No stopping this technology train. The CIO Office has long been constructive on Big Tech. Despite shaky investor sentiment during the relentless Fed rate-hiking cycle in 2022 and 2023, we maintained the view that the technology sector would make a comeback on the basis of robust earnings growth, balance sheet strength, structural criticality, and strong net cash positions. We also contested the notion that higher rates will suppress end demand, citing the emergence of artificial intelligence (AI) as a growth catalyst that would usher in a new growth paradigm for Big Tech companies, many of which form the structural backbone of this nascent technology. Additionally, Big Tech companies have further cemented their leadership in the past two years, establishing their authority in a growing number of tech-related verticals through innovation and inorganic growth. This series of contrarian calls has panned out well, with Big Tech delivering a striking performance of c.+137% from Nov 2022 to Feb 2024.

Latest earnings season affirms momentum. 4Q23 was another strong quarter for Big Tech, with many industry stalwarts posting beats on both the revenue and earnings fronts. Their strong fundamentals position them well to continue delivering promising performance in the coming year. Even for companies that were less sanguine in their guidance, share price performance remained resilient; this suggests that investors are looking beyond near-term factors and are in fact aligning themselves with long-term catalysts.

Embracing Q-GARP. The strong outperformance by Big Tech has prompted us to coin the term "Q-GARP", which stands for Quality Growth-at-a-Reasonable-Price. Traditionally, the Growth-at-a-Reasonable-Price strategy involved picking companies that produced strong earnings without excessive valuations. However, in the current era of Big Tech, valuation multiples have grown, necessitating a new benchmark for what is "reasonable" when taking into account growth, quality, pricing power, and presence of economic moats. Q-GARP focuses on companies with best-in-class qualities and the highest growth potential in their respective sectors. With growth in the markets currently dominated by technology, the areas which we believe align best with this strategy are: i) Big Tech; ii) Artificial Intelligence (AI); and iii) Cybersecurity.

Big Tech

We believe Big Tech will continue to be a bright spot within the equity space, buoyed by the following catalysts:

Catalyst 1: Semiconductor recovery in sight. Semiconductor chipsets form the core foundation of most technology today and is a good barometer of the upstream technology sector. After a year-long slowdown, semiconductor sales to China and the US have passed the trough in mid-2023 on the back of a stable recovery driven by new demand from AI and related services. We believe this represents a turning point for the sector and suggests that inventory issues are gradually being resolved. Coupled with signs that demand is bottoming, we will likely see a further recovery across the semiconductor sector moving forward.

Catalyst 2: Resilient global IT spending uptrend. Global IT expenditure is expected to remain robust and broad-based, spanning across services, hardware, software, and communications, and reaching a total addressable market size of USD5.3t by 2025. This uptrend has remained intact over the past two decades, persisting even during the peak of Covid lockdowns. The only exception was a minor blip during the GFC in 2009. As the adoption of cloud computing and AI-embedded applications expand, we believe Big Tech companies and sector leaders are poised to secure a slice of this growing pie.

Catalyst 3: Strong revenue and earnings backdrop. The sector’s performance was in large part driven by its strong revenue and earnings growth, which outstrip the broader market. The enduring end demand for tech-related products and the admirable pricing power of Big Tech companies should continue to support this trend moving forward.

Catalyst 4: Solid balance sheet and shareholder return. The majority of Big Tech companies have negative net debt, and therefore have a higher degree of liquidity and financial stability compared to more highly leveraged companies. Additionally, a large cash pile gives them the financial muscle to make opportunistic acquisitions. This low dependence on leverage, coupled with growth from M&A activity, has seen Big Tech consistently deliver shareholder returns above that of global equities.

Catalyst 5: Growth-adjusted valuation has room for expansion. While naysayers may argue that Big Tech trades at a huge premium (c.30x and c.26x 2024/25 earnings respectively), we believe the premium is justified given the quality of the companies in question; the combination of growth and true safety that these companies offer is rare in equity investing. On a growth-adjusted basis, the average 2024/25 PE-to-growth (PE/G) is not at all demanding. Big Tech’s 2-year average PE/G of 1.3x is at a stark discount compared to 1.9x of global equities.

