5 Biggest Barriers for AI Adoption

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AI adoption barriers

Overwhelming energy requirements and sustainability concerns are among some of the biggest barriers for AI adoption, according to new research from Pure Storage. 

The report, released in partnership with Wakefield Research, reveals the importance of reassessing data infrastructure to truly reap the benefits of AI, keep energy costs in line, and stay on track with corporate environmental goals.

Why might companies be reluctant to adopt AI?

Numerous companies in the United Kingdom express hesitancy when it comes to embracing artificial intelligence (AI), citing various concerns.

A primary barrier for AI adoption is the associated costs, covering both the initial investment and the continuous maintenance required for AI systems. This financial burden can be particularly daunting for small and medium-sized enterprises (SMEs), limiting their capacity to allocate resources for the seamless integration of AI.

Furthermore, a notable obstacle lies in the insufficient understanding among business leaders regarding the intricacies and potential benefits of AI within their specific industries. This lack of awareness or knowledge can impede decision-making processes concerning the adoption of AI technologies.

Additionally, companies may harbour reservations regarding data privacy and security, given that the implementation of AI frequently involves the collection and analysis of significant volumes of sensitive information.

In today’s Emerge5, we’ll be highlighting some of the key takeaways from Pure Storage's report.

The Need for Computing Power is Surging, Driven by AI Adoption

In the rapidly evolving landscape of artificial intelligence (AI) adoption, a staggering 88% of entities embracing this transformative technology find themselves grappling with an unprecedented surge in the demand for computing power. This surge is indicative of the profound impact that AI has on computational resources, underlining the imperative for organizations to fortify their technological infrastructure.

Organisations Did Not Anticipate the Energy Demands of AI

73% of IT buyers were not completely prepared for the energy requirements of AI. The unanticipated energy demands posed by AI technologies constitute a critical aspect of the implementation process, catching a significant majority of IT buyers off guard. This lack of preparedness sheds light on the complexity inherent in aligning existing infrastructures with the energy-intensive nature of AI algorithms and computations.

Energy Consumption is Just One AI Burden

For 73%, AI requires or will require data management upgrades of some kind. Among specific upgrades: data management tools (48%), data management processes (46%), and data storage infrastructure (46%).

As a Result, Nearly All (96%) Have Already or Plan to Update Their IT Infrastructure

29% of IT Buyers say AI has or will require a complete overhaul. The necessity for a complete overhaul in response to AI integration arises from the unique challenges and opportunities that AI brings to the forefront. Unlike incremental upgrades or minor adjustments, AI often necessitates a holistic reimagining of organizational processes, workflows, and underlying technologies.

These Challenges Have Set Back Businesses’ Sustainability Goals

89% have found ESG goals more difficult to meet as a result of upgrades to their IT infrastructure after AI adoption. However, 60% of those who have already adopted AI technologies (or plan to in the next 12 months) stated they invested in or will invest in more energy-efficient hardware to meet ESG goals.