"A is for Ambition": Apple and Amazon Bet Big on the Future Alphinity Investment Management  December 2024

The recent Apple and Amazon third quarter 2024 results revealed further details around the critical leg of their strategies, with these tech giants continuing to lay down markers for how they see the next stage of tech evolution unfolding and staking out positions to profit from it. Looming large in this evolution is AI, with Apple looking to leverage capabilities across what is an enormous ecosystem of 2.2bn active devices while Amazon is focusing on pushing AI applications across their Cloud and consumer business. The recent results also provided key insights into shorter term business performance. Key takeaway from the result? The key takeaway from the Apple result is that while the gains from the release of "Apple Intelligence" will be significant, they will take time. This was evidenced by the fact that despite this recent result coming in ahead of expectations, it was coupled with a guide for the coming quarter that was mildly below what the market was looking for (Apple guided to revenue growth of low to mid-single digits vs a market that was expecting +7%). This makes sense as "Apple Intelligence" has only just rolled out in the US in recent weeks, and will not become available in the UK, Australia, Canada, and New Zealand until December 2024. Other geographies will follow over the course of 2025. Most importantly, it is also December 2024 before we see a meaningful expansion of the AI features including the long-awaited Chat GPT integration. As such, the powerful iPhone upgrade cycle that we expect to come with "Apple Intelligence" is likely to be a slow burn, with momentum building through 2025 and into 2026. What impressed? The ability of Apple to turn a benign demand environment into double digit EPS growth is impressive. Products growth has been tepid but the higher growth Services business, margin expansion and a buy-back continues to drive EPS growth above 10%. What disappointed? While we appreciate that Apple Intelligence will take time, the pace of the roll-out driving the weaker than expected outlook for 4Q (which is their biggest quarter of the year) was mildly disappointing. However, Apple tend to focus on quality rather than speed, so we do think that their ability to monetise AI across an installed base of 2.2bn active devices is a compelling, multi-year opportunity. Interesting chart? The next phase for Apple is all about an iPhone replacement cycle coupled with an expansion of associated Services revenue. The chart below shows what happened the last time a compelling technology shift occurred, with 5G driving a compression in this replacement cycle. Since the most recent trough in FY21, replacement cycles have shifted out by more than 12 months. A compression of this replacement cycle back towards 4yrs will drive circa 10% EPS upgrades. What are the key risks? There are a few key risks facing Apple in the coming years. Key among these are: What if "Apple Intelligence" is a flop? This would undercut the investment thesis of a compelling technology shift driving customers to upgrade their phone, as well as reduce the ability of Apple to further monetise AI capabilities through their Services business. What about if Apple lose Search payments from Google? The current DOJ case against Google has the potential to eliminate the $20-$25bn of high margin revenue that Google pays Apple to be the default search engine through Safari. While Apple will find a structure to replace at least some of this revenue, it is a potential drag in the short term. Will the phone lose primacy as the key device state? Over the longer term, there is a risk that a different form factor supplants the phone as the dominate device. Meta is pushing down the glasses route and seem to be well ahead currently, but Apple also appear to be on the "visual" path, with the "Vision Pro" potentially just the first step towards a glasses device for Apple. In summary, Apple's ability to monetise their enormous consumer ecosystem is almost unrivalled. They will find a structure through which to monetise Ai, both through device sales but more importantly through an expansion of Ai related Services offerings. There is no company better placed to be the window into Ai for the average consumer. Key takeaway from the result? Margins, margins, margins. Given the scale of the Amazon business, a mild shift in margin outcomes can drive enormous gains in operating income and EPS. Amazon spooked the market during their 2Q24 results which showed margins for their core retail business to be weaker than expected, which was blamed on everything from mix (lower priced "everyday essentials" in baskets) to building extra satellites for their broadband business. However, come the 3Q24 result last week, all was forgotten as Amazon blew those margin expectations (that they ironically had guided to themselves) out of the water. So, the question becomes, will this margin expansion continue? What impressed? The margin outcome in the core retail business was impressive, particularly in the international segment. Despite pressures from mix and what appears to be heightened competition from legacy retailers (eg Walmart) and Chinese players (Temu, Shein), Amazon generated solid topline growth and exceptional margins. The Amazon cloud business AWS also showed a continuing reacceleration driven in part by AI. A combination of the "law of large numbers" plus optimisations had driven compression in cloud growth rates across Amazon (AWS), Microsoft (Azure) and Google (GCP). However, the advent of AI has driven a reacceleration in cloud growth, which is impressive given the base of business is significantly larger. What disappointed? While it may seem unusual to have any source of disappointment in an exceptionally strong result, the variability of the margin outcomes compared to what management expected could indicate a lack of visibility. While a "miss vs expectations" is very happily received when it is an upside surprise, it does raise some concerns that perhaps next time the "surprise" could be the other way.  Interesting chart? Given the scale of the retail business, a shift in margin expectations has a material impact on earnings. A circa 100bps improvement in Retail margins vs current expectations for CY25 would drive a 7% beat in Amazon operating income. What are the key risks? For Amazon, risks are on a couple of key fronts: E-commerce competition: Amazon used to be almost the only game in town when it came to e-commerce, however Covid saw several retailers reshape and improve their e-commerce offerings (facing an existential threat to your survival will do that). Now traditional retailers such as Walmart (who can combine grocery with general merchandise) are making some inroads, while platforms like Shopify can offer alternate paths to market. This is coupled by an increase in competitive intensity from Chinese platforms Temu and Shein. Cloud growth: While AWS has been performing well in recent quarters, they had initially slipped behind Azure in terms of AI functionality. Given the sheer scale of the capex required to build out data centre capacity, continued success in cloud is critical to generate returns on this investment. In summary, Amazon's 3Q24 earnings report highlighted the significant earnings potential of the business and underscored the company's strong market position and attractive consumer offerings. However, it is crucial to closely monitor Amazon's ability to sustain margin improvements and effectively navigate ongoing consumer pressures in the future.

