Change is constant, but one thing is certain: the hype cycle will capture attention and impact budgets, for better or worse. Artificial Intelligence (AI) is the latest concern for businesses, but it won't be the last. Additionally, AI is too broad a term to focus on, and while generative AI dominates many conversations, other forms of artificial intelligence, such as predictive analytics and robotic process automation (RPA), are already having a bigger impact.
Unlike other hot technologies these days (e.g., the metaverse), increased investment in AI has the real potential to realize an almost immediate ROI. But as with any trend, fad, or legitimate area for companies to focus on, there is a knowledge gap between myth and reality. This gap extends to leadership and can quickly lead to disillusionment with digital transformation. Also, category leaders will emerge from organizations that are able to extract the most value from AI.
What happens when the adoption of technologies like AI outpaces leaders' understanding of their potential, current uses, and potential harms? Let's consider how rushing into an AI-driven future without fully understanding it could impact your business, your employees, and your customers.
When Use Exceeds Understanding
While jumping on the bandwagon is nothing new, it still has a major impact on organizations that are investing heavily in what is primarily a new area of exploration: artificial intelligence-based technologies.
According to a CMSWire survey, by the second half of 2023, 60% of leaders believe AI and machine learning will have a significant impact. (Download required)The McKinsey survey goes even further, with 75% of respondents predicting generative AI will soon disrupt their industry.
IDC predicts AI spending will reach $150 billion in 2023 and surpass $300 billion by 2026. And McKinsey's global AI survey revealed that more than 65% of respondents said they use generative AI regularly, nearly doubling from the last survey 10 months ago.
It's clear that the AI hype is driving action, but the rush to adopt AI is exposing several gaps, including a lack of understanding.
Knowledge gaps
Despite all the recent hype, it seems that many companies don’t truly understand the potential opportunities and challenges of AI, let alone the basics of how these technologies work.
A survey of 5,000 consumers by Savanta and Pega found that while 93% claim to have a good understanding of AI and only 3% admitted to not knowing about generative AI, a significant knowledge gap still exists.
For example, even though AI has been around for decades, 80% of respondents believe their business has been using it for five years or less. Additionally, 65% could not properly define generative AI or explain how it works. This lack of understanding will be critical as companies rush to adopt AI without fully understanding its impact. Let's look at three areas where this is evident:
Premature investment leads to failure
The failure rate of digital transformation is well documented, and in general, this doesn't seem to be reduced by the introduction of AI: In the same Savanta survey, nearly two-thirds (61%) of respondents said they had failed to implement an AI-based tool.
Learn more: 67% of marketers say lack of training is the biggest barrier to AI adoption
And yet, a Deloitte survey found that 30% of executives cited the challenge of measuring and delivering business value in AI initiatives as one of their top three challenges. The most commonly cited challenge in that same survey was implementation.
The priorities are wrong
When adoption outpaces understanding, efforts and investments are spent in the wrong places. There are several valid reasons why business stakeholders have concerns about AI adoption, including ethical issues, how to treat human employees, and real-world long-term effectiveness.
In Savanta's survey, up to 42% of respondents are worried that AI will take over their jobs, a fear borne out by recent layoffs, and just over half (51%) are concerned about bias and transparency issues related to increased AI adoption.
These are all valid concerns, backed up by real-world examples and well-documented, but 40% of respondents in the same survey also worry about the possibility of AI-powered robots enslaving humanity.
And many companies are being asked to do more with less: Marketing budgets have steadily declined from about 11% of revenue in the years just before the pandemic, dropping from 9.1% in 2023 to 7.7% in 2024, according to Gartner's 2024 CMO Spending Survey.
When asked how they plan to address this, nearly two-thirds of respondents said they don't have the budget to implement a strategy in 2024, but are hopeful that generative AI can fill some of the gap. It's a big expectation for a technology that many don't fully understand. Savanta's research revealed that nearly half of respondents (47%) have concerns about entrusting their brand's success to AI.
Prioritizing can be difficult in an organization where many fear losing their jobs, doubt the effectiveness of AI, and worry about Terminator-like catastrophes. We'll have to wait and see how these concerns play out, but compromises are possible. With a widespread lack of understanding of the real-world benefits and drawbacks of AI, mistakes are inevitable. The success rate of current AI initiatives is a clear indication of this.
Customers lose out
Finally, if the race to adopt AI outstrips its understanding, end customers will also lose out. While we have yet to see a direct correlation between AI adoption and scores, it may come as a surprise that the recently released Forrester 2024 CX Index recorded its largest decrease (1.6%) from 2024 to 2023. Many factors influence these numbers, but given the lack of understanding of AI and the large number of failed investments, it is likely that customers will suffer from AI-related misunderstandings and mistakes.


Consumers aren't averse to using AI technology, but they expect these tools to provide benefits to the brands that adopt them, rather than simply cost savings: up to 80% of customers surveyed by Verint in 2023 believe they will see at least one benefit from interacting with an AI-powered chatbot.
The aim of greater use of AI in enterprises is to benefit customers through improved efficiency, speed and personalization. However, to realise these benefits, brands may need to experience more failures in their AI projects. More analysis is needed on the relative impact of AI on digital transformation success rates and declining customer satisfaction.
The silver lining: AI works if applied properly
Opportunities remain for brands that can combine understanding with successful implementation to achieve both internal operational improvements and external increases in customer satisfaction and loyalty.
Research shows that leveraging AI can improve both internal productivity and customer satisfaction. A 2020 study by McKinsey estimated that AI technology could add up to $1 trillion in value to businesses annually, especially in customer service. Recent findings from researchers at MIT and Stanford University have shown a 14% increase in internal team productivity and an increase in end-customer Net Promoter Score (NPS).
This potential paves the way for brands that can overcome challenges (some real, some hyped) and balance hype with careful adoption. Companies that can capitalize on the opportunity to adopt AI in meaningful and measurable ways in the coming months and years will be characterized by better education, more strategic thinking, and a customer-centric attitude.
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