Thai executives most optimistic on prospects for generative AI
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Thai executives most optimistic on prospects for generative AI

Mr Lee says enterprises locally are quite active and ready to embrace generative AI.
Mr Lee says enterprises locally are quite active and ready to embrace generative AI.

Thai executives are ready to embrace generative artificial intelligence (AI) technology according to a survey conducted by global consulting firm Accenture.

"AI is the new inflection point for technology, and generative AI is the next performance frontier," said Joon Seong Lee, senior managing director and data & AI Southeast Asia lead at Accenture.

Generative AI is a technique that draws from language and context to teach machines to create original content.

"This brings tremendous opportunities for enterprise reinvention and disrupts traditional business models," said Mr Lee.

Accenture's "Technology Vision 2023" survey of global business and IT executives, involving 4,777 respondents of which 80 were Thai, revealed that 100% of Thai respondents -- the highest percentage globally -- agree that generative AI will transform enterprise intelligence, compared with 95% of executives from other countries.

In addition, 100% of Thai executives, compared to 98% globally, agree software and services powered by AI foundation models would significantly augment innovation and creativity in their organisations in the next 3-5 years.

This suggests that enterprises locally are quite active and ready to embrace generative AI, which would be a game changer for organisations, Mr Lee added.

AI foundation models are large AI models pre-trained across data modalities such as text and images rather than on a specific task, which are able to learn to complete new tasks within these data types with little to no extra training. Examples include large language models (LLM) such as GPT-3, and text-to-image generators such as Dall-E 2 and Stable Diffusion.

Organisations plan to experiment with AI foundation models over the next 3-5 years in various business activities with most Thai executives highlighting process automation (70%) and customer support (69%).

Thailand executives reported that their organisations expect better customer experiences (78%) and accelerated innovation (68%) to be two major benefits from the use of AI foundation models.

The top implementation risks Thai executives foresee are misaligned applications of the technology, stakeholder pushback and high or increased costs.

Mr Lee said firms should consider fine-tuning the AI foundation model to fit well with their businesses.

Another Accenture research study based on employment levels in the US for 2021 found that 40% of all working hours can be impacted by LLMs such as GPT-4. Generative AI will transform work across industries and across every job category, according to the study.

Generative AI could affect more than half of all hours worked in five of 22 occupation groups. These include office and administration support, sales, business and finance operations and legal personnel, according to the survey.

Accenture estimates language tasks account for 62% of the total time employees work, and a majority (65%) of that time could be transformed into carrying out more productive tasks through augmentation and automation.

"Every role in an enterprise has the potential to be reinvented and reimagined for a new future of human plus machine work. The job still exists but the task and job description will change," Mr Lee said.

Banking, insurance, capital markets, energy, and software are among the leading sectors that offer great potential in terms of being automated by AI. For example, banks and insurance firms can utilise a chatbot service to provide advice to consumers.

Accenture recommends six adoption essentials for enterprises in embracing generative AI.

First, companies should focus on "low-hanging fruit" opportunities using consumable models to realise quick returns and the reinvention of their business using customised models.

Second, they should focus on the people as much as on the technology, ramping up talent investment to address both the creation of AI and the use of AI.

Third, they should get proprietary data ready. Foundation models need vast amounts of curated data to learn and that makes solving the data challenge an urgent priority for every business.

Fourth, they should consider requirements for a cost-optimised, sustainable infrastructure, architecture, operating model and governance structure.

Fifth, they should take advantage of industry best practices and insights and ecosystem partners.

Sixth, they should build in controls for assessing risk at the design stage and embed responsible AI.

Accenture recently announced a US$3-billion investment over three years in its data & AI practice to help clients across all industries rapidly and responsibly advance and use AI to provide growth, efficiency and resilience. The investment would deepen and develop new skills and capabilities across diagnostic, predictive and generative AI. Its data & AI practice will double its AI talent to 80,000 professionals through a mix of hiring, acquisitions and training, according to the firm.

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