The paradox of AI: problem vs. opportunity in web innovation
AI has dominated headlines, product strategies, and investment for the past two years, but as businesses reflect heading into 2025, an uncomfortable question lingers: where is AI’s financial impact, really?
Amidst the AI hype climate, businesses have been eager to invest in emerging technologies that promise the world. So eager, in fact, that the market is now saturated with hastily-developed products designed more to showcase adoption than to deliver measurable impact.
While AI tools have existed for some time, the rise of generative AI — starting with the release of ChatGPT just over two years ago — has captured broader attention and rekindled a frenzy of innovation, akin to the dot-com boom of the late 1990s. Generative AI’s accessibility is lowering barriers to entry, sparking both a rush to investment and concern across industries.
When applied strategically, it’s clear that AI can revolutionize user experiences at places like websites, where the potential for customer experience enhancement is unparalleled. But to keep up with lofty AI predictions and heavy investor demands, many businesses today are investing first and looking for ways to measure return on that investment later — an approach that’s led to over-promised and under-delivered initiatives, followed by disappointment among customers and teams alike.
AI has the potential to deliver transformative outcomes when businesses align it with strategic goals, such as improving website functionality and user satisfaction. Rather than integrating AI first and looking for a problem to solve later, it’s time to return to the tried and true formula for innovation: find a problem, figure out how to solve it.
SVP and CTO at WP Engine.
The AI Paradox: ROI vs. FOMO
ROI must be the central factor in AI investment decision-making.
While the number of senior business leaders investing $10 million or more in AI is set to double next year, a Gartner report found that at least 30% of AI projects will be abandoned by the end of 2025. These circumstances — high costs and low success rates — make prioritizing business needs and ROI critical.
AI is an expensive, time consuming endeavor — so in order for an AI product to be worth it, especially in consumer-facing applications, it must add real value to customers. Rushing to bring high-potential technology to market can often hinder, rather than enhance, user experience — particularly in the case of websites, where users increasingly demand seamless interaction.
The early surge of businesses racing to adopt AI chatbots is a prime example. In the push to get the latest feature onto their websites, a critical question was often overlooked: will this actually improve our customer service? Despite their high-potential, chatbots were introduced widely before the technology was developed to the point of adding proper value, often resulting in frustrating user experiences and failing to provide accessible support.
Consider Watsonville Chevy’s viral failure, where a chatbot offered to sell a customer a brand new Chevy vehicle for only $1. Rather than helping customers buy cars, the under-developed technology — despite its high-potential — caused an embarrassing headache for the dealership. More than the technology itself, this failure underscores the critical importance of businesses putting appropriate guardrails in place. Effective AI implementation requires not only understanding the potential of off-the-shelf solutions, but ensuring they are adapted to the specific needs and limitations of the business environment.
In another recent counterproductive AI use case, Spotify whiffed on its perennially popular Wrapped feature by going all-in on AI. While removing features like top genres, the music streaming giant opted to add experiences like an AI-generated podcast. Listeners, predictably, were critical, highlighting the importance of using AI to enhance user experience rather than diminishing features that made products popular in the first place.
Businesses must ask themselves: is this AI use case truly adding to the customer experience? Investments must prioritize functionality and customer needs over hype. By focusing on thoughtful, ROI-driven AI adoption, businesses can avoid costly mistakes and improve outcomes.
Solving Problems, Driving Results
But of course, not every AI investment is destined to fail or hinder customer experience. There are many examples of how AI brings clear value-adds when implemented strategically, especially in ecommerce and content.
In a crowded online environment, frustrated users are a sales killer — customers have access to limitless products and content online, so when their search fails to draw results, they leave.
Netflix, Google and Amazon have all dominated their respective verticals for several years in no small part because of their use of natural language processing. In 2017, more than 80% of the TV shows users watched on Netflix were discovered through its recommendation system. In 2012, 35% of purchases on Amazon came from product recommendations. Google has utilized AI since 2015 to process and provide more relevant search results.
All of these use cases have had a tangible impact on customer experiences — an impact that has long differentiated them from competitors with less resources.
More recently, the rise of generative AI is amplifying this trend — as the current AI frenzy has led to not only the development of cutting-edge technology by major AI players, but also made it more accessible for businesses of all sizes. These advancements enable even mid-market players to leverage tools once exclusive to industry giants, creating new opportunities for differentiation and growth.
In short, these technologies are no longer limited to just big tech like FAANG — AI democratization is unlocking more cost effective tools for SMBs and mid-market companies to optimize their websites. The potential of AI is immense when businesses choose the right product, and legacy examples in e-commerce and user experience, like Netflix’s recommendation engine or Amazon’s personalized shopping, offer a blueprint for websites leveraging AI to create transformative, ROI-driven outcomes. AI-driven smart search and recommendation technologies already exist; businesses just need to evaluate problems and responsibly implement solutions to unlock AI’s transformative potential.
Starting with the pain point — such as low conversion rates — and answering with AI empowers better business outcomes. Implementing AI technologies can help bridge the gap between mid-market companies and enterprises, drive higher conversion rates and justifiable ROI for the cost of AI.
Thoughtful AI integration has the potential to revolutionize industries, and in some cases, already has. These use cases underscore AI’s potential to add real value, making a tangible impact on conversion rates and customer experience.
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AI has dominated headlines, product strategies, and investment for the past two years, but as businesses reflect heading into 2025, an uncomfortable question lingers: where is AI’s financial impact, really? Amidst the AI hype climate, businesses have been eager to invest in emerging technologies that promise the world. So eager,…