Artificial Intelligence

AI leading the charge. Interest in AI has exploded following the release of ChatGPT and its rapid uptake. Generative AI applications, like ChatGPT, Bard, and Dall-E can be used to generate a myriad of outputs, ranging from text and images to more specialised output such as code and audio. This provides tremendous benefits for both businesses and individual users alike, underscoring the potential for a massive total addressable market for AI-related sectors.

With AI’s revenue potential projected to grow rapidly over the next decade, we believe the following pillars will benefit greatly from this trend.

Pillar 1: Integrated circuit – chip designers and semiconductor foundries. Semiconductors are the foundational bricks of the digital world. AI models typically require advanced chipsets, both in training and in production. Market research agency TrendForce estimates that the GPT model needed about 20,000 GPUs to process training data in 2020, and moving forward, running ChatGPT is expected to require at least 30,000 GPUs. Further development and uptake of AI across industries would only increase demand for GPUs, microprocessors, power management ICs etc, especially as commercial development — which demands for the speed and sophistication of AI models to grow — takes over.

Pillar 2: Cloud platforms. Once AI models have been sufficiently trained and deemed fit for commercial purposes, they are likely to be deployed on cloud platforms for ease of access by a general user base. A proliferation of models for language, image, video, music, etc. would naturally give rise to demand for cloud companies to host them. Given that Generative AI is particularly adept at generating large amounts of content, businesses that produce voluminous amounts of material (news websites, e-commerce platforms, online videos) would also likely require ever-increasing hosting space from cloud providers.

Pillar 3: Cybersecurity. Generative AI is especially gifted in "deepfakes" – synthetic media that assimilates the likeness of a person in realistic fashion – which can be used to spread misinformation at scale. For example, an experiment conducted by Singapore’s GovTech found that phishing emails composed and customised using generative AI had significantly higher clickthrough rates compared to human-generated emails. This creates a greater need for cybersecurity across all platforms.

Cybersecurity

The growing need for cybersecurity. The world has benefitted greatly in the Age of Information – democratising access to data and permeating knowledge to millions across the world. But that has now given way to the Age of Misinformation, empowered by AI. Companies now, more than ever, must devote resources to protecting their digital processes and platforms. Besides the threat posed by AI, businesses are currently under pressure to increase cybersecurity due to:

• Rising cost of data breaches and ransomware – an increasing amount of resources have to be devoted to detecting cyberattacks and implementing compliance measures afterfalling victim to one.
• Increasing sophistication of cyberattacks – Technology like AI is being used to create cyberattacks that can better evade detection, and at a much higher frequency thanbefore.
• Hybrid working as the new norm – Remote working increases the vulnerability of company data and digital platforms, particularly through endpoint devices.

AI – both shield and sword. While the threat of cyberattacks is aggravated by AI, this technology can also be leveraged to enhance cybersecurity solutions. The development and integration of AI in cybersecurity can be used to detect and even counteract cyberattacks. For example, AI can be used to analyse databases of existing malware and discern patterns which can be used to identify new malicious code. 35% of Chief Information Security Officers are already employing AI for positive security measures, and 61% are expected to adopt it within the next 12 months.

Winners in the cybersecurity space. As the realm of cybersecurity constantly evolves with the adoption of new technologies, the biggest players in the industry will be best positioned to stay at the forefront of new developments and attract customers who prioritise high quality and secure solutions. Another area of focus is endpoint security as the remote working trend continues; there is a constant need for companies to safeguard corporate IT network endpoints, including computers, laptops, and IoT devices against cyber threats. Because of this, demand for endpoint security is projected to rise at a stellar CAGR of 9.2% from 2024 to 2034.

Capture the value of Big Tech with the DBS CIO I.D.E.A. framework. The pipeline of innovation and new technology reshaping our world bolsters the attractiveness of tech investing. Big Tech and its surrounding ecosystem plays fit the characteristics of Q-GARP. On the growth side of the CIO Barbell strategy, we advocate for investors to employ the Q-GARP philosophy to capture long-term secular growth themes through the DBS CIOI.D.E.A. (Innovators, Disruptors, Enablers, and Adapters) framework in the following verticals: cloud computing, semiconductor, energy transition, AI, data analytics, software applications, and cybersecurity.