Enterprises underestimate GenAI deployment requirements despite having ambitious plans to increase adoption in 2024

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IMAGE: MIT Technology Review Insights (MITTR)

A global study conducted by MIT Technology Review Insights (MITTR) has found while most enterprises expect the number of business functions in which they aim to deploy GenAI to more than double in 2024, only a small portion believe they have the right level of technology and other attributes such as culture and skills to support its adoption. 

There is a need for many organisations to rethink their underlying technology infrastructure and data strategy in order for GenAI to be implemented effectively.

The study was conducted among 300 senior executives mostly responsible for IT management and data engineering-related functions, across various sectors including financial services, consumer packaged goods and retail, manufacturing and automotive, logistics, and media and communications. Majority of the respondents were from APAC, with the remaining from the Americas and Europe.

Combined with insights from an expert interview panel, the study investigates whether enterprises are ready to tackle the challenges surrounding the effective deployment of GenAI. 

Key findings from the study include:

Executives expect GenAI to disrupt industries across economies

Overall, six out of 10 respondents agree that GenAI technology will substantially disrupt their industry over the next 5 years. Despite inevitable variations, respondents that foresee disruption exceed those that do not across every industry. 

Majority do not see AI disruption as a risk and instead hope to be disruptors

Rather than being concerned, 78 per cent of respondents see GenAI as a competitive opportunity. Just 8 per cent regard it as a threat. Most hope to become disruptors: 65 per cent say their businesses are actively considering new and innovative ways to use GenAI to unlock hidden opportunities from data. 

Despite expectations of change, few companies went beyond experimentation with, or limited adoption of, GenAI in 2023

Although most (76 per cent) companies surveyed had worked with GenAI in some way in 2023, few (9 per cent) had adopted the technology widely. The rest that experimented had deployed it in only one or a few limited areas. The most common use case was automating non-essential tasks—a low-to-modest-gain, but minimal-risk usage of the technology. 

Companies have ambitious plans to increase adoption in 2024

Respondents expect the number of functions or general purposes where they will seek to deploy GenAI to more than double in 2024. They expect to frequently apply the technology in customer experience, strategic analysis, and product innovation areas by year end. Respondents also plan to increase the use of GenAI in specific fields relevant to their industries, including coding for IT firms, supply change management in logistics, and compliance in financial services. 

Companies need to address IT deficiencies or risk falling short of their GenAI ambitions

Fewer than 30 per cent of respondents rank IT attributes at their companies as conducive to rapidly adopt GenAI. Those with the most experience of rolling out GenAI have even less confidence in their IT. Many in this group (65 per cent) say their available hardware is, at best, modestly conducive to rapid adoption.

IMAGE: MIT Technology Review Insights (MITTR)

Geraldine Kor, managing director for South Asia at Telstra International, said the effective deployment of GenAI solutions was predicated upon having 100 per cent confidence in the end-to-end operationalisation of capturing, processing, contextualising and actioning data, particularly if attempting to do so in real time or near real time. 

She added that building end-to-end capabilities to handle large datasets, accurately contextualise the data for business value and ensure minimal AI hallucinations was extremely challenging. 

While business leaders are largely in agreement on GenAI being a competitive opportunity rather than a threat, a closer look at the adoption of GenAI across surveyed companies, however, fails to reveal extensive disruptive innovation. Instead, for now, businesses are much more likely to engage in modest experimentation.

“While most businesses are exploring GenAI capabilities, it is disappointing how tactical that experimentation has been,” said Michael Schrage, research fellow of MIT Sloan School’s Centre for Digital Business. “Too many experts look at GenAI as a way of automating or augmenting existing workflows and processes, rather than rethinking use case fundamentals or the desired outputs and outcomes they really want.”

IMAGE: MIT Technology Review Insights (MITTR)

Many organisations seem to underestimate the requirements for effective GenAI implementation because of the ease in using AI-enabled web pages or software. Specialised IT assets that can effectively support extensive, high-quality generative AI tools and platforms are not yet widely deployed.

“There is a misconception about how easy it is to run mature, enterprise-ready GenAI. The large language model is almost the smallest part,” said Stela Solar, inaugural director at Australia’s National Artificial Intelligence Centre, Commonwealth Scientific and Industrial Research. “There are surrounding elements like the app design, connection to data and business processes, corporate policies and more that are still needed.”

“Singapore, like most countries, is still in the early stages of adopting GenAI, with the technology only recently becoming available in productivity suites suitable for a wider audience,” said Laurence Liew, director of AI innovation at AI Singapore (AISG). “Companies face a dilemma in accessing the necessary hardware today. Choices include outright purchase and pay-as-you-go outsourcing, both of which carry their own risks. Additionally, data quality, storage and talent remain bottlenecks for effective deployment.”

IMAGE: MIT Technology Review Insights (MITTR)
IMAGE: MIT Technology Review Insights (MITTR)

Beyond technical requirements, respondents also cited compliance and data privacy as key challenges.

According to Schrage, legal regimes, not technological capabilities, posed the biggest threat to the development and deployment of GenAI. He said regulators and litigators could rein in businesses that overstepped existing rules with the new technology. 

The study suggests that while senior executives from multiple sectors expect the adoption of GenAI to cause substantial disruption, and they see the opportunity to secure competitive advantage as the technology becomes more pervasive, their actions however paint a less ambitious picture. 

The study was sponsored by Telstra International. 

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