Article
6 min read
Gavin Jackson
  • SVP, Data and AI

Not every challenge is an AI problem. 

 

Indeed, AI’s potential is hugely exciting, combining generative and traditional AI capabilities together tobridge the gap between language and numbers that has so often been lacking in business. Yet, while the allure of AI's transformative potential is undeniable, there’s a hidden danger lurking in its deployment.  

 

Far too often, businesses fall into the trap of applying AI to the wrong problem, leading to wasted resources, missed opportunities, and even financial losses. Before jumping headfirst into AI, business leaders must pause and ask: Are we solving the right problem with AI? The cost of not doing so could be far more significant than anticipated.  Papers range from 50% to a whopping 90% of data and AI projects failing to deliver on expected benefits.  

 

Understanding the problem

 

At the heart of AI's promise is its ability to solve complex problems that are too time-consuming or intricate for humans to manage effectively. But before AI can deliver its magic, businesses must clearly identify what the right problem is. The truth is thatmany organisations don’t. Instead, they chase the latest technology development, fall victim to misunderstanding their core challenges, or allow excitement over AI’s potential to lead them astray.  

 

One of the most common pitfalls is focusing on the latest technology release or hype instead of the strategic objectives. With the daily buzz of new capabilities entering the market, many executives are under pressure to demonstrate action by delivering AI projects. As a result, easy-to-implement projects, such as simple chatbots, are taking priority over more strategic endeavors. This isn’t to say that a well-implemented customer support tool isn't the right investment; rather, the key question is: how do you know?  

 

Another frequent issue arises when businesses lack a clear focus on the problem they want to solve with AI. Without the proper domain expertise and clarity around what’s truly causing inefficiencies or lost opportunities, companies may invest heavily in AI solutions that address symptoms, not root causes. In many cases, this stems from a lack of collaboration between technology and business teams, which can lead to a misalignment between the business goals and appropriate technology solutions. 

 

The costs of solving the wrong problem 

 

When AI is used to tackle the wrong problems, the consequences can be severe. Often invisible at first, but the costs can quickly accumulate, affecting both the bottom line and an organisation’s ability to innovate over a sustained period. 
 

Implementing AI is not cheap. It requires significant investments in infrastructure, talent and technology. According to estimates, AI projects can cost anywhere from $500,000 to over $10 million, depending on their scope and complexity. When AI is applied to the wrong problem, these investments quickly turn into sunk costs. Even worse, businesses may double down on these efforts, funnelling more resources into a flawed project in hopes of salvaging the initial investment. This phenomenon often called the sunk cost fallacy, can lead companies further away from achieving meaningful results.  

 

Perhaps even more damaging than the direct financial hit is the opportunity cost of focusing on the wrong problem. AI, when properly applied, can unlock tremendous value and open new avenues for growth. By diverting attention and resources to less impactful areas, businesses forgo these opportunities. Competitors who are more strategic in their AI application will likely pull ahead, gaining market share, improving customer loyalty, and optimising operations in ways that slow-moving organisations won’t keep pace with. 

 

Misapplied AI can also lead to reputational harm. Consider the recent negative press around AI-driven hiring systems that inadvertently introduced bias into recruitment processes. Businesses that mishandle AI implementation not only risk public backlash but also create internal dissatisfaction. This can erode trust and enthusiasm across teams, stifling innovation and damaging company culture.  It is also worth asking which decisions are right to be automated and which are not.  Choosing incorrectly could lead to an erosion of your key differentiators. 

 

Three steps to ensure you’re addressing the right challenge  

 

So, how do businesses avoid these costly mistakes and ensure they’re using AI to solve the right problems? It all begins with strategic alignment and a clear understanding of AI's potential and the company’s own goals. 

 

  1. 1. Focus on business objectives first 
    Before jumping into any AI implementation, executives must first define what success looks like. What are the key business challenges, and how can AI be used to address them in a meaningful way? Whether it’s improving operational efficiency, increasing customer engagement or innovating new product lines, the business problem must drive the AI strategy – not the other way around.  It’s never too late to undertake this exercise to ensure your investments are on track.
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  3. 2. Foster cross-functional collaboration 
    Successful AI initiatives require collaboration between IT, data science teams and business leaders. By working together, these teams can ensure that AI projects are both technically feasible and aligned with business objectives. IT professionals and AI specialists should help business leaders understand what AI can and can’t do while business leaders provide the context and insights needed to identify the right problems.  Endava recently launched Morpheus, a framework for implementing autonomous AI agents at the enterprise scale. A key part of this framework is a process mapping exercise to ensure a full alignment between business outcomes and technology implementation.
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  5. 3. Start small, think big 
    While the temptation to chase big, flashy AI projects is strong, businesses should start with smaller, well-defined pilots. This allows them to learn, iterate and course-correct quickly. Over time, successful pilots can be scaled to address larger, more complex challenges that deliver long-term value.  If this is a challenge for your business, Endava has developed a prioritisation tool to ensure that your path to successful AI delivery is clearly laid out.
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Take a step back and reflect 

 

AI offers boundless opportunities to those willing to invest the time in exploring the type of organisation they want to be, the customer relationships they want to foster and theoperations they wish to run. 

 

The key to success lies in identifying the right problems to solve. By avoiding the temptation to focus on the latest technology hype, fostering collaboration across departments and aligning AI efforts with core business objectives, companies can unlock AI's true potential. The alternative of solving the wrong problem – could lead to wasted resources, missed opportunities and ultimately, an erosion of competitive advantage. 

 

It’s time for businesses to take a step back, reflect and ensure that their AI strategy is built on the foundation of solving the right problem. In the race to adopt AI, this critical step could make all the difference between success and costly failure.

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