24.03 Liontrust Global Innovation Report - The Rise of AI 04.24 - Flipbook - Page 11
Are the companies behind AI technology making
any money yet?
AI sits on the shoulders of the past three major information
technologies – the internet, mobile and cloud – which
means that some of the leading companies in these
technologies (including the Magnificent 7) are currently
leading in AI and already generating incremental
profits. For example, Nvidia (with around 85% AIrelated revenues) generated over $6 billion in net profit
last year, while Broadcom (with around 25% AI-related
revenues) generated over $14 billion in net profit.
Moving up the tech stack, although value creation will
take time to disperse up to the software application
layer, pioneers in AI like Adobe and Salesforce are
already successfully monetising AI.
Are technology company valuations currently high
due to expectations for AI?
While there are always over and undervalued
companies in the market, we believe that overall current
technology valuations are justified by fundamentals.
Although AI is sometimes compared with the 2000
dotcom bubble, valuations are nowhere near the
levels reached in that episode. In 1999, the S&P 500
IT sector traded at a forward price-to-earnings ratio
of 75 times, representing a 3 times premium to the
overall market; today, the S&P 500 IT sector trades
at about 28 times and a 1.4 times premium to the
overall S&P 500 index and the Nasdaq 100 index
trades at a 1.3 times premium.We believe the current
valuations are justified given strong fundamentals (the
technology sector has the highest ROIC and lowest
leverage of all sectors) and superior growth, which
will be further aided by AI tailwinds.
Is AI just the technology sector?
General purpose technologies such as AI impact most
sectors, not just technology companies. Business use
cases among those that stand to benefit the most from
AI fall across four areas: customer operations, marketing
and sales, software engineering, and R&D – functions
that span the vast majority of companies across industries.
General purpose
technologies such as AI
impact most sectors,
not just technology companies
Life sciences is a sector that could see the biggest
impact as a percentage of revenues. For example,
drugs could be discovered and validated much faster
using AI. Meanwhile, AI prompts are also helping to
drive digital sales for consumer-facing brands such as
McDonald’s, and the role of virtual assistants present
meaningful opportunities for customer-engagement
heavy platforms like Airbnb.
Will the Magnificent 7 be the main winners in AI or
are there opportunities for smaller companies too?
The Magnificent 7 companies are at the forefront of AI.
Having suffered significant stock price declines in 2022,
they had a strong 2023 as the new technology cycle
began. While it is rare for the leaders of a previous
cycle to transition successfully into the next one, these
companies are well-positioned to benefit from AI due to
their leveraging of the internet, mobile and cloud, and
their access to data, capital and innovative capabilities.
Yet, the opportunities in AI extend beyond the tech
giants. AI will have broad and transformative effects.
We expect companies far below the Magnificent
7 to compete in many different ways. Their agility
and ability to start from scratch, alongside the opensource nature of AI tools, allow them to focus on
niche AI areas, develop unique applications, or
solve specific problems.
How does generative AI differ from standard AI?
Generative AI is a significant step forward in AI
capabilities. While standard AI uses data to make
predictions, such as recommendations for consumers
based on data on their previous and other activity,
generative AI uses data to create original content, in
the fields of language, imagery, sounds and video.
The increased capabilities of generative AI over
and above those of standard AI lie crucially in its
ability to contextualise text and other data. This in turn
has been enabled by rapid progress in computing
power and methodological developments in handling
natural language in all its complexity, particularly the
introduction of the Transformer model in 2017.
The emergence of generative AI means that AI has
become applicable to a much larger range of tasks
than before and is likely to have much larger effects
on economic activity.
What are the main risks of AI?
Businesses that delay AI adoption risk falling behind
competitors that do not delay. Conversely, embracing
AI brings its own set of challenges, including the need
for significant investment in technology and talent, the
high energy intensity associated with accelerated
computing, potential biases in algorithms, and
navigating data privacy and ethical use.
From a social perspective, risks include the misuse of
AI by bad actors, such as in cybersecurity breaches,
deepfake creation, and digital scams, underscoring
the need for robust ethical and safety regulations.
AI is likely to displace jobs but also drive economic
growth and create new opportunities.
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