MARKET INSIGHTS

Weekly market commentary

02-Dec-2024
  • BlackRock

Getting active to identify AI winners

BlackRock Bottom Line

Weekly video_20241125

Wei Li

Global Chief Investment Strategist, BlackRock

SCRIPT

Title: Three phases of the AI opportunity

Tech companies are investing heavily in developing artificial intelligence. How can investors map the course on this emerging trend? Here are three key phases of AI’s revolution that we think could help guide investors.
We see the AI revolution unfolding in three phases - buildout, adoption and transformation.
Let’s start with buildout. This is where we are now. Tech companies are investing heavily in the race to build the infrastructure that AI needs. Data centers that provide AI capabilities are more costly than traditional data centers across all three of the main cost components: building the data center itself, installing chips and servers and powering them. We see big cloud providers and chip producers benefiting, along with firms in the utilities, energy, industrials, materials and real estate space that provide key inputs for this buildout.
Moving to phase 2: adoption. As data centers come online and AI matures, adoption across industries is expected to accelerate. Companies are still learning how to harness AI. We think they will invest in AI to reshape operations and drive growth, with winners emerging beyond the tech sector in industries like healthcare, financials and communication services.
And finally, phase 3: transformation. This is where companies could unlock the full value of AI adoption, as broad productivity gains and new business models and industries emerge. The magnitude and timing of these changes remain uncertain – and it’s possible they don’t materialize at all if adoption is not as widespread as expected. Identifying winners here is particularly challenging — some of them may not even exist yet. 
The bottom line is the AI opportunity is just starting. We think investors should prepare for the transformation phase, but the opportunities from the buildout phase and in early adopters are here and now.

Our AI view

We believe AI could radically reshape economies and markets. Identifying the full slate of potential beneficiaries calls for an active investment approach.

Market backdrop

U.S. stocks edged up near record highs last week, with Nvidia’s results highlighting the AI buildout. U.S. bond yields held near six-month highs.

Week ahead

We eye October U.S. core PCE. Recent wage data shows gains remain high and suggests core inflation is unlikely to cool near the Federal Reserve’s 2% target.

Nvidia’s Q3 corporate earnings results show the buildout of artificial intelligence (AI) data centers is powering ahead as tech firms race to build the infrastructure AI needs. We think AI could eventually radically reshape economies and markets. Yet uncertainty over how AI evolves from here raises big questions. We use our three-phase framework – buildout, adoption, transformation – to track the AI revolution. Taking an active approach helps us identify and capture investment opportunities.

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Traditional vs. AI data centers
Range of estimates of data center buildout costs

The chart shows that AI data centers are more costly to build than traditional ones.

Forward looking estimates may not come to pass. Source: BlackRock Investment Institute, Thunder Said Energy, November 2024. Note: The chart shows the estimated costs across three key components for data centers. Data center infrastructure relates to the full infrastructure build, excluding the cost of chips and servers. Power supply costs relate to the building of facilities needed to power data centers.

In the buildout phase underway, tech giants are pouring record amounts of capital into AI. Chips are the single largest cost and Nvidia is one of the big winners of that demand. Some of the most powerful chips can cost $40 billion per gigawatt versus $10-20 billion for traditional chips, according to Thunder Said Energy. Advanced chips are one reason AI data centers – the backbone of the buildout – are costlier than traditional ones. See the chart. Spending on traditional and AI data centers combined could top U.S. $700 billion annually by 2030, industry estimates show. All this spending could add to inflation, including via higher near-term energy costs given AI’s huge power needs. Eventually, AI could boost energy efficiency, offsetting some of the initial spike in energy demand. Yet those savings can come only after mass AI adoption, a process that will take time.

We think investment in AI could rival the amount seen in the industrial revolution – especially once including the spending on energy infrastructure as part of both the data center buildout and the low-carbon transition. Investment of this magnitude demands significant financing, creating a key funding role for capital markets and private markets. Yet private markets are complex and not suitable for all investors. We see big cloud providers and chip producers as the buildout’s main beneficiaries – particularly mega cap tech companies, whose unmatched resources and tech expertise give them a competitive advantage.

AI's big questions

Questions around AI overinvestment are valid. Yet we think this should be assessed in aggregate, given AI's potential to unlock new revenue streams across the whole economy. Mega cap tech does not look overextended for now. Comparisons to the dot-com era fall short, according to BlackRock’s Systematic Active Equity team: Analysis of hundreds of metrics on valuations, earnings and other features reveals few similarities between now and then. Beyond tech, other likely beneficiaries of the buildout include companies in the utilities, energy, industrials, materials and real estate sectors providing key inputs.

What comes after the buildout raises more big questions. Part of AI’s promise hinges on its ability to drive a productivity boom. Near term, we expect moderate productivity gains as AI reshapes specific tasks. Longer term, AI could accelerate the process of generating new ideas and discoveries, with far-reaching implications for innovation and growth. Much depends on how rapidly AI is adopted across industries. Broad adoption could alter the makeup of the economy by shifting labor and resources, creating new jobs and industries. Sectors like finance and IT could benefit as early adopters. If adoption happens too quickly, it could drive inflation as demand grows faster than resources can be reallocated and workers reskilled. Yet it is difficult now to imagine all of the future AI use cases. Navigating this uncertainty calls for an active investment approach, in our view. Private markets can provide an opportunity to invest in potential winners before they are publicly listed.

