The Morgan Stanley AI Guidebookpdf
The Morgan Stanley AI Guidebookpdf
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  1. M FoundationGlobal TechnologyIntroducing The Morgan Stanley AI GuidebookOur new AI Guidebook provides 1) A list of notable AI-centered macro research, 2) Stock/sector specific AI-related work and views, and 3) An updated AI presentation analyzing the foundational tech, how we view the tech leaders vs market, and context for investing in this cycle vs past tech cycles.Morgan Stanley does and seeks to do business with companies covered in Morgan Stanley Research. As a result, investors should be aware that the firm may have a conflict of interest that could affect the objectivity of Morgan Stanley Research. Investors should consider Morgan Stanley Research as only a single factor in making their investment decision.For analyst certification and other important disclosures, refer to the Disclosure Section, located at the end of this report.+= Analysts employed by non-U.S. affiliates are not registered with FINRA, may not be associated persons of the member and may not be subject to FINRA restrictions on communications with a subject company, public appearances and trading securities held by a research analyst account. June 14, 2023 08:19 PM GMT
  2. M Foundation2ContributorsMorgan Stanley & Co. LLCBrian Nowak, CFAEquity Analyst+1 212 761-3365Brian.Nowak@morganstanley.comMorgan Stanley & Co. LLCKieran Kenny, CFAResearch Associate+1 212 296-5137Kieran.Kenny@morganstanley.comMorgan Stanley & Co. LLCKeith Weiss, CFAEquity Analyst+1 212 761-4149Keith.Weiss@morganstanley.comMorgan Stanley & Co. LLCJoseph MooreEquity Analyst+1 212 761-7516Joseph.Moore@morganstanley.comMorgan Stanley & Co. LLCMeta A MarshallEquity Analyst+1 212 761-0430Meta.Marshall@morganstanley.comMorgan Stanley & Co. LLCErik W WoodringEquity Analyst+1 212 296-8083Erik.Woodring@morganstanley.comMorgan Stanley & Co. International plc+Edward StanleyEquity Strategist+44 20 7425-0840Edward.Stanley@morganstanley.comMorgan Stanley & Co. LLCLauren SchenkEquity Analyst+1 212 761-4143Lauren.Schenk@morganstanley.comMorgan Stanley & Co. LLCMatthew CostEquity Analyst+1 212 761-7252Matthew.Cost@morganstanley.comMorgan Stanley & Co. LLCChloe A CurrieResearch Associate+1 212 761-2158Chloe.Currie@morganstanley.com
  3. M FoundationMorgan Stanley Research37How AI is Set to Transform Technology, Business and the Investing Landscapes25Morgan Stanley AI Research30Valuation Methodology and Risks Contents
  4. M Foundation4Introducing The Morgan Stanley AI GuidebookThe Morgan Stanley AI Guidebook. The pace of AI advancement and level of macro economic, sector-specific and stock specific AI debates remain incredibly high. Today we introduce the Morgan Stanley AI Guidebook which provides 1) A comprehensive list of notable AI-centered thematic/macro research, 2) Our stock/sector specific AI-related work, and 3) Our latest AI presentation materials which provide an AI founda-tional background, analyze how the market and we view the positioning of leading tech companies, and lay out some historical context for how to invest in this tech cycle compared to past cycles. We plan to refresh and update the Morgan Stanley AI Guidebook on a recurring basis going forward.Internet: Covered by Brian NowakInternet: Sizing the $6 Trillion AI Internet Opportunity and Who Will Capture It (2 Mar 2023)•We detail our views on accelerating AI trends driving new consumer use cases and changes in behavior. We outline potential new/improved search tools, AI assistants, stronger social/e-commerce recommendation engines, next genera-tion content creation tools, more optimized shared economy marketplaces, and more.•Analyzing our NEXT framework, scale and investment, we also detail 11 companies best positioned to drive/benefit from AI (including GOOGL/AMZN/META/SSTK/TTD/U), 14 likely to face challenges, and 10 with unresolved debates.Internet: Building JARVIS: Will GOOGL, AMZN, AAPL or META Win the AI Assistant Race? (10 May 2023)•We dive into AI-based assistants, which seem on the way. Our analysis of hardware, data and AI tech speaks to GOOGL's leading opportunity here, the behavior changes needed for AMZN/META to lead, and the AI uncertainty around AAPL. We also lay out potential financial upside and catalysts from here for each player.Internet: Structural AI-Driven Efficiency Ahead? (24 Apr 2023)•We detail how next gen AI tools are set to lead to internal productivity gains (within engineering, sales and G&A), why we look for big tech leaders (META/GOOGL/AMZN) to lead in these areas through slower hiring and higher budgeting dis-cipline going forward and potential EBIT upside from increased efficiency focus.AI Primers and Macro-Economic Work:Global Technology: How