Difference between revisions of "Case Studies"
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|title=PRIMO.ai | |title=PRIMO.ai | ||
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| − | |keywords=artificial | + | |keywords=AI case studies, AI use cases, artificial intelligence applications, machine learning use cases, generative AI use cases, enterprise AI, AI by industry, AI adoption, AI ROI, real-world AI, AI implementation |
| − | |description= | + | |description=A directory of real-world artificial intelligence case studies and use cases, organized by industry and business function, with links to major public case-study libraries. |
}} | }} | ||
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| − | + | [https://www.youtube.com/results?search_query=ai+case+study+enterprise+use+cases YouTube] | |
| − | + | [https://www.quora.com/search?q=AI%20case%20study%20use%20cases%20enterprise ... Quora] | |
| − | + | [https://www.google.com/search?q=ai+case+study+enterprise+use+cases ...Google search] | |
| − | + | [https://news.google.com/search?q=ai+case+study+enterprise+use+cases ...Google News] | |
| − | + | [https://www.bing.com/news/search?q=ai+case+study+enterprise+use+cases&qft=interval%3d%228%22 ...Bing News] | |
| − | |||
| − | |||
| − | |||
| − | |||
| − | + | * [[Conversational AI]] ... [[ChatGPT]] | [[OpenAI]] ... [[Gemini]] | [[Google]] ... [[Claude]] | [[Anthropic]] ... [[Bing/Copilot]] | [[Microsoft]] ... [[Apple| Siri | Apple]] ... [[Meta]] ... [[Perplexity]] ... [[You]] ... [[phind]] ... [[Grok]] | [https://x.ai/ xAI] ... [[Groq]] ... [[Ernie]] | [[Baidu]] ... [[DeepSeek]] ... [[Alibaba]] | |
| − | * [[ | + | This page indexes '''real-world deployments''' of AI — what organizations actually built, what it cost them, and what it returned. Use the libraries below for documented implementations, and the industry index further down to jump to PRIMO.ai coverage of a specific domain. |
| − | * [[ | + | |
| + | == Case Study Libraries == | ||
| + | |||
| + | Searchable collections of documented, named-organization deployments. | ||
| + | |||
| + | * [https://bestpractice.ai/ai-use-cases/case-studies AI Use Case & Case Study Library | Best Practice AI] ... The largest curated collection of its kind — 1,171 case studies and 972+ validated use cases, filterable by 40+ industries and 18+ business functions. Each case study links to the generalized use-case pattern behind it. Start here. | ||
| + | ** [https://bestpractice.ai/ai-use-cases/industries Browse by industry] | ||
| + | ** [https://bestpractice.ai/ai-use-cases/functions Browse by business function] | ||
| + | * [https://cloud.google.com/transform/101-real-world-generative-ai-use-cases-from-industry-leaders Real-world gen AI use cases from the world's leading organizations | Google Cloud] ... Named-customer deployments organized by 11 industry groups and six [[Agents/Assistants|Agent]] types (Customer, Employee, Creative, Code, Data, Security). First published April 2024 and expanded repeatedly since; check the "last updated" stamp, as the count grows with each Cloud Next. | ||
| + | * [https://cloud.google.com/blog/products/ai-machine-learning/real-world-gen-ai-use-cases-with-technical-blueprints 101 real-world gen AI use cases with technical blueprints | Google Cloud] ... The engineering companion to the above: architectural patterns and reference tech stacks for each scenario, across 10 industry groups. | ||
| + | * [https://topai.tools/usecases AI Tools Use Cases | TopAI.tools] ... 333 task-level themes across business, personal, and digital categories. A '''tool directory''' rather than a case-study library — useful for "what software does this," not "who deployed it and what happened." | ||
| + | * [https://en.wikipedia.org/wiki/Applications_of_artificial_intelligence Applications of Artificial Intelligence | Wikipedia] ... Broad, well-cited survey of application domains. | ||
| + | |||
| + | === Research & Benchmarks === | ||
| + | |||
| + | For adoption rates, investment figures, and measured outcomes rather than individual deployments. | ||
