AI Hype vs. Reality: Consumer and Creator Attitudes Toward Smart Technology

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Click to learn more about author Rachel Roumeliotis.

The hype around artificial intelligence (AI) has grown significantly over the years. While the technology has been a major topic in the boardroom and a prominent headline in business and trade press, that’s only half of the equation. Let’s not forget, AI has been a pop culture and science fiction phenomenon too, and with that comes a warped sense of what it is, what it can deliver, and how it will impact our lives. One could argue that the futuristic depictions of AI have actually distracted consumers from how AI is already playing a vital part in their everyday lives.

As such, a recent O’Reilly survey set out to explore the disconnect between the consumer understanding of AI and how it’s actually being applied in production. More specifically, the findings highlight the opinions of AI consumers compared to “creators” – those working to develop AI-driven solutions, including CTOs, data scientists, software engineers, solutions architects, and IT directors. While we have a long way to go to bridge the gap between AI hype and reality, surprisingly, there are some strong areas of overlap between creators and consumers, suggesting a shared hope in the future of AI’s potential.  

For example, both groups appreciate the success of smart home technology and are watching the development of autonomous vehicles closely. But for creators working to incorporate AI technology into products and develop new ways to use it, robots and cars are not the primary focus. The areas of advancement instead look at AI that learns from our actions to more efficiently help us with our daily responsibilities. This includes functions such as automating once-manual processes, answering questions, and completing tasks through speech recognition and natural language processing (NLP).

Ultimately, it’s up to a wide range of individuals, including developers, marketers, product managers, and sales personnel, to ensure that AI is being used and understood correctly. For successful consumer AI adoption, developers should focus their efforts on leveraging AI to make consumers’ everyday lives easier, augmenting existing experiences to make them more seamless and exciting. A prime example of this is Netflix: Its AI-powered personalized recommendation engine algorithm is worth $1 billion a year. It’s not as awe-inspiring as a flying car, but it makes finding a new series to binge-watch an easy and enjoyable experience. 

Counter to how consumers have embraced smart applications from Google’s Nest to Amazon’s Ring, they are less enthused about how AI can help them at work. In fact, the aforementioned survey found that only 22% of workers desire automation to help with their workloads, and just 11% want help from AI to make business decisions. For creators, those numbers were slightly elevated – for instance, 28% desire AI to make business decisions – but as expected, their priorities lie in different areas. Creators believed AI would be most useful in software development and coding environments (45%) – processes not necessarily applicable to the wider workforce. 

While consumers may not be ready for AI in the workplace just yet, creators would be smart to expand their ideas of where the technology can be useful to encourage adoption for processes and teams outside their immediate jobs. There is great potential for AI tools that increase employee productivity and augment their workflows, and the numbers are there to back it up. According to Gartner, in 2021, the increase in AI usage across businesses will create $2.9 trillion of business value and 6.2 billion hours of worker productivity. These are significant contributions to our economy and workforce.

But to truly bridge the gap between consumer expectations and business value, there needs to be cohesion from the creators, to those with a moderate understanding of and interaction with AI, down to the end-users. AI engineers who work with deep learning and NLP and create the algorithms are thinking about machine learning in a code-centric, process-driven way. NLP is part of what makes Alexa work, while advances in computer vision enable Ring doorbells to turn on. When nontechnical stakeholders enter the mix, their focus is productization – how can we integrate AI into a given product and market it? For individuals, the AI piece is irrelevant – it’s about awesome features and ease of use.

As AI-enabled solutions and tools become more commonplace both at work and at home, it’s likely that perceptions will shift from the sci-fi connotations to the practical everyday applications of AI. However, only when the goals of creators and consumers align will we realize the true value of AI and smart technology. Ultimately, that balance is up to creators, as they continuously learn from consumer attitudes towards AI – whether they know they’re using it or not. 

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