AI Challenges: Are Your AI Plans Based on Sand

AI Challenges: Are Your AI Plans Based on Sand

We are at the height of AI euphoria, powered mostly by the fast adoption of generative AI in both the consumer and corporate sectors. However, the excitement only sometimes equals comprehension, as demonstrated by a survey of more than 500 corporate decision-makers from various organizations worldwide done by research company Savanta for Pega.

The majority of those polled (82%) believe that AI adoption and usage will account for up to half of their higher revenues in the next three years. Building on this, a larger majority (93%) claim to grasp what AI is and how it works, but only 35% can offer an appropriate explanation of generative AI. The risk of a knowledge gap between the reality of AI and possible AI applications and advantages only harms companies that profit from its strategic adoption.

Let’s look at a few examples of how the gap between AI understanding and possible applications affects the organization. We’ll look at various AI issues resulting from this knowledge gap and lost possibilities. 

Challenge: 1 Overconfidence in Understanding Solutions

This gap between anticipated knowledge and real comprehension can lead to overconfidence in possible outcomes and a “silver bullet” solution to long-term issues. We’ve been down this road before with other technologies (remember the metaverse, anyone?), so those in charge of long-term strategies must understand that there are potential AI applications, as well as the various types of artificial intelligence that can be leveraged in the enterprise, such as predictive analytics, automation, robotic process automation (RPA), and, yes, generative AI.

According to the study’s profit estimates, this AI challenge overconfidence may result in failed expectations. I’ve stated repeatedly that AI is neither a goal nor a tactic. It is vital to understand where AI fits in and where it might not. With 85% of survey respondents spending up to half of their yearly IT budget on AI solutions, businesses cannot afford to waste time (or money) on bad judgments and investments.

Challenge: 2. Assumption of the Best Solution

Another AI difficulty posed by the AI knowledge gap is the inaccurate scoping of an AI solution that marketers will confront in the coming months. For example, without the capacity to correctly describe generative AI, it is difficult to offer the greatest directional counsel on what the best answer to an AI problem would be.

It appears that many in the organization are aware of this on some level, but the AI hype may be too great. More than three-quarters (77%) of respondents admit to wasting money in their budgets (almost half of which is spent on AI) owing to a lack of a sufficient plan.

The writing is already on the wall here. The knowledge gap translates into a strategy gap, and more AI education is required to match the proper fit solutions to the relevant AI issues or AI opportunities.

Challenge: 3. Missed Opportunities

Another AI difficulty brought about by this knowledge gap is being sidetracked by the hype and missing out on real ways AI may improve how marketing teams in the organization function.

For example, generative AI is frequently thought of as a means of creating text- and image-based content (and increasingly video). However, one of the most ignored areas where it may assist marketers and many others inside the company is in the execution of tasks. Marketing operations may use generative AI to simplify steps in developing content and campaigns in ways that go beyond delivering a single prompt for assistance with writing a blog post.

Also, combining different forms of AI can produce disruptive outcomes. Using predictive analytics with generative AI, for example, allows you to combine propensity models and generative AI to generate content and experiences that are specifically tailored to your best and most valued clients.

Combining multiple forms of AI solutions necessitates a more sophisticated understanding of artificial intelligence so that these applications may be used to discover the appropriate tool for the task at hand. Simply said, CEOs and leaders who believe that using AI to tackle a single problem will lose out on greater and more substantial benefits.

So, what is the solution? There are numerous potential solutions to this knowledge gap, but the most obvious is increased education about not only where potential hype may be creating unrealistic expectations, but also where the true potential for gains may be obscured by shiny objects that make good headlines but do not translate into real results.

AI is not all hype. However, it is easy to become diverted by the hype and overlook certain significant AI potential that organizations may use to revolutionize the way they work. With deeper knowledge of the various ways that AI may assist corporate marketing, we can go beyond some flashy items to get more practical benefits.

Source- cmswire

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