SUMMARY
As per the report, organisations are failing to understand the computing and networking demands across the end-to-end AI life cycle
The report identified critical areas that businesses may be neglecting, which could impact their ability to achieve successful AI outcomes
The report surveyed over 2,000 IT leaders across 14 countries
Almost 44% of surveyed 2,000 IT leaders feel their organisations are fully prepared to leverage the advantages of AI, according to a report by Hewlett Packard Enterprise (HPE).
The study titled ‘Architect an AI Advantage’, conducted across 14 countries, uncovered a trend of increasing global investments in AI.
However, it also identified critical areas that businesses may be neglecting, which could impact their ability to achieve successful AI outcomes. These include low levels of data maturity, potential deficiencies in networking and compute provisioning, as well as essential ethics and compliance considerations.
The findings also uncovered significant disconnects in both strategy and understanding that could adversely affect future return on investment (ROI).
“There’s no doubt AI adoption is picking up pace, with nearly all IT leaders planning to increase their AI spend over the next 12 months,” said Sylvia Hooks, VP, HPE Aruba Networking.
“These findings clearly demonstrate the appetite for AI, but they also highlight very real blind spots that could see progress stagnate if a more holistic approach is not followed,” added Hooks.
AI performance impacting business outcomes hinges on quality data input. However, research indicates organisations grasp this importance, labelling data management as critical for AI success, yet their data maturity levels are low.
Only 7% can conduct real-time data pushes/pulls for innovation, and 26% have established data governance models for advanced analytics.
Of notable concern, fewer than 6 in 10 respondents indicated that their organisation possesses full capabilities in handling key stages of data preparation for AI models, encompassing access, storage, processing, and recovery. This discrepancy not only risks slowing down the AI model creation process but also heightens the likelihood of delivering inaccurate insights and experiencing negative ROI.
Similarly, a significant gap emerged regarding computing and networking requirements throughout the AI lifecycle.
While confidence levels appear high on the surface, with 93% of IT leaders believing their network infrastructure supports AI traffic and 84% agreeing their systems offer adequate compute capacity flexibility, these disparities underscore potential challenges in effectively supporting AI initiatives from end to end, the report added.
Gartner’s projection that “GenAI will play a role in 70% of text- and data-heavy tasks by 2025, up from less than 10% in 2023,” highlights the rapidly expanding role of AI in various tasks. However, less than half of IT leaders claim to fully grasp the demands of AI workloads across training, tuning, and inferencing, raising doubts about their ability to adequately provision for them.
Moreover, organisations are neglecting crucial aspects such as cross-business connections, compliance, and ethics. A significant portion of IT leaders (28%) perceive their organisation’s AI approach as fragmented, with over a third opting for separate AI strategies for individual functions and 32% establishing different sets of goals altogether. This disjointed approach risks hindering the effective integration and utilization of AI across the organisation.
Moreover, the research shows that legal/compliance (13%) and ethics (11%) were deemed by IT leaders to be the least critical for AI success. In addition, the results showed that almost 1 in 4 organisations (22%) aren’t involving legal teams in their business’s AI strategy conversations at all.
“AI is the most data and power-intensive workload of our time, and to effectively deliver on the promise of GenAI, solutions must be hybrid by design and built with a modern AI architecture,” said Eng Lim Goh, SVP for Data & AI, HPE.
The development comes at a time when more Indian startups are looking to increase their use of generative AI capabilities to automate business functions.
On Tuesday, General Catalyst’s Anand Chandrasekaran stepped down as partner after his three-year stint with the VC firm, as he aims to spend more time building his own artificial intelligence startup, Crescendo.
Meanwhile, investment arm Premji Invest is planning to boost its bets on AI companies.
As per Inc42’s ‘India’s Generative AI Startup Landscape, 2023’ report, the country’s GenAI market is expected to grow exponentially in the next few years, surpassing $17 Bn by 2030 from $1.1 Bn in 2023, growing at a CAGR of 48%. India’s startup ecosystem already comprises 70+ GenAI startups.