Funds operated by this manager: Alphinity Australian Share Fund, Alphinity Concentrated Australian Share Fund, Alphinity Global Equity Fund, Alphinity Global Sustainable Equity Fund, Alphinity Sustainable Share Fund

Artificial Intelligence will change the world (eventually) Alphinity Investment Management  October 2024

"The risk of underinvesting is dramatically greater than the risk of overinvesting" (Sundar Pichai, Alphabet CEO, 23rd July 2024). This quote from the Alphabet CEO during the Alphabet 2Q earnings call amplified investor concerns around the current Artificial Intelligence ("AI") investment landscape. The technology industry appears to be engaged in a high-stakes race to develop AI infrastructure, while the potential returns on these massive investments remain ambiguous. Given the substantial market share and valuation premiums now commanded by AI-focused companies, there's mounting pressure for these firms to demonstrate tangible returns on their AI investments. Investors are increasingly looking for concrete evidence that the massive capital inflows into AI infrastructure and development will translate into sustainable revenue streams and long-term profitability. Despite market impatience, we are observing encouraging signs of AI's impact starting to emerge from both the revenue and expense sides of businesses. Substantial returns will however take time to materialise. Given the current market dynamics, we remain nimble with our AI exposure in the short term, but unequivocally convinced on the longevity and scale of the AI opportunity over the long term. Where are the returns? Market concerns around overinvesting in AI are not without precedent given the technology sector's history of several technology boom-and-bust cycles: From the 1990's internet era exuberance leading to the dot.com crash, to the recent hype around the metaverse (virtual worlds), Web 3 (decentralised internet vision), and even non-fungible tokens (NFT's). These examples serve as cautionary tales, illustrating how technology hype can outpace real-world applications, leaving a trail of poor returns and crushed share prices in their wake. Current investment levels into AI architecture are extraordinary. Hyperscaler (Microsoft (NASDAQ: MSFT), META (NASDAQ: META), Alphabet (NASDAQ: GOOGL) & Amazon (NASDAQ: AMZN)) capex will rise more than 40% in CY24 and is expected to rise further in CY25 to levels 2.5x what they were in CY20. This level of investment is starting to have an impact on financial returns for these companies, both in terms of cash flow returns and on margins as higher depreciation flowing from this investment begins to bite in the P&L. Hyperscaler Capex ($bn) Returns take time to materialise In any major technological transition - be it internet, cloud computing, or the current wave of generative AI, there is a consistent pattern: infrastructure development precedes widespread application and the realisation of value. The internet evolution provides a compelling case study, where the true value from end applications and the resultant share price movements only started to emerge after 3 years and really gathered momentum after 5 years. Internet Cycle Stock Performance We can see a similar phenomenon play out with generative AI. Cloud AI services are beginning to inflect, as evidenced by recent results showing a reacceleration in cloud demand but several cutting-edge AI applications such as Edge AI, Smart Robots and Multi-Agent Systems are still in development and yet to reach widespread commercial deployment. Where are the end applications? Contrary to the notion that end applications of AI are not yet visible, we're witnessing a robust proliferation of AI-powered solutions across various sectors already emerging just ~20 months after the emergence of GEN AI. While these applications are in their initial phases and will take time to scale, their market potential is substantial. Take for example the M365 co-pilot example: a US$30 subscription fee per month across their 160m high value commercial users, could add $58bn revenue annually (a +23% lift to FY24 revenue). Expansion to the remaining 200m commercial users and integration into broader