Wait and See: Where AI is missing the mark to solve problems in the business world
Businesses feel the pressure to implement AI into their business, but many are worried that it won’t live up to the hype about its tangible business impacts
Written by: Anne T. Griffin, Founder & Principal Consultant - Eighth Ave AI, and Dr. Denise Turley, Business and AI Leader
These days, everyone feels behind on AI, especially in business. Reading the latest headlines, many business leaders get the impression that every business has already adopted AI and is integrating with it or launching innovative products that leverage it. How could it be that they are the very last leaders to get on the AI train? Is there something everyone else understands that they don’t?
The reality is that hundreds of thousands of businesses are still figuring it out. Many are being sold solutions that seem too good to be true or truly show they don’t understand their businesses or customers. This has led to a “wait and see” approach by many business leaders, and understandably.
Recently, McDonald's decided to remove the AI technology from its drive-through because it added hundreds of dollars worth of McNuggets to orders and things like butter or bacon ice cream. Businesses like McDonald's are built on efficiency and the more mishaps and misunderstandings that happen because of the AI, the more it slows down ordering, creating more friction. This can translate to longer times, less revenue, and potential customer churn. This underlines the importance of AI companies understanding the core needs and principles of the businesses they serve. While AI has undeniably cool applications, many companies need innovative solutions that understand their business and may seem “boring” on the outside.
Suppose a large, successful company like McDonald's needs help with implementing customer-facing AI experiments. What are businesses that don’t have the stomach or budget for that kind of margin of error supposed to do? Overall, they are looking for guidance that doesn’t feel like magical thinking. At a high level, business leaders need to understand what problems in their business they can solve today that they couldn’t solve before AI. Secondly, it’s crucial to know how the AI solution being considered aligns with the principles of the business. In the McDonald's example, they need a certain level of accuracy so that inaccuracy doesn’t interfere with efficiency. That efficiency is a core part of what McDonald's customers have come to know and expect from the brand. Because the AI solution used in their drive-throughs in about 100 restaurants uses generative AI, that type of AI predicts the next word in a sentence and isn’t wholly constrained to a narrow set of products and quantities, such as a McDonald's menu. There are solutions for generative AI to lower the probability of making up menu items or adding way too many nuggets. Still, sometimes, the technology is not accurate enough for the level of fidelity needed or too expensive to get to that level of fidelity at scale.
Additionally, there are many other considerations businesses need to make. One is data quality. Some of this is related to how data is formatted, the completeness of the data, and how it’s stored. This impacts how AI-ready a company is. Thinking about data as part of a profit center and not seeing it as an IT cost center is a key mindset change. Also, the quantity of data matters depending on the type of AI solution being proposed.
Time to value is also a consideration, but if your business hasn’t been using any type of AI in recent years, AI needs to be looked at as a long-term game. To do it well and add meaningful value, many infrastructure and cultural changes will likely need to be needed. This could mean that a quick and effective solution in one business could take more time in another, depending on several factors. But you'll fall behind tomorrow if you don’t start planning for it.
Monica H. Kang, Founder & CEO of InnovatorsBox, a leadership development and executive coaching business, shared that while she is excited about AI and its adoption in her industry, she doesn't want to rush and create something that may bring only short-term value. "AI is changing rapidly, as are our customers' needs. A good product should be able to cater for that future, and I envision waiting sometimes for the tech to evolve is a better solution than rushing to work with a capability that isn't ready for the full AI adoption and impact that I want to create."
To have that impact that will wow customers, the organization must be aligned on key shifts required to launch successful AI-powered tools, products, and experiences. Organizational change is a significant consideration. What roles need to be added, and does it make sense to keep them full-time or hire them as consultants? What roles might be needed less in the future, and can you upskill those in those roles now to shift to more different-skilled roles? How can businesses shift the mindset of their most critical decision-makers, leading to decisions that help the organization succeed in the era of AI and not be left behind like Blockbuster in the battle against Netflix? Each organization will address these differently, and each of these considerations needs to be addressed very intentionally.
Another big consideration is the cost. Many of these solutions talk about saving organizations money, but the reality is that how much it costs up front to create these cost-saving solutions depends on how AI-ready the organization already is, what type of solution it needs, and what technology is actually powering it.
Above all else, many organizations are looking for a blueprint to show them what success looks like and how to measure it with AI solutions. Seeing a vision for their business and industry's future and where their competitors are with AI would make them feel more confident about moving forward with the time and investment needed to integrate AI into their business. Most organizations care more about how this will impact their bottom line. They want to avoid throwing money away on failed AI initiatives or, at worst, being a viral cautionary tale of AI gone wrong.
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This article is the first in a series between Anne T. Griffin of Eighth Ave AI and Dr. Denise Turley on the realities of businesses considering and implementing AI.