Ce diaporama a bien été signalé.
Le téléchargement de votre SlideShare est en cours. ×

Imagining Intelligent Information Machines for 2020

Publicité
Publicité
Publicité
Publicité
Publicité
Publicité
Publicité
Publicité
Publicité
Publicité
Publicité
Publicité
Chargement dans…3
×

Consultez-les par la suite

1 sur 33 Publicité

Imagining Intelligent Information Machines for 2020

Télécharger pour lire hors ligne

A Strategic Roadmap for Artificial Intelligence in Social Sector considering the challenges and constraints of 2020. A survey of global reference case studies, key pillars, maturity models, growth markets, revenue projections, use cases etc.

A Strategic Roadmap for Artificial Intelligence in Social Sector considering the challenges and constraints of 2020. A survey of global reference case studies, key pillars, maturity models, growth markets, revenue projections, use cases etc.

Publicité
Publicité

Plus De Contenu Connexe

Diaporamas pour vous (20)

Similaire à Imagining Intelligent Information Machines for 2020 (20)

Publicité

Plus par Gokul Alex (20)

Plus récents (20)

Publicité

Imagining Intelligent Information Machines for 2020

  1. 1. Imaging Intelligent Information Machines AI Strategy Blueprint 2020
  2. 2. Pillars of AI Strategy Interdisciplinary data science team Robust data strategy Robust data ecosystem Established business processes Commitment to IT best practices High risk tolerance Experimental thinking
  3. 3. Benefits of AI Creating New Products and Services Increasing Workforce Productivity Winning more market share Better Customer Segmentation Better Business Intelligence Efficient Business Models
  4. 4. AI Revenue Projections
  5. 5. Growth Markets for AI Asia Pacific North America Western Europe Middle East
  6. 6. Top Challenges Skills of Staff Data Quality Data Relevance Use Case Clarity Integration Complexity
  7. 7. AI Maturity Model Awareness in AI Activism in AI Vitality in AI Operationalising AI Systems of AI Transformations through AI
  8. 8. Phase Wise Approach Phase 1 : Data Strategy Phase 2: Service Incubation Phase 3 : Pilot Deployments Phase 4: Product Incubation Phase 5: Product Deployment Phase 6: Platform Engineering Phase 7: Ecosystem Integration
  9. 9. What problems do we want to solve through AI ? Data Deluge Content Clutter Information loss Rule Ambiguity Lack of Optimisation Lack of Efficiency
  10. 10. Top 10 AI Use Cases Contract / Agreement Analysis Object Detection & Navigation Objects from Geospatial Images Image Search Engines Predictive Maintenance Image Classification & Tagging Algorithmic Trading Strategy
  11. 11. Long Term Objectives Developing Smarter Products and Services Making Business Processes and Functions Intelligent Automating Repetitive and Mundane Tasks Automating Manufacturing Processes
  12. 12. Required Capabilities Conversational AI Recommendation Systems Anomaly Detection Systems Speech Recognition Systems Image Processing Systems Video Analytics Systems
  13. 13. Roadmap for AI Assisted Intelligence Augmented Intelligence Autonomous Intelligence
  14. 14. AI Priority Sectors Travel, Transportation & Logistics Retail, FMCG & Supply Chain Chemical & Petroleum Media & Entertainment Construction Agriculture Financial Services Public Sector
  15. 15. Business Value of AI Public Sector - 0.2 Trillion ( 9 % ) Banking - 0.3 Trillion ( 4 % ) Construction - 0.2 Trillion ( 2%) Oil & Gas - 0.2 Trillion ( 1.8 % ) Agriculture - 0.1 Trillion ( 3 % )
  16. 16. AI landscape in India Good Consumer Awareness Good Consumer Readiness Growing StartUp Ecosystem Early Adoption Businesses Great Government Support Access to Data Sets
  17. 17. AI & Industry Growth Agriculture Manufacturing Social Services Public Services Education Food Services
  18. 18. Global Use Cases Intrusion Detection Systems for Cyber Security Operation Centers Anomaly Detection in Audit and Assurance services in Government Runbook Automation for Banking and Financial Services Automation of Vendor Evaluation Automated Auction Systems
  19. 19. AI for B2B & B2C AI for Product Development ● Predictive Maintenance ● Supply Chain Optimisation ● Operation Optimisation ● Asset Management AI for App Development ● Billing Management ● Fraud Detection ● Customer Authentication ● HR Management
  20. 20. AI Use Cases for Social Sector Workflow Optimisation for Agriculture Workflows Predictive Maintenance for Agriculture Machinery Personalisation for Finance Engineering Analytics for Manufacturing Industry Operational Analytics for Construction Industry Recommendation Systems for Educational Platforms
  21. 21. Chatbot Use Cases Emergency Response Production Support Customer Service Bill Payment Hotel Reservation Purchase Assistant Learning Assistant
  22. 22. AI IoT Convergence Sensor Fusion through AI Sensor Modelling through AI Sensor Analytics through AI Sensor Optimisation through AI
  23. 23. AI & Cybersecurity AI for Biometric Pattern Recognition AI for Malware Threat Detection AI for Digital Forensics AI based Authentication Frameworks
  24. 24. Next Steps ● AI Action Plan ● AI Methodology ● AI Reference Architecture ● AI Ecosystem ● AI Task Force ● AI Solution Accelerators ● AI Sales Accelerators ● AI Delivery Accelerators ● Skill Gap Analysis ● SWOT Analysis
  25. 25. Appendix
  26. 26. Emerging Use Cases Medical Image Classification Automated Insurance Claims Self Navigating Drones Autonomous Mining Legal Advisors Decentralized Data Marketplaces
  27. 27. AI Policies Across the Globe - A Reference
  28. 28. An AI Ops Framework
  29. 29. An AI Deployment Reference Model - PwC
  30. 30. An AI first Enterprise Model - Google
  31. 31. An AI Product Strategy Reference - Amazon
  32. 32. References https://sloanreview.mit.edu/tag/artificial-intelligence-business-strategy/ http://www3.weforum.org/docs/WEF_National_AI_Strategy.pdf https://towardsdatascience.com/ultimate-ai-strategy-guide-9bfb5e9ecf4e https://towardsdatascience.com/ultimate-ai-strategy-guide-9bfb5e9ecf4e https://sloanreview.mit.edu/article/five-management-strategies-for-getting-the-most-from-ai/

×