterprise software systems rested largely with the vendor. However, with the rise of AI-powered software, responsibility has shifted from being solely on the vendor to being shared between them and their enterprise customers. As a result, the customer now undertakes significantly more work than they would have previously done.

Yes, you can work with suppliers and vendors and lean heavily on them to help set up, develop and manage new systems. However, unless you are completely outsourcing the ongoing management and development of this technology, it will require new skills and additional resources to optimize its benefits.

Now, I understand that leaders want to harness the power and potential of this new technology as quickly as possible, often fearing that if they do not, they will be left behind. However, recommending that a particular technology be adopted without properly understanding how it works, where it is best deployed or what is needed to make it work can, at best, be distracting and, at worst, potentially damaging to a brand.

Consequently, it is no longer sufficient for leaders and board members to have only a superficial understanding of new technology. Nowadays, and increasingly so, leaders and boards must become fluent in the language and practical aspects of AI.

To achieve this, leaders and their boards need to continually equip themselves with the knowledge required not only to transform their current business by leveraging existing technology, but also to stay abreast of technological developments. This way, they can be better prepared to reimagine what their business and the customer experience they would like to deliver to their customers could look like in the future.

This article was originally published on Forbes.com.

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