Businesses optimistic on generative AI, but face a reality gap in deployment: Study
With the mainstream emergence of generative AI, organizations across Asia Pacific are rightly enthused by the myriad possibilities. There are numerous use cases – such as coding for IT firms, supply chain management in logistics, and financial services compliance – that provide better customer support, deep data analysis, and computer code generation. But like the technology itself, most organizations are at the beginning of their AI journeys.
To leverage the full capabilities generative AI offers requires an enterprise-wide implementation, with fully-connected data resources. It’s the processes, infrastructure, and strategy needed to achieve that which prove challenging. Without that far-reaching presence of AI across the business, the technology cannot provide significant competitive advantages.
However, a global study by MIT Technology Review Insights (MITTR) has found that despite the technology advancing at a rapid pace, the practical application of AI remains relatively limited in scope – reducing such competitive advantages. The study uncovered a significant reality gap between decision-makers’ expectations of generative AI’s implementation, and their organizations’ ability to implement it.
The report for the study was produced in partnership with Telstra International, a global arm of leading telecommunications and technology company Telstra. The respondents comprised business leaders across Asia-Pacific, the Americas, and Europe, who mostly manage IT, data, and data engineering-related function in industries such as financial services, manufacturing, logistics, energy, media and communications.
Limited AI deployment at most organizations
Around 37% of respondents said their organisations had experimented with deploying AI in limited areas, but many realize that there are significant impediments to full rollouts across the business. In fact, those that have adopted generative AI widely – or the early adopters – are less confident that they have the knowledge, skills, resources, and infrastructure to enable their end-game.
It’s easy, of course, to remain bullish about the possibilities of a new technology when decision-makers’ experience of real-world implementations are limited. The fact is that while most business leaders expect to disrupt their industries using generative AI, the majority will likely face disruption by their competitors instead. The difference between the disrupters and disrupted lies in the ability to overcome the problems and roadblocks that prevent the technology from working effectively across the business.
“As the world becomes increasingly digitized and human-to-machine interactions flourish, being able to process data to drive informed real-time or near real-time business decisions is paramount,” said Geraldine Kor, Managing Director and Head of Global Enterprise at Telstra International.
“When implemented successfully, this proficiency will be a game-changer for most organizations, and will distinguish leaders from followers. However, building end-to-end capabilities to handle large datasets, accurately contextualize the data for business value and ensure the responsible and ethical application of AI is extremely challenging.”
Top challenges in generative AI
The MITTR report highlights the following top challenges faced by many organisations:
Hardware: Appropriate hardware, in-house or outsourced, is a prerequisite of extensive generative AI adoption, and decision-makers often fail to grasp the degree of the requirement. Accessing these assets poses a dilemma: outright purchase carries risk and in a fast-moving landscape, over-committing is risky.
Datasets and volume: Good data – fundamental for generative AI – is in short supply. Among early adopters, 58% said available volume of data at their companies was at best modest, and half said the same of data accuracy and storage infrastructure (Figure 6).
Regulatory, compliance, and data privacy environment: This was the most commonly mentioned non-IT impediment, with more than half of early adopters saying they struggle to address cybersecurity issues (Figure 6).
Budget for technology investment: The second most common barrier reported by respondents is budgetary constraints (Figure 7). The numerous technological challenges for generative AI adoption indicate that success may require substantial investment.
Competitive environment and organizational culture: About half of respondents cited the competitive environment as a barrier to generative AI adoption, while 41% said the same of cultural attitude toward technological innovation (Figure 7).
Shortage of AI talent: 31% of respondents who were early adopters said skills within their companies were a barrier, while 46% said the same of available external talent. Non-early adopters were more optimistic: a minority (21%) of them said the skill levels within their workforce were a barrier to rapid adoption, with a similar number (23%) saying the same of skills within their domestic economies.
Expertise to navigate generative AI deployment challenges
The above challenges highlight the need for a well-planned and robust data strategy in implementing AI projects, which requires a whole-of-company approach to fully realize AI-driven operations.
However, organizations often encounter roadblocks in areas such as connectivity and data management, issues around legacy interoperability, and strategic planning for generative AI.
With this era of digital business defined by a hyperconnected landscape of distributed workforces, decentralized applications, and external ecosystems, the seamless and secure movement of data is key to competitive advantage.
“The hyperconnected digital fabric is the foundation of the digital-first economy, and data in motion is essential to the effective creation, consumption and contextualization of corporate and ecosystem data, applications, and operations,” said Linus Lai, Chief Analyst and Vice President for Digital Business, Trust and Services at IDC Australia and New Zealand.
“Organizations must develop the capabilities for anytime and anywhere access, pervasive digital experiences, real-time insights, and business continuity and reliability. By doing so, a digital business can excel in value creation for improved efficiency, new innovation, and greater agility; enabling the business to adapt continuously.”
The requirement for expertise to navigate these challenges means enterprises in Asia Pacific often look to established providers with a track record in deploying technologies that have significant strategic impact. One example would be Telstra International, which owns the largest subsea cable network in Asia Pacific that carries around a third of the region’s internet traffic, offering connectivity to more than 200 countries and territories.
Telstra offers an array of product and service offerings to support organizations on their digitization and AI journey. These include AI and data envisioning customer workshops that examine the organization’s existing processes, identify gaps and co-create solutions aligned with business objectives. Additionally, Telstra’s Security Operations Centers in Australia provide comprehensive managed security services, complemented by security services centers in Asia and the U.K.
“Effectively deploying generative AI solutions is predicated upon having 100% confidence in the end-to-end operationalization of capturing, processing, contextualizing, and actioning data,” said Kor.
“In today’s hyperconnected business and AI landscape, it is essential that IT leaders embark upon a technology adoption strategy that right-fits, right-sizes and right-locates their IT investments.”
Click here to download the MIT Technology Review Insights report, “Generative AI: Differentiating Disruptors from the Disrupted”.
About Telstra International
Telstra is a leading telecommunications and technology company with a proudly Australian heritage and a longstanding, growing international business. Today, Telstra International has over 3,000 employees based in more than 35 countries outside of Australia, providing services to thousands of business, government, carrier and OTT customers.
Telstra International empowers businesses with innovative technology solutions including data and IP networks, and network application services such as managed networks, unified communications, cloud, industry solutions, integrated software applications and services. These services are underpinned by its subsea cable network, with licences in Asia, Europe and the Americas and access to more than 2,000 Points of Presence (PoPs) in more than 200 countries and territories globally.
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