| + | |||
| + | * [https://hai.stanford.edu/ai-index/2026-ai-index-report The 2026 AI Index Report | Stanford HAI] ... Ninth edition, 400+ pages across nine chapters (R&D, Technical Performance, Responsible AI, Economy, Science, Medicine, Education, Policy, Public Opinion). The standard neutral reference for AI adoption and economic-impact data. | ||
| + | * [https://www.wired.com/category/artificial-intelligence/ The Artificial Intelligence Database | Wired] ... Ongoing journalism on AI deployments and their consequences. | ||
| + | |||
| + | === Historical (pre-generative AI) === | ||
| + | |||
| + | Retained for the analytical frameworks, which hold up better than the specific examples. Treat the company examples as period documents. | ||
| + | |||
| + | * [https://www.mckinsey.com/featured-insights/artificial-intelligence/notes-from-the-ai-frontier-applications-and-value-of-deep-learning Notes from the AI frontier: Applications and value of deep learning | McKinsey Global Institute, April 2018] ... Maps AI techniques to eight problem types (classification, continuous estimation, clustering, optimization, anomaly detection, ranking, recommendations, data generation) across 400+ use cases in 19 industries and nine business functions. The problem-type taxonomy remains the most useful part. | ||
| + | * [https://wiki.pathmind.com/use-cases Deep Learning, Machine Learning & AI Use Cases | Chris Nicholson, Pathmind A.I. Wiki] ... Concise mapping of deep-learning capabilities to sectors. Site is no longer maintained (last copyright 2023). | ||
| + | * [https://www.forbes.com/sites/forbestechcouncil/2018/09/27/15-business-applications-for-artificial-intelligence-and-machine-learning/ 15 Business Applications For Artificial Intelligence And Machine Learning | Forbes Technology Council, September 2018] ... Practitioner accounts from 15 CIOs and CTOs. Note that Forbes CommunityVoice is fee-based membership content, not editorial reporting. | ||
| + | |||
| + | <hr> | ||
| + | |||
| + | <b>What challenge(s) can your AI investment solve?</b> | ||
| + | |||
| + | * increase revenue ([[Marketing|marketing]]) | ||
| + | * more competitive ([[Moonshots|gain capability]]) | ||
| + | * increase performance ([[Anomaly Detection|detection]], [[Robotics|automation]], [[Astronomy|discovery]]) | ||
| + | * reduce costs ([[Agriculture|optimization]], [[Operations & Maintenance|predictive maintenance]], [[Forecasting|reduce inventory]]) | ||
| + | * [[Drug Discovery|time reduction]] | ||
| + | * provide personalization ([[Recommendation|recommendations]]) | ||
| + | * [[Risk, Compliance and Regulation|avoid risk of non-compliance]] | ||
| + | * better communication (user interface, [[Natural Language Processing (NLP)#Natural Language Understanding (NLU)|natural-language understanding]], [[Telecommunications]]) | ||
| + | * broader and better integration ([[Internet of Things (IoT)]], [[Smart Cities|smart cities]]) | ||
| + | * or other outcome(s) such as below... | ||
| + | |||
| + | == Industry & Domain Index == | ||
| + | |||
| + | * [[Market Trading]] | ||
* [[Sports]] | * [[Sports]] | ||
| + | ** [[Sports Prediction]] | ||
* [[Gaming]] | * [[Gaming]] | ||
* [[Toys]] | * [[Toys]] | ||
* [[Social Science]] | * [[Social Science]] | ||
| − | ** [[ | + | ** [[Journalism]]/News |
** [[Marketing]] | ** [[Marketing]] | ||
** [[Religion]] | ** [[Religion]] | ||
** [[Education]] | ** [[Education]] | ||
| − | ** [ | + | ** [[Art]] |
| − | |||
** [[Music]] | ** [[Music]] | ||
| − | |||
** [[Photography]] | ** [[Photography]] | ||
| − | ** [[ | + | ** [[Video/Image|Video]] & Movie Entertainment |
| − | ** [[ | + | ** [[Writing/Publishing]] |
| − | * [ | + | ** [[Fashion]] |
| + | ** [[Fabrics & Textiles]] | ||
| + | * [[Project Management]] | ||
* [[Client Engagement]] | * [[Client Engagement]] | ||
| − | * [[Human Resources]] | + | * [[Human Resources (HR)]] |
| − | * [[Personal | + | * [[Personal Productivity]] |
| − | * [[ | + | ** [[Personal Companions]] |
