Why Brands Should Overcome the Knowledge Gap in AI Adoption

AI hype is driving fast adoption, but what happens when knowledge falls behind?

Change is continuous, but one thing is certain: hype cycles attract attention and impact budgets, for better or worse.

AI is the current workplace obsession, but it won’t be the last. Also, AI is too wide a topic to focus on, with generative AI taking up a lot of space in discussions while other kinds of artificial intelligence, such as predictive analytics and robotic process automation (RPA), have a greater existing footprint.

Unlike other highly advertised technologies (such as the metaverse), larger AI investments offer a genuine and immediate potential for ROI. However, like with every trend, fad, or genuine sector in which business organizations should invest, there is a knowledge gap between myth and fact. This divide starts with leadership and can swiftly add to dissatisfaction with digital change. It also develops category leaders from organizations that maximize the benefits of AI.

What happens when leaders’ grasp of a technology, such as artificial intelligence, outpaces their understanding of its potential, present use, and possible harm? Let’s look at how racing towards an AI-powered future without properly comprehending the implications for organizations, employees, and customers.

When Usage Exceeds Knowledge

While hopping on the technology train is nothing new, organizations that make major investments in artificial intelligence-based technologies, which are mostly new areas of investigation, face severe consequences. 

According to a CMSWire poll, 60% of CEOs believe AI and machine learning will have a significant influence by late 2023. According to a McKinsey survey, 75% of respondents expect generative AI will soon disrupt their business.

IDC anticipated that AI spending will reach $150 billion in 2023, with forecasts of exceeding $300 billion by 2026. According to McKinsey’s Global poll on AI, more than 65% of respondents utilize generative AI regularly, substantially tripling from the last poll ten months ago.

It is evident that the AI hype is driving action, but the rush to adopt it is exposing multiple flaws, beginning with a need for more awareness.

The Knowledge Gap

Despite the current excitement, only some organizations fully understand the potential clients and problems of artificial intelligence, let alone the fundamentals of how these technologies function. 

Savanta and Pega researched 5,000 customers and discovered that, while 93% claimed to understand AI well and only 3% acknowledged not knowing anything about generative AI, there are still considerable knowledge gaps.

For example, 80% of respondents believed that AI has only been utilized in business for five years or fewer, even though technology has been around for decades. Also, 65% of respondents were unable to accurately define or understand generative AI. This lack of awareness is essential when businesses hurry to implement AI without fully understanding its implications. 

Let’s look at three examples where this is clear.

1. Premature Investments Result in Failing Efforts

There is much documentation on the failure rate of digital conversions. In general, the introduction of AI does not appear to have reduced the failure rate. According to the same Savanta poll, nearly two-thirds (61%) of respondents had experienced a disastrous adoption of AI-based technologies. 

2. Improper Priorities are Created

When adoption outpaces comprehension, efforts, and investments are directed in the wrong direction. There are valid reasons for company executives to be concerned about AI adoption, including ethical difficulties, how human employees are treated, and the actual long-term efficacy, to name a few. 

According to the Savanta study, up to 42% of respondents are concerned about AI stealing their employment, which is backed up by recent layoffs. A bit more than half (51%) are concerned about bias and transparency issues with greater AI deployment. 

All of these are serious issues, supported by real-world instances and well-documented. However, 40% of respondents to the same study are concerned about the future enslavement of mankind by AI-powered robots. 

Many people are being expected to accomplish more with less. According to Gartner’s 2024 CMO Spend Survey, marketing expenditures will be 7.7% of sales in 2024, down from 9.1% in 2023, and down from over 11% of revenue in the years leading up to the pandemic.

When asked how they plan to deal with this, over two-thirds of respondents responded that, despite a lack of funding to carry out their goals in 2024, they are optimistic that generative AI would fill some of the gaps. That is a lot of optimism for a technology that many people do not appear to completely comprehend, as the Savanta study found that almost half of respondents (47%) are apprehensive about entrusting their brand’s success to AI.

Setting priorities can be difficult in an organization when many individuals are afraid about losing their jobs, questioning AI’s effectiveness, and anticipating a Terminator-style Armageddon. We’ll have to wait and see how these worries shake out, but concessions are expected. Mistakes are unavoidable owing to a widespread misunderstanding of AI’s real-world advantages and downsides. The present success rate of AI programs demonstrates this.

3. The Client Loses

Finally, when the adoption race outpaces knowledge of AI, the end user loses. While a clear association between AI usage and scores has yet to be established, it is not surprising that Forrester’s newly revealed 2024 CX Index had its largest fall (1.6%) between 2024 and 2023. Many factors can influence these figures, but given a lack of understanding of AI and numerous unsuccessful investments, customers are likely to suffer from AI-related misconceptions and blunders.

Consumers are open to using AI technology, but they expect these tools to provide benefits to the companies that use them, not just cost savings. Verint studied up to 80% of consumers in 2023, and they expect interactions with an AI-powered chatbot to provide at least one advantage. 

The objective of increasing the use of AI in organizations is to increase efficiency, speed, and personalization, all of which benefit customers. However, to reap these benefits, companies may have to face more failures in their AI efforts. More research should be conducted on AI’s relative influence on the success rate of digital transformations and the decline in customer satisfaction. 

The Silver Lining: AI Works When Applied Properly

Brands that can combine insight with successful execution may enhance their operations both internally and externally, resulting in more pleased and loyal consumers.

Based on research, using AI increases both internal efficiency and consumer happiness. According to a McKinsey 2020 report, AI technologies have the potential to add up to $1 trillion to organizations’ annual value, notably in customer service. More recent study results from researchers at MIT and Stanford demonstrate that internal teams’ productivity increased by 14%, as did their Net Promoter Score (NPS) with end consumers.

Having this potential, the door is open for companies that can overcome the barriers some genuine, others overblown, and strike a balance between enthusiasm and measured uptake. Better education, more strategic thinking, and a customer-centric approach will distinguish those companies that can seize the chance to implement AI in a meaningful and identifiable way in the next months and years.

Source- Martech