A global survey of 1,200 IT, business and public sector decision-makers working in organizations that generate $250 million in annual revenue finds that while 59% are of positive dispositions toward artificial intelligence, only 37% report they are fully prepared to implement it.
Conducted by the market research firm Coleman Parkes on behalf of Riverbed, the survey shows 42% of respondents identifying a lack of high-quality internal data as what’s preventing them from investing more in AI, and more than three quarters (76%) said they lack confidence in synthetic data as an alternative.
Additionally, the same percentage of respondents are concerned that the training of AI models might result in proprietary data finding its way into the public domain.
The survey makes it apparent that despite a high level of enthusiasm, the average enterprise IT organization is not prepared to fully operationalize generative AI, says Riverbed CEO Dave Donatelli. “We’re seeing a typical technology adoption cycle,” says Donatelli. “Everyone gets excited and then reality sets in.”
Those challenges span everything from data management issues to the amount and types of IT infrastructure required, he adds. In many cases, there are also data gravity issues that need to be addressed. Organizations will need to decide whether to move data or bring compute resources to where data already resides, notes Donatelli.
Organizations will need to be able to observe how individual AI models are performing over time, but most organizations lack the platforms needed to effectively manage AI.
Finally, organizations will need to work through a host of cultural issues involving which departments in organizations actually control that data, he adds.
Despite all these issues, 52% of respondents said their use of AI is slightly ahead of the competition, while another 30% said their use of AI is significantly ahead of their peers. A full 91% also admitted they are concerned their competitors will have an advantage if they fall behind on implementing AI. Organizations, on average, have already spent $14.7 million on AI initiatives, including $8.5 million on IT services specifically, the survey finds.
More than half of respondents (54%) said the primary reason for implementing AI is to drive operational efficiencies, compared to 46% that cited growth. However, by 2027 the percentage of respondents that expect to be using AI to drive growth rises to 58%, compared to those focusing primarily on operational efficiency (42%).
Overall, 65% said they are at the stage of accelerating their AI use, and 86% expect to be fully prepared to implement AI by 2027. Just under a quarter (23%) said AI is fully integrated into business processes and drives strategic decision making across the organization.
In fact, 66% said AI is a strategic priority, with 57% having created a dedicated AI team. A full 94% said AI remains a key focus for the business leaders, with adoption being driven from the top of the organization. However, nearly a quarter (23%) underperformed compared to only 18% exceeded expectations.
It’s clearly still early days as far as adoption of AI is concerned, but it’s apparent much work still needs to be done. The issue now is maintaining the current level of enthusiasm as AI projects become simultaneously more ambitious and challenging to successfully implement.