Our bottom line

Investment opportunities in the AI buildout expand beyond tech into sectors providing key energy, infrastructure and data center inputs. Uncertainty beyond the buildout calls for an active approach to identify future beneficiaries.

Market backdrop

U.S. stocks edged up last week, hovering just off record highs. Nvidia’s strong Q3 corporate earnings results show robust demand for its chips, a sign the AI buildout is powering ahead. Flash PMIs for November offered a glimpse into uneven global growth: The U.S. composite PMI showed growth accelerating further, while the euro area PMI showed activity shrinking and hit 10-month lows. U.S. 10-year Treasury yields were flat at 4.41%, sticking near their six-month peak.

This week, we get October U.S. core PCE, the Federal Reserve’s preferred inflation measure. We eye core services inflation for clues on where core inflation ultimately settles. Recent wage data shows gains remain elevated and suggests core inflation is unlikely to cool near the Fed’s 2% target. Markets have been pricing out Fed rate cuts — and moving closer to our view — as it becomes clearer that inflation pressures could prove persistent.

Week ahead

The chart shows that gold is the best performing asset year-to-date among a selected group of assets, while Brent crude is the worst.

Past performance is not a reliable indicator of current or future results. Indexes are unmanaged and do not account for fees. It is not possible to invest directly in an index. Sources: BlackRock Investment Institute, with data from LSEG Datastream as of Nov. 21, 2024. Notes: The two ends of the bars show the lowest and highest returns at any point year to date, and the dots represent current year-to-date returns. Emerging market (EM), high yield and global corporate investment grade (IG) returns are denominated in U.S. dollars, and the rest in local currencies. Indexes or prices used are: spot Brent crude, ICE U.S. Dollar Index (DXY), spot gold, MSCI Emerging Markets Index, MSCI Europe Index, LSEG Datastream 10-year benchmark government bond index (U.S., Germany and Italy), Bank of America Merrill Lynch Global High Yield Index, J.P. Morgan EMBI Index, Bank of America Merrill Lynch Global Broad Corporate Index and MSCI USA Index.

Nov. 26

U.S. consumer confidence survey

Nov. 27

U.S. core PCE; U.S. durable goods

Nov. 29

Euro area inflation data; Japan unemployment data

Big calls

Our highest conviction views on tactical (6-12 month) and strategic (long-term) horizons,
November 2024

Reasons
Tactical
AI and U.S. equities We see the AI buildout and adoption creating opportunities across sectors. We get selective, moving toward beneficiaries outside the tech sector. Broad-based earnings growth and a quality tilt make us overweight U.S. stocks overall.
Japanese equities A brighter outlook for Japan’s economy and corporate reforms are driving improved earnings and shareholder returns. Yet the drag on earnings from a stronger yen and some mixed policy signals from the Bank of Japan are risks.
Income in fixed income The income cushion bonds provide has increased across the board in a higher rate environment. We like quality income in short-term credit. We’re neutral long-term U.S. Treasuries.
Strategic
Private markets We see opportunities in infrastructure equity due to attractive relative valuations and mega forces. For income, we prefer direct lending given more attractive yields than in public credit.
Fixed income granularity We prefer intermediate credit, which offers similar yields with less interest rate risk than long-dated credit. We also like short-term government bonds, and UK long-term bonds.
Equity granularity We favor emerging over developed markets yet get selective in both. EMs at the cross current of mega forces – like India and Saudi Arabia – offer opportunities. In DM, we like Japan as the return of inflation and corporate reforms brighten our outlook.

Note: Views are from a U.S. dollar perspective, November 2024. This material represents an assessment of the market environment at a specific time and is not intended to be a forecast of future events or a guarantee of future results. This information should not be relied upon by the reader as research or investment advice regarding any particular funds, strategy or security.

Tactical granular views

Six to 12-month tactical views on selected assets vs. broad global asset classes by level of conviction, November 2024

Legend Granular

Our approach is to first determine asset allocations based on our macro outlook – and what’s in the price. The table below reflects this and, importantly, leaves aside the opportunity for alpha, or the potential to generate above-benchmark returns. We don’t think this environment is conducive to static exposures to broad asset classes but creates more space for alpha.

Past performance is not a reliable indicator of current or future results. It is not possible to invest directly in an index. Note: Views are from a U.S. dollar perspective. This material represents an assessment of the market environment at a specific time and is not intended to be a forecast or guarantee of future results. This information should not be relied upon as investment advice regarding any particular fund, strategy or security.

Jean Boivin
Head – BlackRock Investment Institute
Wei Li
Global Chief Investment Strategist – BlackRock Investment Institute
Raffaele Savi
Global Head of Systematic — BlackRock
Nicholas Fawcett
Senior Economist – BlackRock Investment Institute