| − | * [[ | + | *** [[Agents/Assistants]] ... [[Robotic Process Automation (RPA)|Robotic Process Automation]] ... [[Personal Companions]] ... [[Personal Productivity|Productivity]] ... [[Email]] ... [[Negotiation]] ... [[LangChain]] |
| − | * [ | + | ** [[Email]] |
| − | * [[Language Translation]] | + | ** [[Transhumanism]] |
| + | * [[Natural Language Processing (NLP) | Language]] | ||
| + | ** [[Animal Language]] | ||
| + | ** [[Language Translation]] | ||
* [[Travel & Tourism]] | * [[Travel & Tourism]] | ||
* [[Hospitality, Food, and Spirits]] | * [[Hospitality, Food, and Spirits]] | ||
| − | + | * [[Quantum]] | |
| − | + | * Science: | |
| − | * | ||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
** [[Agriculture]] | ** [[Agriculture]] | ||
** [[Animal Ecology]] | ** [[Animal Ecology]] | ||
| − | ** [[ | + | ** [[Archaeology]] |
| + | *** [[Paleontology]] | ||
| + | ** [[Genealogy]] | ||
| + | ** [[Bioinformatics]] | ||
** [[Chemistry]] | ** [[Chemistry]] | ||
| − | ** [[ | + | ** [[Environmental Science]] |
| + | ** [[Geology: Mining, Oil & Gas]] | ||
** [[Healthcare]] | ** [[Healthcare]] | ||
| + | *** [[Pharmaceuticals]] | ||
| + | **** [[Drug Discovery]] | ||
| + | ***** [[Protein Folding & Discovery]] | ||
*** [[Psychology - Mental Health]] | *** [[Psychology - Mental Health]] | ||
| − | *** [[ | + | ** [[Life Sciences]] |
| + | ** [[Materials]] | ||
| + | ** [[Meteorology]] | ||
| + | ** [[Physics]] | ||
| + | ** [[Seismology]] | ||
| + | ** [[Aerospace]] | ||
| + | ** [[Astronomy]] | ||
| + | *** [[Satellite#Satellite Imagery|Satellite Imagery]] | ||
* [[Real Estate]] | * [[Real Estate]] | ||
| − | * [[ | + | * [[Architecture and Interior Design]] |
* [[Construction]] | * [[Construction]] | ||
* [[Smart Cities]] | * [[Smart Cities]] | ||
* [[Transportation (Autonomous Vehicles)]] | * [[Transportation (Autonomous Vehicles)]] | ||
| − | * | + | * [[Robotics]] |
| − | * [[Logistics]] | + | * [[Supply Chain]] ... [[Supply Chain#Logistics|Logistics]] ... [[Supply Chain#Warehousing|Warehousing]] ... [[Supply Chain#Retail|Retail]] |
| − | + | * Software [[Development]] | |
| − | + | * [[Computer Networks]] | |
| − | * | ||
| − | |||
* [[Telecommunications]] | * [[Telecommunications]] | ||
| + | ** [[AI Generated Broadcast Content#Television (TV)|Television (TV)]] | ||
* [[Power (Management)]] | * [[Power (Management)]] | ||
** [[Nuclear Fusion]] | ** [[Nuclear Fusion]] | ||
* [[Resources & Utilities]] | * [[Resources & Utilities]] | ||
* [[Operations & Maintenance]] | * [[Operations & Maintenance]] | ||
| − | * [ | + | * [[Requirements Management]] |
| − | |||
| − | |||
* [[Enterprise Architecture (EA)]] | * [[Enterprise Architecture (EA)]] | ||
* [[Risk, Compliance and Regulation]] | * [[Risk, Compliance and Regulation]] | ||
| Line 88: | Line 136: | ||
** [[Cybersecurity]] | ** [[Cybersecurity]] | ||
* [[Law]] | * [[Law]] | ||
| + | ** [[Law Enforcement]] | ||
| + | * [[Economics]] | ||
| + | * [[Finance & Accounting]] | ||
* [[Banking]] | * [[Banking]] | ||
| − | |||
* [[Insurance]] | * [[Insurance]] | ||
| − | * [ | + | * [[Strategy & Tactics#Business Strategy/Consulting|Business Strategy/Consulting]] |
| − | * [[ | + | * [[Politics]] |
* [[Government Services]] | * [[Government Services]] | ||
| − | * [[Defense]] | + | ** [[National Institute of Standards and Technology (NIST)]] |
| − | * [ | + | ** [[U.S. Department of Homeland Security (DHS)]] |
| + | ** [[Defense]] | ||
| + | |||
| + | == Consumer Products == | ||
| + | |||
| + | * [https://www.nature.com/articles/s41415-019-0551-9 A revolutionary toothbrush with artificial intelligence | British Dental Journal - Nature, 2019] | ||
| + | |||
| + | == Analysts' Lists == | ||
| + | |||
| + | <!-- MAINTENANCE NOTE: the images below are hot-linked from third-party CDNs (Medium, Pinterest). | ||
| + | They may break without warning and carry no source attribution or date. | ||
| + | Recommend re-hosting locally via Special:Upload with a caption naming the analyst, | ||
| + | publication, and year for each. --> | ||
