What does it mean to be AI-first?
AI-first strategy can be defined as a corporate focus on the use of Artificial Intelligence (AI) to achieve competitive advantages. Despite how straightforward it may sound, an AI-first strategy does not simplay translate to an abundant use of AI solutions; instead, it’s a systematic, clearly defined roadmap for integrating the technology into the core systems. An AI-first strategy does not mean overlooking core business functions such as customer services and back-office, but rather the opposite – it’s about leveraging AI to optimize existing processes, boost efficiency, and ultimately improve performance.
The sheer volume of AI investment has signaled a global shift in corporate strategy to focus more on this technology. The Financial Times has reported a record high of investment in GenAI in 2023, accumulating from deals among global tech giants, including Microsoft – OpenAI and Microsoft & Amazon – Anthropic. Such investment is estimated to be nearly three times the amount of the previous record set in 2021, at US$ 11 billion [2].
Despite the AI-driven strategy remaining in its infancy, outperforming companies, those who are more advanced on their AI journeys than their peers, already see positive results from AI investment. Research by ServiceNow and Oxford Economics concludes that AI outperforming companies, or pacesetters as they call it, report positive ROI, with one in three achieving at least 15%. With such favorable results, it is undoubted that 94% of these companies plan to increase AI investment in the coming years, with 40% willing to raise it by 15% and more [3].
AI-first across sectors
AI is expected to create tremendous values to the global economy, with Gen AI applications alone potentially adding up to US$4.4 trillion annually [4]. Renounced for its unprecedented level of accuracy, speed of delivery, and the ability to identify patterns that are invisible to the naked eye, AI holds the potential to optimize operations, enhance customer experience, and strengthen flexibility and scalability for businesses across industries.
In energy & utilities, AI plays a critical role in facilitating the energy transition, so much so that Mr. Jozef Farkas, managing partner at P3 Group, sees AI as a key success factor when sharing his company’s AI journey at the annual FPT Techday 2024. P3 was facing mounting challenges to anticipate the energy demand in the German and European markets, driven by issues such as supply shortage, rising demand for electric vehicles, and legacy systems. Partnering with FPT, P3 aims to accelerate the digitalization of the energy market, leveraging AI for use cases such as predictive maintenance for the charging infrastructure. This application has helped P3 reduce infrastructure costs by 30% and increase uptime for electric vehicle users. Similarly, another leading utility company wished to leverage AI to transform their traditional business into a more agile, faster-to-action operation. With the help of FPT, the company managed to scale from 3 to as many as 15 use cases in just one year, applying AI across their entire business, ranging from energy optimization, legal contract review, to HR management and database management.
In logistics, AI is extensively used across the entire supply chain to increase efficiency, with PSA, the world’s largest port group, offering a comprehensive example. In the port areas, AI has been utilized for automation, such as planning for terminal operations and more recently, the operations of Tuas, the world’s largest fully automated port to date. To achieve an efficient logistic ecosystem, the company has also moved beyond the port operation to develop digital, AI-powered solutions for other stakeholders, such as the trucking community. The primary focus has been to leverage AI for productivity, including increasing asset utilization, AI for safety, and AI for sustainability.
In other sectors, businesses are also turning to AI for enhanced agility and scalability. For example, Itochu Corporation, a leading Japanese trading company, has partnered with FPT to accelerate its agent development process. The company designed an AI platform with FPT, consisting of a core platform, which saved the company from developing from scratch, and multi-agents on top of the core, which the company developed based on different business requirements. With this model, Itochu Corporation managed to implement each individual agent in only two months, cutting down from as long as one year as the traditional process.
Learn more about how leading corporations are embracing the AI-first strategy here.
Going AI-First with caution
Embracing the AI-first approach is arguably inevitable; nevertheless, business leaders are advised to proceed with caution.
Building the AI-ready infrastructure
AI solutions consume an enormous amount of energy to run and require even more to become efficient. Such demand requires specialized and powerful infrastructure, which often exceeds the current capacity of legacy systems. In fact, nearly half of IT managers show a lack of confidence in their infrastructure to handle the AI workload despite a majority of them (85%) planning to or already implementing AI solutions [5]. Moreover, most companies lack the data capabilities to fuel AI, resulting from siloed data and fragmented workflow that stem from using legacy systems. Without a quality data repository and the ability to update it in real-time, even the most powerful AI solutions would not generate much value.
Modernizing legacy systems is indeed critical to building the future-ready infrastructure for pursuing an AI-first approach. Some might fear the modernization process to be lengthy, complex, and time-consuming, but here’s a catch: AI requires modernized infrastructure to run on, but it is AI that accelerates the modernization process. Indeed, utilizing Gen AI solutions can help businesses reduce modernization costs by up to 70%, as estimated by Gartner [6]. And leveraging ready-made, well-tested solutions, such as xMainframe by FPT, further optimizes the modernization effort by cutting down the solution development process. xMainframe is an advanced large language model (LLM) specifically designed with expertise in mainframe legacy systems and COBOL codebases. The solution exhibits impressive performance, achieving a 97% accuracy in comprehending mainframe knowledge, which is 6 times more efficient than previous models such as ChatGPT 3.5 and 4. For that reason, the solution managed to help businesses reduce up to 50% effort in estimating the complexity of modernization projects and increase the speed of understanding the COBOL codebase by two times.
Learn more about overcoming legacy modernization challenges here.
Building the AI-ready workforce
IT talent shortage remains a prolonged issue globally, with IDC estimating 90% of businesses worldwide to suffer from the crisis, accumulating to as much as US$5.5 trillion loss by 2026 [7]. Given the increasing complexity of AI development, it is no doubt that the situation would not get any better, at least in the foreseeable future. In response, global companies are expanding their search for talent beyond their traditional markets, with some showing no hesitance to travel across the globe.
Among the emerging markets, Vietnam has risen as a global hub for AI research and development. Reaffirming Vietnam’s potential, in his recent visit to Vietnam, Mr. Jensen Huang, NVIDIA’s CEO, has referred to the country as a “second home” and committed to making Vietnam a key focus for NVIDIA. During this visit, the company has also signed a corporation agreement with the Vietnamese government to establish an AI research and development center and an AI data center in the country [8]. Business-wise, local corporations are also joining hands to strengthen Vietnam’s AI capabilities. FPT Corporation recently announced the establishment of a US$200-million AI factory in Vietnam and another in Japan, strengthened by a partner ecosystem including NVIDIA, SCSK, ASUS, Hewlett Packard Enterprise, VAST Data, and DDN Storage. The corporation is also a pioneering force in advancing AI training and fostering responsible AI, establishing partnerships with leading AI institutes, including Mila, Landing AI, and members of the AI Alliance.
From one of the poorest countries to an emerging destination for AI. Learn how Vietnam got there.
Navigating the complexity
Going AI-first is essential yet complex. To truly unlock the values of AI, companies must have the right infrastructure, develop the right talent, gather abundant data, and the list goes on. In addition, the demand for powerful AI chips and the global chip shortage further complicate the situation, which can be overwhelming for business leaders. Seeking help from experienced partners offers an optimal solution, especially ones that engage in the entire AI process, from research, development, and implementation to training and chip design like FPT. The corporation has accompanied more than 1,100 businesses on their digital transformation and AI journeys, 96 of which are Fortune 500 companies.
Learn how FPT helps envision your AI-first future: https://fpt-aicenter.com/en
