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小売業における人工知能 (AI)

Artificial Intelligence in Retail - Thematic Research

発行 GlobalData 商品コード 646076
出版日 ページ情報 英文 47 Pages
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小売業における人工知能 (AI) Artificial Intelligence in Retail - Thematic Research
出版日: 2018年04月26日 ページ情報: 英文 47 Pages
概要

当レポートでは、世界の小売業向け人工知能 (AI) の市場について分析し、現時点でのAIの普及状況や活用方法、今後のAIの普及見通し、それに伴う小売業の変化の方向性、関連企業のプロファイル・動向見通しなどを調査しております。

目次

  • 企業
  • 市場動向
    • 技術動向
    • マクロ経済動向
    • 小売業でのAIの活用状況
  • バリューチェーン
    • AIソフトウェア:10種類のカテゴリー
  • 産業分析
    • 技術企業の観点
    • 企業合併・買収 (M&A)
    • タイムライン
  • 小売業に対するAIの影響度
    • 小売業での利用事例 (ケーススタディ)
    • AIベンダーが小売業に売り込む方法
  • 企業部門
    • 上場済み技術企業
    • 非公開の技術企業
    • 小売企業
  • 技術概略
    • 定義
    • 機械学習 (ML) の歴史
    • 深層学習 (DL) はどのように機能するのか?
  • 付録:分析手法
目次
Product Code: GDRTAI-TR-S001

Machine learning is an artificial intelligence (AI) technology which allows machines to learn by using algorithms to interpret data from connected 'things' to predict outcomes and learn from successes and failures.

There are many other AI technologies - from image recognition to natural language processing, gesture control, context awareness and predictive application programming interfaces (APIs) - but machine learning is where most of the investment community's funding has flowed in recent years. It is also the technology most likely to allow machines to ultimately surpass the intelligence levels of humans.

Many companies, like Alphabet, have already become 'AI-first' companies, with machine learning at their core. At the same time, many ML techniques are getting commoditized by being open sourced and pre-packaged into developer toolkits that anyone can use.

This report focuses on Artificial Intelligence in Retail.

Scope:

This report is part of our ecosystem of thematic investment research reports, supported by our "thematic engine". About our Thematic Research Ecosystem -

  • GlobalData has developed a unique thematic methodology for valuing technology, media and telecom companies based on their relative strength in the big investment themes that are impacting their industry. Whilst most investment research is underpinned by backwards looking company valuation models, GlobalData's thematic methodology identifies which companies are best placed to succeed in a future filled with multiple disruptive threats. To do this, GlobalData tracks the performance of the top 600 technology, media and telecom stocks against the 50 most important themes driving their earnings, generating 30,000 thematic scores. The algorithms in GlobalData's "thematic engine" help to clearly identify the winners and losers within the TMT sector. Our 600 TMT stocks are categorised into 18 sectors. Each sector scorecard has a thematic screen, a risk screen and a valuation screen. Our thematic research ecosystem has a three-tiered reporting structure: single theme, multi-theme and sector scorecard. This report is a Multi-Theme report, covering all stocks, all sectors and all themes, giving readers a strong sense of how everything fits together and how conflicting themes might interact with one another.

Reasons to buy:

  • Our thematic investment research product, supported by our thematic engine, is aimed at senior (C-Suite) executives in the corporate world as well as institutional investors.
  • Corporations: Helps CEOs in all industries understand the disruptive threats to their competitive landscape
  • Investors: Helps fund managers focus their time on the most interesting investment opportunities in global TMT.
  • Our unique differentiator, compared to all our rival thematic research houses, is that our thematic engine has a proven track record of predicting winners and losers.

Table of Contents

PLAYERS

TRENDS

  • Technology trends
  • Macro-economic trends
  • Applications of AI in Retail

VALUE CHAIN

  • Ten categories of AI software

INDUSTRY ANALYSIS

  • The tech sector's angle
  • M&A
  • Timeline

IMPACT OF AI ON RETAIL

  • Retail case studies
  • How AI vendors can sell into the retail sector
  • Recommendations for IT vendors

COMPANIES SECTION

  • Listed tech companies
  • Privately held tech companies
  • Retail companies

TECHNOLOGY BRIEFING

  • Definitions
  • History of machine learning
  • How does deep learning work?

APPENDIX: OUR "THEMATIC" RESEARCH METHODOLOGY