The AI-First Future: Challenges & Opportunities

AI is expected to keep shaping global business strategy, with Gartner predicting the technology to rank among the top 10 technology trends in 2025 [1].

This prominence has fueled a so-called "AI-first" approach, in which AI is treated as the primary engine for business growth. While this approach offers clear advantages in maintaining a competitive edge, unlocking its full potential also entails mounting challenges.

What does it mean to be AI-first?

Being AI-first means adopting a business strategy that systematically integrates Artificial Intelligence into core systems to create sustainable competitive advantage, rather than simply deploying as many AI tools as possible. In practice, an AI-first company uses AI as a strategic lever that shapes how it operates, serves customers, and allocates resources.

An AI-first strategy can be understood as a clearly defined roadmap for embedding AI into the organization's core technology and business architecture. It is not about sidelining essential functions such as customer service or back-office operations. On the contrary, it focuses on using AI to optimize existing processes, enhance operational efficiency, and ultimately improve business performance.

The scale of recent AI investment underscores a broader shift in corporate strategy toward this technology. According to the Financial Times, investment in generative AI reached a record high in 2023, driven by deals involving global technology giants such as Microsoft–OpenAI and Microsoft & Amazon–Anthropic. This investment is estimated to be nearly three times the previous record set in 2021, which stood at US$ 11 billion [2].

Although AI-first strategies are still in their early stages, companies that are further along in their AI journey are already reporting positive outcomes. Research by ServiceNow and Oxford Economics finds that AI outperforming companies – or "pacesetters" – are seeing positive returns on their AI investments, with one in three achieving a return on investment of at least 15%. Reflecting this success, 94% of these organizations plan to increase AI spending in the coming years, and 40% intend to raise it by 15% or more [3].

AI-first across sectors

Artificial intelligence (AI) is expected to generate tremendous value for the global economy, with Generative AI applications alone potentially adding up to US$4.4 trillion annually [4]. Renowned for its unprecedented accuracy, speed, and ability to uncover patterns that are invisible to the naked eye, AI has the potential to optimize operations, elevate customer experience, and strengthen flexibility and scalability for businesses across industries.

Energy and utilities

In the energy and utilities sector, AI plays a critical role in enabling the energy transition. At FPT Techday 2024, Mr. Jozef Farkas, Managing Partner at P3 Group, highlighted AI as a key success factor when sharing his company’s AI journey.

P3 was facing growing challenges in forecasting energy demand in the German and broader European markets, due to factors such as supply shortages, rising demand for electric vehicles, and legacy systems. By partnering with FPT, P3 aims to accelerate the digitalization of the energy market and is leveraging AI for use cases such as predictive maintenance for charging infrastructure.

This predictive maintenance application has helped P3:

• Reduce infrastructure costs by 30%;
• Increase uptime for electric vehicle users.

Similarly, another leading utility company sought to use AI to transform its traditional business into a more agile, faster-to-action operation. With support from FPT, the company scaled its AI adoption from 3 to 15 use cases in just one year, applying AI across its entire business, including:

• Energy optimization
• Legal contract review
• HR management
• Database management.

Logistics

In logistics, AI is being deployed extensively across the end-to-end supply chain to increase efficiency. PSA, the world’s largest port group, offers a comprehensive example of how AI is reshaping port and logistics operations.

Within port areas, AI has been used to automate planning for terminal operations and, more recently, to support the operations of Tuas, the world’s largest fully automated port to date. To build an efficient logistics ecosystem, PSA has also expanded beyond port operations to develop digital, AI-powered solutions for other stakeholders, such as the trucking community.

The company’s primary focus has been to leverage AI to:

• Increase productivity and asset utilization;
• Enhance safety across operations;
• Support sustainability objectives.

Other sectors

Across other sectors, businesses are also turning to AI to achieve enhanced agility and scalability. Itochu Corporation, a leading Japanese trading company, illustrates how an AI-first approach can accelerate innovation.

Itochu partnered with FPT to speed up its agent development process by designing an AI platform consisting of:

• A core platform provided by FPT, which removed the need to build everything from scratch;
• Multiple agents developed on top of the core, tailored to different business requirements.