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| + | https://cdn-images-1.medium.com/max/1000/1*ga8VI5-nLXjzdwAZ8JPDcw.png | ||
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| + | https://cdn-images-1.medium.com/max/800/1*dC383HXyeEcc0xTFOakwHg.jpeg | ||
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| − | + | https://cdn-images-1.medium.com/max/800/1*dovmtW8dkSASQCFaUV1t7A.jpeg | |
| − | + | https://cdn-images-1.medium.com/max/800/1*3B9-ZnqgivZtUsQfHWsJlA.jpeg | |
| + | https://cdn-images-1.medium.com/max/800/1*jYO-1Phyv4f6FajbROs85Q.jpeg | ||
| − | + | https://cdn-images-1.medium.com/max/800/1*3tfxkkQNeDNUGFvVAMZ3yg.jpeg | |
| − | + | https://cdn-images-1.medium.com/max/800/1*r1MY6AbJMxYiN3A2wLc-ww.jpeg | |
| − | + | https://cdn-images-1.medium.com/max/800/1*P8K1oaGZIy5oAkr2RB1yIQ.jpeg | |
| − | + | https://cdn-images-1.medium.com/max/800/1*MctFSavN05ZQm7wa5bS1yg.jpeg | |
| − | + | https://cdn-images-1.medium.com/max/800/1*L_yobuaENnrKjZES8unrUA.jpeg | |
| − | + | https://cdn-images-1.medium.com/max/800/1*FkPVs3IbZ36M9CEhtcewHA.jpeg | |
| − | + | https://cdn-images-1.medium.com/max/800/1*t1IPrwYLlEYH2HW831n3og.jpeg | |
| − | + | https://i.pinimg.com/originals/ab/90/09/ab90093dfdbcb08f3cacd7ffed61349e.png | |
| − | + | == <span id="Identifying AI Use Cases"></span>Identifying AI Use Cases == | |
| + | * [[How do I leverage Artificial Intelligence (AI)?#Example Patterns to Leverage|Example Patterns to Leverage]] | ||
| − | + | <hr><center><b><i> | |
| − | + | If a typical person can do a mental task with less than one second of thought, we can automate it using AI …</i></b> - Andrew Ng | |
| − | + | </center><hr> | |
| − | + | ''The sessions below date from 2018–2020 and predate generative AI. The selection frameworks — problem-type matching, data-readiness assessment, portfolio prioritization — transfer well; the technology examples do not.'' | |
| − | + | {|<!-- T --> | |
| + | | valign="top" | | ||
| + | {| class="wikitable" style="width: 550px;" | ||
| + | || | ||
| + | <youtube>fUiezSdnYZ0</youtube> | ||
| + | <b>MIT Bootcamps: How to identify business opportunities with AI | ||
| + | </b><br>AI is a fundamental, transformative technology like the microprocessor or the Internet. In the coming decades it will impact nearly all aspects of business. Unfortunately, few good resources exist for our future business leaders to learn about practical AI solutions and how to integrate them into their businesses. This is a E-Seminar for interested individuals to (1) understand how AI can generate revenue in business applications; (2) identify and develop AI use cases within your business environments; and (3) mitigate risks on any new AI initiative. By the end of this session, you will be able to put these new skills to immediate use at your company or startup. This is a business skills training and not a technical training. Participants won’t learn how to build a neural network or perform feature engineering. Instead, they will learn how to use fundamental AI concepts such as training data, machine learning, deep learning in customer conversations and proposals. They will learn how to identify emerging business opportunities for AI solutions like computer vision and natural language processing. | ||
| + | |} | ||
| + | |<!-- M --> | ||
| + | | valign="top" | | ||
| + | {| class="wikitable" style="width: 550px;" | ||
| + | || | ||
| + | <youtube>XZBxx6nPEj4</youtube> | ||
| + | <b>How To Identify AI/ML Use Cases | ||
| + | </b><br>How do you identify AI/ML use cases in your company? | ||
| − | + | 1. Assess internal products and business processes. | |
| + | 2. Enhance B2C software and hardware products. | ||
| + | 3. Explore B2B products and AI consulting. | ||
| − | + | If you know where to look and what questions to ask, you will develop the skill and intuition of AI/ML opportunity assessment. If you believe artificial intelligence is the future and you want to capitalize on the new career growth opportunities, consider breaking into AI through the non-technical career path. | |
| + | |} | ||
| + | |}<!-- B --> | ||
| + | {|<!-- T --> | ||