is AI Set to Change the Tech Landscape...and What’s NEXT? (2 Mar 2023)•Our AI primer deck analyzes the AI tech layers and players, from silicon to software. Our NEXT framework shows how AI could accelerate tech diffusion across the economy, with unique, scaled data and investment critical in the AI age ahead. We also discuss 8 key unresolved debates to watch from here that could impact how and at what pace the AI eco-system develops.Economics, Technology & Public Policy: The Great Productivity Race (25 Apr 2023)•After an extended period of sluggish growth, we think pro-ductivity is poised to rebound. Tight labor markets and supply chain disruption in the multipolar world make higher produc-tivity an imperative. Our economists and industrials teams show how technology diffusion can drive change.Sustainability: AI & ESG: Our Thoughts on Benefits, Risks, Investing, and Regulation (3 Apr 2023)•We analyze the range of ESG implications from the coming AI evolution, including the many ESG-related benefits and risks/negative implications. We then layout our approach on how to invest in AI-driven ESG opportunities, and end with a deep dive on regulation, frameworks, and guidance globally.Thematics: Tech Diffusion: 10 Lessons from 100 Years (1 Jun 2023)•The breadth, depth and speed of change posed by AI are leaving many investors looking to history for a guide on stocks, even if an imperfect one. History tends to rhyme for businesses' valuations and consensus earnings both to the upside and downside.
  5. M FoundationMorgan Stanley Research5Alphabet Inc.: How Can AI Drive Upside to Estimates and Key Catalysts Ahead (16 Apr 2023)•We detail expected AI-driven behavior change that we see leading to more durable multi-year e-commerce and online ad growth, and why we believe GOOGL is positioned to drive and benefit from these changes. We also lay out key catalysts ahead and why we remain bullish. Meta Platforms Inc: How Can AI Drive Upside to Estimates and Key Catalysts Ahead (23 Apr 2023)•We see META benefitting from AI-driven enhancements across core Facebook and Instagram, leading to more durable multi-year revenue growth as generative AI tools should drive engagement, ad unit conversion and platform utility. We also see call options like paid verification supporting growth and outline key META AI-based catalysts from here. Software: Covered by Keith WeissSoftware: Public Cloud 2.0: Building Towards a $2.5 Trillion Opportunity (16 Mar 2023)•Declining costs of compute/software development, matched with ubiquity of data and expanding capabilities of software driven by recent AI advancements will shift the pendulum back to customers building new capabilities, propelling cloud market from $500bn + today to $2.5tr over next decade, implying a 17% CAGR.Microsoft: Co-Piloting the Way to Productivity Gains (17 Mar 2023)•The demo of Microsoft 365 Copilot, powered by an OpenAI-based LLM well illustrates the large potential for productivity gains driven by Generative AI. While investors have to wait 'a few' months before pricing and GA are announced, the potential value unlock for MSFT is readily apparent today.Cybersecurity: Can Microsoft Co-Pilot the Way to Security Automation? (29 Mar 2023)•Advancements in AI have potential to automate and disrupt an >$100B market for security services. While Microsoft's new Security Copilot (a new AI assistant to help security pro-fessionals quickly summarize and make sense of threat intel-ligence, investigate incidents and help with reporting) aims to improve productivity for security users/teams, we think the features showcased are more evolutionary vs. revolutionary so far. Semiconductors: Covered by Joe Moore, Shawn Kim, and Charlie Chan NVIDIA Corp.: Upgrading to OW as large language model enthu-siasm is transforming cloud capex (16 Mar 2023)•Having been EW for a large move in the stock, we still see indi-cations that LLM enthusiasm is turning into stronger spending both near term and long term; we have been too data point oriented around a positive bigger picture, but the narrative is too strong to remain on sidelines and the develop-ment of generational AI is too much of a megatrend to get distracted by tactical concerns. The stock will continue to be hard to ignore in an otherwise challenging semiconductor environment.Advanced Micro Devices: AI opportunity looks to be multiples of our initial assessment (11 May 2023)•We have tried to set conservative forecasts for AMD's AI, given historical false starts, but higher price points plus supply chain commentary is pointing to an opportunity that is multiples of our initial target. We continue to hear about more aggressive investment in both training and inference and AMD's share of this opportunity seems more tangible and durable.
