When generative AI exploded onto the tech scene in 2022, companies scrambled to adopt the “Next Big Thing.” Now, everyone from the smallest startups to the biggest banks and retailers wants to reap the benefits it has to offer.

GenAI promised a workforce revolution – let the computer take care of your busywork so you have time for more critical thinking. It sounds great on paper, a huge boost in productivity and revenue, but many organizations find themselves now struggling to make this their reality. The proliferation of generative AI tools has captured the imagination of consumers and companies alike, but have we overstated the actual impact of AI on innovation and business benefits?

For the past year, we’ve watched tech companies embark on a race for AI dominance: rushing to showcase new enterprise AI solutions, rebranding existing technology with an AI lens, and touting the business benefits of various AI tools. However, a new global study of 1,700 senior decision-makers finds that the promise of AI is being held back. Although they acknowledge that AI is expected to deliver high-impact value in product and service innovation, improve data availability, and reduce costs, they feel significant pressure to adopt AI quickly and worry about the potential failure of the AI bubble.

It’s clear that many organizations have been captivated by the shiny new toy that is generative AI, but they aren’t prioritizing the necessary aspects of development and infrastructure required to reap the rewards that were promised. Without these critical elements, organizations simply aren’t prepared to scale AI adoption across their business.

Where AI Adoption Is Now

Considering it’s the home of industry leaders like OpenAI, the AI “bubble” is most prominent in the U.S. – but, despite AI’s domineering presence, the country has fallen furthest behind in bridging the gap from AI hype to adoption. Across global markets, the study above reveals that France seems to be spearheading AI adoption, with over a third (36%) of organizations already having a clear AI strategy and perceivable results. On the other hand, those in North America were the least likely (21%) to have a clear AI strategy in place, citing ethical and security concerns as the main factors impacting their AI adoption and deployment progress.

From an industry perspective, organizations in Construction & Engineering are leading the way, with 31% having a clear AI strategy and perceivable results, compared to just under a quarter (24%) of those in the Aerospace & Defense sector who said the same. Strikingly, just 1% of organizations across all industries said nothing is slowing their progress in adopting and deploying AI, meaning 99% are facing a challenge that’s holding back AI innovation.

The delay from existing AI hype to impactful AI adoption comes down to a few key aspects: skillsets and resources, legacy tech impediments, and a lack of data readiness. AI is still so new that many organizations simply don’t have the skills needed to develop and operate AI tools. Furthermore, many industries are still using legacy tech that isn’t conducive to creating an AI-ready workforce. Digital transformation is still in progress at many companies, and they don’t yet have the modern, cloud-based architecture that is ideally suited for AI. 

Where to Go Next

As tech-forward companies continue to make breakthroughs in AI, the pressure is on for other industries to catch up. More than four in five (84%) decision-makers agree that the business at large holds high expectations for AI, noting the pressure to adopt AI quickly, but without a clear strategy.

For leaders struggling to articulate an AI strategy or move towards AI adoption, the first step in overcoming the hurdle is to identify the challenges they’re facing. The most common factors slowing progress differ depending on where a company is in its AI journey:

• For those with a clear AI strategy and perceivable results, data complexity is most likely to be slowing progress for AI adoption and deployment
• For those gathering proposals or those with only structured pilot projects, limited skills and expertise are most likely to be slowing progress for AI adoption and deployment
• For those in the research phase of the AI journey with uncontrolled tests taking place, concerns about ethics, safety, and security are most likely to be slowing progress for AI adoption and deployment 
• Finally, for those who do not have anything in motion yet or lack a coordinated approach, legacy-based tech is the biggest barrier to AI adoption and deployment progress

As long as businesses can take that first step, the promised land of increased productivity and more effective operational management is not far away. With the right combination of cloud, data, processes, and skills in place, AI can offer a slew of benefits, including proactive insight delivery to improve processes, increased personalization for customer experiences, anomaly detection, performance monitoring, asset management, and automation.

While it may take months, or even years, to progress from ideating a strategy to seeing the full impact of AI on business outcomes, it’s never too early to start strategizing. In fact, it’s imperative to start as early as possible to avoid being left behind. The good news is that we’re all figuring AI out together as the technology continues to develop. No one knows what the future of AI will look like exactly, but it can only become what we make of it now.