product offerings offer additional upside. Returns from "efficiencies" The impact of generative AI on business efficiency and productivity is emerging as a transformative force, with potential returns far exceeding initial revenue gains. This trend, while significant, remains underappreciated due to public concerns about AI-driven job displacement. However, real-world applications are already demonstrating substantial benefits across diverse industries. Companies are implementing AI with measurable success. For example: Uber (NASDAQ: UBER) is using gen AI to enhance customer service and marketing efforts; Mercado Libre (NASDAQ: MELI) is optimising capacity planning and fulfillment operations; Wipro (NASDAQ: WIT) is using it to boost software development through code assistance & documentation; Best Buy (NASDAQ: BBY) is deploying AI-powered trouble-shooting assistants. Importantly, companies are beginning to qualify these benefits well beyond the bounds of tech: Walmart's (NASDAQ: WMT) quantified generative AI's contribution to catalogue creation in their recent results call with the CEO stating that: "without the use of generative AI, the work would have required nearly 100 times the current head count to achieve what we did using generative AI" Pfizer (NASDAQ: PFE) is leveraging AI as a key component in a $4bn operating expense reduction initiative; American Express (NASDAQ: AXP) is realising a 30% higher response rate on corporate offers through AI assistance; and L'Oreal reported a 10-15% boost in advertising productivity, by spotting trends (using "Trendspotter") early and marketing to online shoppers. The list goes on. The adoption of generative AI is rapidly expanding, with companies across various sectors reporting emerging and expanding use cases. How to quantify these returns Quantifying the actual returns from generative AI can be a difficult exercise. For example, disaggregating how much of the Meta revenue acceleration comes from product enhancement due to Gen AI is complex, as is product augmentations flowing from its application to existing capabilities. Stepping back to a broader economic perspective, McKinsey undertook a study trying to piece together the incremental value that generative AI could bring. The total value was $6.1tr - $7.9tr annually across specific generative AI use cases and general productivity. Taking specific use cases, McKinsey's comprehensive analysis of generative AI applications provides a detailed roadmap of its potential impact across various business functions. McKinsey identified activities within business functions where generative AI could be applied and then calculated both the efficiency impact (as a % of functional spend) and the aggregate size of the opportunity. Remarkably, 75% of the generative AI impact was across a handful of functions spanning sales, marketing, product R&D, customer operations and software engineering, estimated to be a c$400-500bn impact across each function. Interestingly, we are beginning to get validation of some of these data points in our conversations with company management teams, for example in software engineering the efficiency/cost boost figure of c. 30% is now being discussed. Looking ahead, we will continue to monitor validation points of this return profile, but if this current trajectory of efficiency gains persists across various business functions, it suggests that the substantial investments in AI infrastructure are likely to be more than justified.

Funds operated by this manager: Alphinity Australian Share Fund, Alphinity Concentrated Australian Share Fund, Alphinity Global Equity Fund, Alphinity Global Sustainable Equity Fund, Alphinity Sustainable Share Fund

Global Webcast: Reflecting on a volatile month & 2Q24 results season Alphinity Investment Management  August 2024

Elfreda Jonker and Jonas Palmqvist reflect on what has been happening in markets over the previous month and review key themes from the second quarter of 2024.

Funds operated by this manager: Alphinity Australian Share Fund, Alphinity Concentrated Australian Share Fund, Alphinity Global Equity Fund, Alphinity Global Sustainable Equity Fund, Alphinity Sustainable Share Fund