  6. M Foundation6Asia Semiconductors: Tech Diffusion – Fulfilling the surge in AI demand with custom chips (11 Jun 2023)•We believe GP GPUs (provided by NVIDIA and AMD) demand will continue to expand in 2024e, but AI ASICs (or custom chips) may outgrow GP GPUs given lower costs reaching scale. We view TSMC, Alchip, GUC, Andes, and ASM Pacific as key enablers in Asia.Networking & Hardware: Covered by Meta Marshall and Erik WoodringGlobal Technology: Cloud Optimization: Short Term Pain for Long Term Gains (12 Apr 2023)•Morgan Stanley conducted a proprietary AlphaWise survey to look at duration and long term impacts of cloud optimiza-tion. Survey points to slightly longer digestion period than expected, but nearly 25% higher public cloud adoption longer term. Microsoft and Google would be the biggest share gainers as cloud growth resumes given AI expertise, but there is a longer tail of beneficiaries enabling hybrid future; chal-lenged vendors are still largely premise technology pro-viders.Telecom & Networking Equipment: AI Workloads: A Look at the Networking Opportunity (2 Mar 2023)•With GPU workloads the fastest growing part of cloud data center spend, networking architectures need adaptations to accommodate increased bandwidth. We estimate cloud net-working TAM could grow to $24bn as a result, increasing Ethernet TAM ~50%. ANET is the biggest branded benefi-ciary.Tech Hardware Pulse: What Investors Are Asking: What Is the AI Opportunity For Hardware Companies? (24 Feb 2023)•Over a multi-year period, generative AI could drive greater demand for more powerful compute (GPU-enabled servers, AI-integrated PC CPUs) and data storage (flash HDDs). AAPL, STX, DELL, and IBM are names we believe could benefit from this shift, but the P&L impact is still in its early days. Tech Diffusion and Non-Tech Industry AI Work:Freight Transportation: AI in Freight Transportation: The Final Piece of the Automation Puzzle? (24 May 2023)•We have long believed the Freight Transportation space is on the cusp of a generational shift driven by disruptive technolo-gies including Autonomous, EV, blockchain and drones. AI is the latest one of these potentially transformative technolo-gies to emerge – and perhaps the most powerful to-date.
  7. M FoundationMorgan Stanley Research7How AI is Set to Transform Technology, Business and the Investing LandscapesJune 14, 2023Morgan Stanley does and seeks to do business with companies covered in Morgan Stanley Research. As a result, investors shouldbeaware that the firm may have a conflict of interest that could affect the objectivity of Morgan Stanley Research. Investors should consider Morgan Stanley Research as only a singlefactor in making their investment decision.For analyst certification and other important disclosures, refer to the Disclosure Section, located at the end of this report.Morgan Stanley ResearchNorth America
  8. M Foundation8of this lineof this lineSource: Morgan Stanley ResearchTechnology and Compute Platforms Building Upon Themselves For Over 50 Years...Devices / Users (MM in Log Scale)Computing Cycles Over Time, 1960s -TodayMinicomputerPCDesktopInternet Data EraMainframeMobileInternet196019701980199020002010202020301M+ Units10M+Units 100M+Units 1B+ Units/ Users Billionsof Units 110010,0001,000,000Tens ofBillionsof Units -Transformers-CPU GPU-Data-Cloud & MobileReasons This Is Different
  9. M FoundationMorgan Stanley Research9of this lineof this line200 13 1 3 - 50 100 150 200 2501995200020052010201520202025Users Added Per Day (Thousands)Launch DateSource: Company data, Statista, Morgan Stanley Research...Driving an Inflection in AI Adoption as the Data Era Gains Momentum...Users Added Per Day From Launch to One Million Users
  10. M Foundation10of this lineof this lineSource: OurWorldInData, Various Websites, Morgan Stanley Research. Note: 3yrs for the AI Era implies that the time to 50% US Household adoption is similarly cut in half from the previous cycle. ...and Representing a Continuation of Long-Term Tech Adoption TrendsTime to 50% US Household Adoption Has Halved Each Cycle42 Years20 Years12 Years6 Years3 Years?454035302520151050Second Industrial RevolutionPC EraDesktop Internet EraMobile Internet EraAI EraYearsYears Until 50% US Household Adoption of New Technologies
  11. M FoundationMorgan Stanley Research11of this lineof this line...With a Case for AI Diffusion Reaccelerating Productivity GrowthSource: FRED, Morgan Stanley Research. Note: Annualized performance is based on the time period between the technology introduction and peak 5yr rolling avg. productivity growth.•New AI-based technologies could drive incremental productivity and can coincide with periods of strong market returns
  12. M Foundation12of this lineof this lineThe Roadmap to Monetizing Cycles: The Mobile Internet as a Case Study•Mobile Internet Cycle Stock Performance•Indexed Performance Relative to S&P 5003Source: Factset, Morgan Stanley ResearchSemiconductorsInfrastructure / DevicesSoftware + Services12
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