| + | | valign="top" | | ||
| + | {| class="wikitable" style="width: 550px;" | ||
| + | || | ||
| + | <youtube>VQ0IYbfM8pg</youtube> | ||
| + | <b>Applying AI to Real World Use Cases - MIT AI Conference 2019 | ||
| + | </b><br>Julie Choi - Intel Corporation, VP of Artificial Intelligence Products and Research Marketing. The 2019 MIT AI Conference, the 3rd edition of this annual conference, focused on the Future of Computing - the rise of Artificial Intelligence and how innovators are leveraging AI to drive new use cases and achieve better outcomes across industries. | ||
| + | |} | ||
| + | |<!-- M --> | ||
| + | | valign="top" | | ||
| + | {| class="wikitable" style="width: 550px;" | ||
| + | || | ||
| + | <youtube>eTNRWtfCm4Q</youtube> | ||
| + | <b>Identifying Machine Learning Use Cases | ||
| + | </b><br>In this Video we will see how to identify good candidates for machine learning. Machine learning is not a solution for all problem. If problem can be solved with simpler techniques like rules or statistics that must be the way to go. But there are reason where simple techniques might not be effective or hard to manage and maintain in this rapidly evolving data space as well as in big data era | ||
| + | |} | ||
| + | |}<!-- B --> | ||
| + | {|<!-- T --> | ||
| + | | valign="top" | | ||
| + | {| class="wikitable" style="width: 550px;" | ||
| + | || | ||
| + | <youtube>jNP1lbDIzyY</youtube> | ||
| + | <b>AI Simplified: What Makes a Good Machine Learning Use Case? | ||
| + | </b><br>Hear from Jake Shaver, Director of Strategic Initiatives, as he walks through a checklist of steps to help you determine a good machine learning use case for your specific organization. | ||
| + | |} | ||
| + | |<!-- M --> | ||
| + | | valign="top" | | ||
| + | {| class="wikitable" style="width: 550px;" | ||
| + | || | ||
| + | <youtube>9nuJdj4Pfqs</youtube> | ||
| + | <b>MFML 003 - Advice for finding AI use cases | ||
| + | </b><br>Cassie Kozyrkov. Welcome to a machine learning course for everyone! This video features a neat trick for finding an AI/ML use case. | ||
| + | |} | ||
| + | |}<!-- B --> | ||
| + | {|<!-- T --> | ||
| + | | valign="top" | | ||
| + | {| class="wikitable" style="width: 550px;" | ||
| + | || | ||
| + | <youtube>AGKAjiXwSaA</youtube> | ||
| + | <b>From Industrial AI Ambition to Operational Reality: Choosing the Right Use Cases | ||
| + | </b><br>OpenAI's GPT-6 Astra jumped from 18% to 41% on a real workplace task automation benchmark in just 8 weeks, yet 41% still means the AI makes more mistakes than it gets right. Maddie Zeng of NeoAI explains why that gap matters: if a vendor promises high precision across everything, the best funded labs on earth are publishing numbers that say otherwise. The panel maps out what has changed in industrial AI, from sensor monitoring to autonomous closed-loop decision making, and what traps wait between a successful pilot and a production deployment. | ||
| + | |} | ||
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| + | {| class="wikitable" style="width: 550px;" | ||
| + | || | ||
| + | <youtube>0L2wFPfVkz8</youtube> | ||
| + | <b>AI Use Cases Pattern Across Industries | ||
| + | </b><br>“It’s really challenging to identify AI/ML use cases. How to identify?” A project manager asked this question. I said – “the easiest way to find opportunity is to look for common patterns across industries.” | ||
| + | |} | ||
| + | |}<!-- B --> | ||
Latest revision as of 13:48, 19 September 2026
YouTube ... Quora ...Google search ...Google News ...Bing News
- Conversational AI ... ChatGPT | OpenAI ... Gemini | Google ... Claude | Anthropic ... Bing/Copilot | Microsoft ... Siri | Apple ... Meta ... Perplexity ... You ... phind ... Grok | xAI ... Groq ... Ernie | Baidu ... DeepSeek ... Alibaba
This page indexes real-world deployments of AI — what organizations actually built, what it cost them, and what it returned. Use the libraries below for documented implementations, and the industry index further down to jump to PRIMO.ai coverage of a specific domain.