With this model, Itochu managed to implement each individual agent in only two months, compared with up to one year under its traditional process.

Learn more about how leading corporations are embracing the AI-first strategy here.

Adopting an AI‑first strategy is becoming increasingly unavoidable for many organizations, as artificial intelligence reshapes products, operations, and customer expectations. However, business leaders should approach this shift with measured caution, carefully weighing potential risks, ethical implications, and regulatory constraints before committing to large‑scale transformation.

Building the AI-ready infrastructure

AI solutions consume an enormous amount of energy to run and demand even more to operate efficiently at scale. This level of consumption requires highly specialized, powerful infrastructure that often exceeds the capacity of legacy systems. In fact, nearly half of IT managers lack confidence in their current infrastructure to handle AI workloads, despite a majority of them (85%) planning to or already implementing AI solutions [5].

Beyond compute and energy, most companies also lack the data capabilities needed to properly fuel AI. Siloed data and fragmented workflows, often rooted in legacy systems, prevent organizations from building a unified, high-quality data foundation. Without a reliable data repository and the ability to update it in real time, even the most advanced AI solutions struggle to deliver meaningful business value.

Modernizing legacy systems is therefore critical to building future-ready infrastructure for an AI-first approach. Although some organizations see modernization as a lengthy, complex, and time-consuming process, there is an important dynamic at play: AI requires modernized infrastructure to run on, yet AI itself can significantly accelerate the modernization journey.

According to Gartner, utilizing Gen AI solutions can help businesses reduce modernization costs by up to 70% [6]. Leveraging ready-made, well-tested solutions further optimizes efforts by shortening the development and implementation cycle.

xMainframe by FPT: an AI accelerator for legacy modernization

xMainframe by FPT is an advanced large language model (LLM) specifically designed with deep expertise in mainframe legacy systems and COBOL codebases. The solution demonstrates strong performance, achieving 97% accuracy in comprehending mainframe knowledge, making it six times more efficient than previous models such as ChatGPT 3.5 and 4.

With this level of capability, xMainframe helps businesses cut up to 50% of the effort required to estimate the complexity of modernization projects and doubles the speed of understanding existing COBOL codebases. As a result, organizations can modernize mission-critical systems faster, with lower risk and more predictable outcomes.

Learn more about overcoming legacy modernization challenges here.

Building the AI-ready workforce

IT talent shortage remains a prolonged global issue. IDC estimates that 90% of businesses worldwide will be affected by this crisis, with potential losses reaching as much as US$5.5 trillion by 2026 [7]. Given the growing complexity of AI development, there is little indication that this situation will improve in the foreseeable future. In response, companies around the world are expanding their search for digital talent far beyond traditional markets, with some even willing to travel across the globe to secure the expertise they need.

Among emerging markets, Vietnam has risen as a global hub for AI research and development. Underscoring the country’s potential, NVIDIA CEO Jensen Huang recently referred to Vietnam as the company’s "second home" and committed to making it a key focus market. During this visit, NVIDIA signed a cooperation agreement with the Vietnamese government to establish an AI research and development center and an AI data center in the country [8].

In business terms, local corporations are also joining forces to strengthen Vietnam’s AI capabilities. FPT Corporation has announced the establishment of a US$200-million AI factory in Vietnam and another in Japan, supported by an ecosystem of partners 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 through partnerships with leading AI institutes such as 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 AI-First Complexity

Becoming an AI-first enterprise is both essential and highly complex. To truly unlock the value of AI, organizations must build the right infrastructure, develop the right talent, and accumulate sufficient high-quality data, among many other requirements. At the same time, surging demand for powerful AI chips and ongoing global chip shortages make the landscape even more challenging and overwhelming for business leaders.

Partnering with experienced experts offers a practical way to move forward, especially with those who can support the entire AI lifecycle—from research and development to implementation, training, and even chip design—such as FPT. The corporation has supported more than 1,100 businesses on their digital transformation and AI journeys, including 96 Fortune 500 companies.

To explore how FPT can help you envision and build an AI-first future, visit: https://fpt-aicenter.com/en