Generative AI has taken the world by storm since the launch of ChatGPT in 2022, with enterprises globally ramping up adoption and seeking to unlock its benefits.
While there is a keen enterprise appetite for generative AI, adopting, implementing, and delivering success with the technology is another matter entirely.
Research from Dell Technologies earlier in 2024 highlighted this challenge for many IT leaders. Globally, 81% of respondents to the Dell Technologies Innovation Catalyst Research agreed that generative AI will “significantly transform” their industries in the years to come.
While optimism about the potential of generative AI is high, enterprise preparedness for the technology is lacking, with the blistering pace of change specifically highlighted as a key hurdle.
Nearly half (48%) of respondents globally said they are uncertain what their particular industry will look like within five years. Six in ten also warned their organization is struggling to keep pace with current developments in the technology.
A key challenge for IT leaders with regard to generative AI adoption is the level of excitement surrounding the technology.
The benefits of generative AI are widely publicized, enabling teams as diverse as cybersecurity and human resources to markedly improve productivity and potentially deliver cost savings.
This has created a sense of urgency among IT and enterprise leaders, many of whom are keen to capitalize on this industry trend and keep pace with competitors.
Dell Technologies’ research found that many organizations are still working through the practicalities of the technology, however, and moving from ideation to implementation can be challenging.
During this critical period, it’s crucial that organizations take a considered approach to generative AI adoption, yet many fail to do so.
A study from Ardoq in May 2024 found that emerging technology investments are often driven by ‘fear of missing out’ (FOMO). Six in ten CIOs identified FOMO as a key factor behind accelerating investment in AI over the last two years, especially when it comes to generative AI.
While enterprises should strike while the iron’s hot to maintain a competitive edge, a rash approach to generative AI adoption can create longer term issues for enterprises.
The level of investment required when embarking on a generative AI journey should not be underestimated, either - especially with many experiencing questionable returns on investment (ROI).
Analysis from Google earlier this year, for example, found that some enterprises could be waiting up to a year for a return on investment after generative AI adoption projects.
With these considerations in mind, how can IT leaders take their first steps toward generative AI success? A good place to start is by getting their data in order.
Maximizing data to unlock generative AI
Unlocking the value of data has been a key enterprise focus for several years now and the advent of generative AI has made this even more imperative. With this in mind, building a robust data strategy is critical, according to Dell Technologies. The Dell Technologies 2023 Innovation Index, for example, highlighted a “clear link between innovation success and organizations that have a mature data strategy”.
Despite this, only 26% of IT decision makers said all innovation efforts are based on data insights.
“The appetite – and demand – to maximize the value of this data and drive innovation is insatiable,” reads Dell’s 2024 Innovation Catalyst Research.
“When used correctly, AI and GenAI can fundamentally change the role and value of data, but with many organizations facing turbulent times, not all are set to fully capitalize on its capabilities.”
Dell Technologies’ research on data maturity aligns with previous research on the subject, which has been a long-running issue for enterprises. In the 2023 Data Maturity Index from Carruthers and Jackson, for example, 29% of respondents revealed their organization had no established data strategy at all.
Although this marked an improvement on the year prior - in which 27% of respondents reported having a robust data strategy - this shows there are still signs for improvement.
A key focus at present for organizations is modernization of the infrastructure which underpins generative AI development. Respondents to Dell Technologies’ 2024 Innovation Catalyst Research, for example, identified scalable infrastructure as the leading area of improvement required to accelerate generative AI innovation.
Yet many IT leaders are struggling to fully harness their IT infrastructure, Dell Technologies noted. So far in the generative AI journey, organizations have leveraged a combination of both public and private clouds to “uphold their IT infrastructure, the company found - but this raises unique challenges.
“While there are important advantages to the different approaches, integrating private and public clouds introduces a myriad of obstacles,” the company noted.
“There are technical, operational, and security challenges that demand meticulous planning, ongoing optimization, and a skilled IT workforce to navigate the complexities of diverse cloud ecosystems effectively.”
Choosing the right technology partner
Given long-standing infrastructure and data-related challenges for enterprises, choosing the right technology partner in the age of generative AI can be crucial to achieving success.
“The promises [of GenAI] are immense, organizations are seeking these opportunities and want partners to help them get there,” Dell’s Innovation Catalyst report noted.
In particular, enterprises seek a range of services and capabilities when choosing a partner. This includes services that guide them during the implementation, training, and scaling process of AI development.
Similarly, those that can provide infrastructure curated specifically to their unique business needs is a key requirement.
Organizations such as Dell Technologies offer a range of solutions and services aimed at overcoming these challenges, such as the Dell AI Factory. This approach is a reimagining of traditional IT infrastructure to accommodate the new demands of AI, and essentially “brings AI as close as possible to where data resides”, according to Nigel Burmeister, director of APEX portfolio marketing at Dell Technologies.
“Just like physical factories fueled the industrial revolution, AI factories will drive the AI revolution. But instead of producing physical goods, they create actionable intelligence, fresh content and new insights,” he said in a May 2024 blog post.
In essence, the Dell AI Factory enables organizations that are starting to use AI to minimize latency, reduce costs, and bolster security by ensuring data is hosted within a controlled environment.
The Dell AI Factory with Nvidia, for example, helps enterprises to simplify and streamline AI deployment. This combines the company’s compute, networking, and storage expertise with Nvidia’s AI infrastructure capabilities, as well as its enterprise AI software options.
The solution builds on a long-standing collaboration between the two companies, and supports a broad range of potential AI use cases and applications, providing enterprises with end-to-end support throughout the generative AI lifecycle – from inferencing to model training, development, and fine tuning.
Dell’s AI approach, products and services will be a key part of the Dell Tech Forum London event on 26th November. Register here.