Case Study Libraries
Searchable collections of documented, named-organization deployments.
- AI Use Case & Case Study Library | Best Practice AI ... The largest curated collection of its kind — 1,171 case studies and 972+ validated use cases, filterable by 40+ industries and 18+ business functions. Each case study links to the generalized use-case pattern behind it. Start here.
- Real-world gen AI use cases from the world's leading organizations | Google Cloud ... Named-customer deployments organized by 11 industry groups and six Agent types (Customer, Employee, Creative, Code, Data, Security). First published April 2024 and expanded repeatedly since; check the "last updated" stamp, as the count grows with each Cloud Next.
- 101 real-world gen AI use cases with technical blueprints | Google Cloud ... The engineering companion to the above: architectural patterns and reference tech stacks for each scenario, across 10 industry groups.
- AI Tools Use Cases | TopAI.tools ... 333 task-level themes across business, personal, and digital categories. A tool directory rather than a case-study library — useful for "what software does this," not "who deployed it and what happened."
- Applications of Artificial Intelligence | Wikipedia ... Broad, well-cited survey of application domains.
Research & Benchmarks
For adoption rates, investment figures, and measured outcomes rather than individual deployments.
- The 2026 AI Index Report | Stanford HAI ... Ninth edition, 400+ pages across nine chapters (R&D, Technical Performance, Responsible AI, Economy, Science, Medicine, Education, Policy, Public Opinion). The standard neutral reference for AI adoption and economic-impact data.
- The Artificial Intelligence Database | Wired ... Ongoing journalism on AI deployments and their consequences.
Historical (pre-generative AI)
Retained for the analytical frameworks, which hold up better than the specific examples. Treat the company examples as period documents.
- Notes from the AI frontier: Applications and value of deep learning | McKinsey Global Institute, April 2018 ... Maps AI techniques to eight problem types (classification, continuous estimation, clustering, optimization, anomaly detection, ranking, recommendations, data generation) across 400+ use cases in 19 industries and nine business functions. The problem-type taxonomy remains the most useful part.
- Deep Learning, Machine Learning & AI Use Cases | Chris Nicholson, Pathmind A.I. Wiki ... Concise mapping of deep-learning capabilities to sectors. Site is no longer maintained (last copyright 2023).
- 15 Business Applications For Artificial Intelligence And Machine Learning | Forbes Technology Council, September 2018 ... Practitioner accounts from 15 CIOs and CTOs. Note that Forbes CommunityVoice is fee-based membership content, not editorial reporting.
What challenge(s) can your AI investment solve?
- increase revenue (marketing)
- more competitive (gain capability)
- increase performance (detection, automation, discovery)
- reduce costs (optimization, predictive maintenance, reduce inventory)
- time reduction
- provide personalization (recommendations)
- avoid risk of non-compliance
- better communication (user interface, natural-language understanding, Telecommunications)
- broader and better integration (Internet of Things (IoT), smart cities)
- or other outcome(s) such as below...
Industry & Domain Index
- Market Trading
- Sports
- Gaming
- Toys
- Social Science
- Journalism/News
- Marketing
- Religion
- Education
- Art
- Music
- Photography
- Video & Movie Entertainment
- Writing/Publishing
- Fashion
- Fabrics & Textiles
- Project Management
- Client Engagement
- Human Resources (HR)
- Personal Productivity
- Language
- Travel & Tourism
- Hospitality, Food, and Spirits
- Quantum
- Science:
- Real Estate
- Architecture and Interior Design
- Construction
- Smart Cities
- Transportation (Autonomous Vehicles)
- Robotics
- Supply Chain ... Logistics ... Warehousing ... Retail
- Software Development
- Computer Networks
- Telecommunications
- Power (Management)
- Resources & Utilities
- Operations & Maintenance
- Requirements Management
- Enterprise Architecture (EA)
- Risk, Compliance and Regulation
- Law
- Economics
- Finance & Accounting
- Banking
- Insurance
- Business Strategy/Consulting
- Politics
- Government Services
Consumer Products
Analysts' Lists
Identifying AI Use Cases
If a typical person can do a mental task with less than one second of thought, we can automate it using AI … - Andrew Ng
The sessions below date from 2018–2020 and predate generative AI. The selection frameworks — problem-type matching, data-readiness assessment, portfolio prioritization — transfer well; the technology examples do not.
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