Beyond the AI Hype: Plotting a Measured Course to Business Value

“Patience is bitter, but its fruit is sweet.” Aristotle

When electric cars first came out, many people were excited about them. Many people thought electric cars would get very popular right away because of all the hype.

But that did not happen. Electric cars took much longer to catch on with regular people than the early predictions said.

There were two big reasons regular people did not buy electric cars quickly:

1. Initially, electric cars were still too expensive for most average drivers.

2. There were not enough electric charging stations for people to plug in and recharge their electric car batteries.

Because of these issues with the high prices and not enough plug-in stations, electric cars did not sell well to regular consumers as fast as first expected. Instead of everyone switching fast, ordinary people started buying electric cars slowly over many more years, and the early hype did not match a slower reality.

"Rome wasn't built in one day"

Lots of companies today are very excited to add artificial intelligence (AI) tools to their businesses. This excitement can make sense because AI can improve companies’ operations if appropriately used. However, business leaders should realise that bringing in AI will take thoughtful planning over longer periods before it changes things.

Adopting AI cannot happen overnight if done carefully. This is similar to the story of electric cars, where the early hype did not match the challenging reality. With AI, too, companies need realistic views of the costs, employee training required, upgrading systems, and more.

The current situation around AI follows a similar path as electric cars. There is so much enthusiasm now about AI as there was about electric cars at first. However, companies’ executives should understand that adding AI has practical issues to solve, just like electric cars initially had issues that slowed adoption. Leaders should have realistic plans for integrating AI that allow enough time and budget to do it right. This will help make the benefits of AI last over the long term rather than fading after the initial hype dies down. There are no shortcuts if AI is to improve companies substantially.

Adding artificial intelligence (AI) into companies will take years of careful planning and slow integration before it changes how they operate. The example of electric cars shows that huge potential does not immediately translate into huge real-world impact. There are always practical challenges to work through first before big shifts can fully take hold.

When electric cars first came out, they faced issues like high sticker prices but insufficient charging stations, uncertainties about electrical grid capacity, how to dispose of used batteries, and more.

Companies today wanting to use AI should study the adoption curve of electric cars. Moving too fast with new technology often has unintended consequences. Instead, AI should be designed carefully around solving immediate business problems, not just flashy technological innovations.

Companies must learn to walk before they can run when bringing in innovations like AI. Finding specific issues that AI can help improve step-by-step is smarter than disrupting everything overnight with untested changes.

In addition to realistic expectations and patience, AI core producers should prioritise accessibility and fairness from the start. At first, electric cars were only affordable for wealthier consumers. This slowed mainstream adoption and made eco-friendly cars seem like a luxury item. Regardless of the reasons, average drivers felt excluded from electric cars for years due to high costs.

Similar stratification could happen with AI between technology “haves” and “have nots.” Giant corporations have huge budgets to build advanced AI systems. Meanwhile, smaller companies lack equivalent money to keep up. Without care, an AI divide could form, concentrating more power among dominant players, similar to early electric cars. Efforts must be made to make AI tools affordable over time so no businesses are left behind in digital changes because of old-fashioned barriers like size and status.

The bottom line is that while promising, AI requires careful management, which is not fully seen with the mixed results of electric vehicles. Patience, precision implementation aimed at fixing current issues, accessibility prioritised across the market, and ethical concerns are crucial for AI to have positive impacts rather than negative ones.

Promising innovations take time, especially seismic shifts like AI. Companies should gradually integrate AI tools to solve today’s problems while building a foundation to benefit tomorrow. With a sound strategy,[1] AI can empower both businesses and society. But unrealistic timetables help no one in the end. Moving carefully is better than rushing forward without thinking.